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| author | jan.nijtmans <nijtmans@users.sourceforge.net> | 2017-08-30 11:20:19 (GMT) |
|---|---|---|
| committer | jan.nijtmans <nijtmans@users.sourceforge.net> | 2017-08-30 11:20:19 (GMT) |
| commit | d1a565fde90f8805d8e50073455049f92bef1d43 (patch) | |
| tree | ebb1443471f7f12938ec55ce3b4a7f5ead28c781 /libtommath | |
| parent | 3a2a78a48a0eeea16928dca431306167ed6cddaa (diff) | |
| download | tcl-d1a565fde90f8805d8e50073455049f92bef1d43.zip tcl-d1a565fde90f8805d8e50073455049f92bef1d43.tar.gz tcl-d1a565fde90f8805d8e50073455049f92bef1d43.tar.bz2 | |
Cherry-pick [https://github.com/libtom/libtommath/commit/a0a86c696a7182f8be4b10bb79a1c5c971dc9561]: Merge branch 'tcl-fixes' into develop
Remove many files, which are not used in Tcl.
Modify "changelog.txt", with real release-date of 1.0.1 version
Diffstat (limited to 'libtommath')
81 files changed, 126 insertions, 44141 deletions
diff --git a/libtommath/bn.ilg b/libtommath/bn.ilg deleted file mode 100644 index 2a14624..0000000 --- a/libtommath/bn.ilg +++ /dev/null @@ -1,6 +0,0 @@ -This is makeindex, version 2.15 [TeX Live 2013] (kpathsea + Thai support). -Scanning input file bn.idx....done (85 entries accepted, 0 rejected). -Sorting entries....done (554 comparisons). -Generating output file bn.ind....done (88 lines written, 0 warnings). -Output written in bn.ind. -Transcript written in bn.ilg. diff --git a/libtommath/bn.ind b/libtommath/bn.ind deleted file mode 100644 index 01cff1a..0000000 --- a/libtommath/bn.ind +++ /dev/null @@ -1,88 +0,0 @@ -\begin{theindex} - - \item mp\_add, \hyperpage{24} - \item mp\_add\_d, \hyperpage{44} - \item mp\_and, \hyperpage{24} - \item mp\_clear, \hyperpage{9} - \item mp\_clear\_multi, \hyperpage{10} - \item mp\_cmp, \hyperpage{19} - \item mp\_cmp\_d, \hyperpage{20} - \item mp\_cmp\_mag, \hyperpage{18} - \item mp\_div, \hyperpage{24} - \item mp\_div\_2, \hyperpage{22} - \item mp\_div\_2d, \hyperpage{23} - \item mp\_div\_d, \hyperpage{44} - \item mp\_dr\_reduce, \hyperpage{33} - \item mp\_dr\_setup, \hyperpage{33} - \item MP\_EQ, \hyperpage{18} - \item mp\_error\_to\_string, \hyperpage{7} - \item mp\_expt\_d, \hyperpage{35} - \item mp\_expt\_d\_ex, \hyperpage{35} - \item mp\_exptmod, \hyperpage{35} - \item mp\_exteuclid, \hyperpage{43} - \item mp\_gcd, \hyperpage{43} - \item mp\_get\_int, \hyperpage{16} - \item mp\_get\_long, \hyperpage{17} - \item mp\_get\_long\_long, \hyperpage{17} - \item mp\_grow, \hyperpage{13} - \item MP\_GT, \hyperpage{18} - \item mp\_init, \hyperpage{8} - \item mp\_init\_copy, \hyperpage{10} - \item mp\_init\_multi, \hyperpage{10} - \item mp\_init\_set, \hyperpage{17} - \item mp\_init\_set\_int, \hyperpage{17} - \item mp\_init\_size, \hyperpage{11} - \item mp\_int, \hyperpage{8} - \item mp\_invmod, \hyperpage{44} - \item mp\_jacobi, \hyperpage{43} - \item mp\_lcm, \hyperpage{43} - \item mp\_lshd, \hyperpage{23} - \item MP\_LT, \hyperpage{18} - \item MP\_MEM, \hyperpage{7} - \item mp\_mod, \hyperpage{29} - \item mp\_mod\_d, \hyperpage{44} - \item mp\_montgomery\_calc\_normalization, \hyperpage{31} - \item mp\_montgomery\_reduce, \hyperpage{31} - \item mp\_montgomery\_setup, \hyperpage{31} - \item mp\_mul, \hyperpage{25} - \item mp\_mul\_2, \hyperpage{22} - \item mp\_mul\_2d, \hyperpage{23} - \item mp\_mul\_d, \hyperpage{44} - \item mp\_n\_root, \hyperpage{36} - \item mp\_neg, \hyperpage{24} - \item MP\_NO, \hyperpage{7} - \item MP\_OKAY, \hyperpage{7} - \item mp\_or, \hyperpage{24} - \item mp\_prime\_fermat, \hyperpage{37} - \item mp\_prime\_is\_divisible, \hyperpage{37} - \item mp\_prime\_is\_prime, \hyperpage{38} - \item mp\_prime\_miller\_rabin, \hyperpage{37} - \item mp\_prime\_next\_prime, \hyperpage{38} - \item mp\_prime\_rabin\_miller\_trials, \hyperpage{38} - \item mp\_prime\_random, \hyperpage{38} - \item mp\_prime\_random\_ex, \hyperpage{39} - \item mp\_radix\_size, \hyperpage{41} - \item mp\_read\_radix, \hyperpage{41} - \item mp\_read\_unsigned\_bin, \hyperpage{42} - \item mp\_reduce, \hyperpage{30} - \item mp\_reduce\_2k, \hyperpage{34} - \item mp\_reduce\_2k\_setup, \hyperpage{34} - \item mp\_reduce\_setup, \hyperpage{29} - \item mp\_rshd, \hyperpage{23} - \item mp\_set, \hyperpage{15} - \item mp\_set\_int, \hyperpage{16} - \item mp\_set\_long, \hyperpage{17} - \item mp\_set\_long\_long, \hyperpage{17} - \item mp\_shrink, \hyperpage{12} - \item mp\_sqr, \hyperpage{26} - \item mp\_sqrtmod\_prime, \hyperpage{44} - \item mp\_sub, \hyperpage{24} - \item mp\_sub\_d, \hyperpage{44} - \item mp\_to\_unsigned\_bin, \hyperpage{42} - \item mp\_toradix, \hyperpage{41} - \item mp\_unsigned\_bin\_size, \hyperpage{41} - \item MP\_VAL, \hyperpage{7} - \item mp\_xor, \hyperpage{24} - \item MP\_YES, \hyperpage{7} - -\end{theindex} diff --git a/libtommath/bn.pdf b/libtommath/bn.pdf Binary files differdeleted file mode 100644 index a1f40ef..0000000 --- a/libtommath/bn.pdf +++ /dev/null diff --git a/libtommath/bn.tex b/libtommath/bn.tex deleted file mode 100644 index d975471..0000000 --- a/libtommath/bn.tex +++ /dev/null @@ -1,1913 +0,0 @@ -\documentclass[synpaper]{book} -\usepackage{hyperref} -\usepackage{makeidx} -\usepackage{amssymb} -\usepackage{color} -\usepackage{alltt} -\usepackage{graphicx} -\usepackage{layout} -\def\union{\cup} -\def\intersect{\cap} -\def\getsrandom{\stackrel{\rm R}{\gets}} -\def\cross{\times} -\def\cat{\hspace{0.5em} \| \hspace{0.5em}} -\def\catn{$\|$} -\def\divides{\hspace{0.3em} | \hspace{0.3em}} -\def\nequiv{\not\equiv} -\def\approx{\raisebox{0.2ex}{\mbox{\small $\sim$}}} -\def\lcm{{\rm lcm}} -\def\gcd{{\rm gcd}} -\def\log{{\rm log}} -\def\ord{{\rm ord}} -\def\abs{{\mathit abs}} -\def\rep{{\mathit rep}} -\def\mod{{\mathit\ mod\ }} -\renewcommand{\pmod}[1]{\ ({\rm mod\ }{#1})} -\newcommand{\floor}[1]{\left\lfloor{#1}\right\rfloor} -\newcommand{\ceil}[1]{\left\lceil{#1}\right\rceil} -\def\Or{{\rm\ or\ }} -\def\And{{\rm\ and\ }} -\def\iff{\hspace{1em}\Longleftrightarrow\hspace{1em}} -\def\implies{\Rightarrow} -\def\undefined{{\rm ``undefined"}} -\def\Proof{\vspace{1ex}\noindent {\bf Proof:}\hspace{1em}} -\let\oldphi\phi -\def\phi{\varphi} -\def\Pr{{\rm Pr}} -\newcommand{\str}[1]{{\mathbf{#1}}} -\def\F{{\mathbb F}} -\def\N{{\mathbb N}} -\def\Z{{\mathbb Z}} -\def\R{{\mathbb R}} -\def\C{{\mathbb C}} -\def\Q{{\mathbb Q}} -\definecolor{DGray}{gray}{0.5} -\newcommand{\emailaddr}[1]{\mbox{$<${#1}$>$}} -\def\twiddle{\raisebox{0.3ex}{\mbox{\tiny $\sim$}}} -\def\gap{\vspace{0.5ex}} -\makeindex -\begin{document} -\frontmatter -\pagestyle{empty} -\title{LibTomMath User Manual \\ v1.0.0} -\author{Tom St Denis \\ tstdenis82@gmail.com} -\maketitle -This text, the library and the accompanying textbook are all hereby placed in the public domain. This book has been -formatted for B5 [176x250] paper using the \LaTeX{} {\em book} macro package. - -\vspace{10cm} - -\begin{flushright}Open Source. Open Academia. Open Minds. - -\mbox{ } - -Tom St Denis, - -Ontario, Canada -\end{flushright} - -\tableofcontents -\listoffigures -\mainmatter -\pagestyle{headings} -\chapter{Introduction} -\section{What is LibTomMath?} -LibTomMath is a library of source code which provides a series of efficient and carefully written functions for manipulating -large integer numbers. It was written in portable ISO C source code so that it will build on any platform with a conforming -C compiler. - -In a nutshell the library was written from scratch with verbose comments to help instruct computer science students how -to implement ``bignum'' math. However, the resulting code has proven to be very useful. It has been used by numerous -universities, commercial and open source software developers. It has been used on a variety of platforms ranging from -Linux and Windows based x86 to ARM based Gameboys and PPC based MacOS machines. - -\section{License} -As of the v0.25 the library source code has been placed in the public domain with every new release. As of the v0.28 -release the textbook ``Implementing Multiple Precision Arithmetic'' has been placed in the public domain with every new -release as well. This textbook is meant to compliment the project by providing a more solid walkthrough of the development -algorithms used in the library. - -Since both\footnote{Note that the MPI files under mtest/ are copyrighted by Michael Fromberger. They are not required to use LibTomMath.} are in the -public domain everyone is entitled to do with them as they see fit. - -\section{Building LibTomMath} - -LibTomMath is meant to be very ``GCC friendly'' as it comes with a makefile well suited for GCC. However, the library will -also build in MSVC, Borland C out of the box. For any other ISO C compiler a makefile will have to be made by the end -developer. - -\subsection{Static Libraries} -To build as a static library for GCC issue the following -\begin{alltt} -make -\end{alltt} - -command. This will build the library and archive the object files in ``libtommath.a''. Now you link against -that and include ``tommath.h'' within your programs. Alternatively to build with MSVC issue the following -\begin{alltt} -nmake -f makefile.msvc -\end{alltt} - -This will build the library and archive the object files in ``tommath.lib''. This has been tested with MSVC -version 6.00 with service pack 5. - -\subsection{Shared Libraries} -To build as a shared library for GCC issue the following -\begin{alltt} -make -f makefile.shared -\end{alltt} -This requires the ``libtool'' package (common on most Linux/BSD systems). It will build LibTomMath as both shared -and static then install (by default) into /usr/lib as well as install the header files in /usr/include. The shared -library (resource) will be called ``libtommath.la'' while the static library called ``libtommath.a''. Generally -you use libtool to link your application against the shared object. - -There is limited support for making a ``DLL'' in windows via the ``makefile.cygwin\_dll'' makefile. It requires -Cygwin to work with since it requires the auto-export/import functionality. The resulting DLL and import library -``libtommath.dll.a'' can be used to link LibTomMath dynamically to any Windows program using Cygwin. - -\subsection{Testing} -To build the library and the test harness type - -\begin{alltt} -make test -\end{alltt} - -This will build the library, ``test'' and ``mtest/mtest''. The ``test'' program will accept test vectors and verify the -results. ``mtest/mtest'' will generate test vectors using the MPI library by Michael Fromberger\footnote{A copy of MPI -is included in the package}. Simply pipe mtest into test using - -\begin{alltt} -mtest/mtest | test -\end{alltt} - -If you do not have a ``/dev/urandom'' style RNG source you will have to write your own PRNG and simply pipe that into -mtest. For example, if your PRNG program is called ``myprng'' simply invoke - -\begin{alltt} -myprng | mtest/mtest | test -\end{alltt} - -This will output a row of numbers that are increasing. Each column is a different test (such as addition, multiplication, etc) -that is being performed. The numbers represent how many times the test was invoked. If an error is detected the program -will exit with a dump of the relevent numbers it was working with. - -\section{Build Configuration} -LibTomMath can configured at build time in three phases we shall call ``depends'', ``tweaks'' and ``trims''. -Each phase changes how the library is built and they are applied one after another respectively. - -To make the system more powerful you can tweak the build process. Classes are defined in the file -``tommath\_superclass.h''. By default, the symbol ``LTM\_ALL'' shall be defined which simply -instructs the system to build all of the functions. This is how LibTomMath used to be packaged. This will give you -access to every function LibTomMath offers. - -However, there are cases where such a build is not optional. For instance, you want to perform RSA operations. You -don't need the vast majority of the library to perform these operations. Aside from LTM\_ALL there is -another pre--defined class ``SC\_RSA\_1'' which works in conjunction with the RSA from LibTomCrypt. Additional -classes can be defined base on the need of the user. - -\subsection{Build Depends} -In the file tommath\_class.h you will see a large list of C ``defines'' followed by a series of ``ifdefs'' -which further define symbols. All of the symbols (technically they're macros $\ldots$) represent a given C source -file. For instance, BN\_MP\_ADD\_C represents the file ``bn\_mp\_add.c''. When a define has been enabled the -function in the respective file will be compiled and linked into the library. Accordingly when the define -is absent the file will not be compiled and not contribute any size to the library. - -You will also note that the header tommath\_class.h is actually recursively included (it includes itself twice). -This is to help resolve as many dependencies as possible. In the last pass the symbol LTM\_LAST will be defined. -This is useful for ``trims''. - -\subsection{Build Tweaks} -A tweak is an algorithm ``alternative''. For example, to provide tradeoffs (usually between size and space). -They can be enabled at any pass of the configuration phase. - -\begin{small} -\begin{center} -\begin{tabular}{|l|l|} -\hline \textbf{Define} & \textbf{Purpose} \\ -\hline BN\_MP\_DIV\_SMALL & Enables a slower, smaller and equally \\ - & functional mp\_div() function \\ -\hline -\end{tabular} -\end{center} -\end{small} - -\subsection{Build Trims} -A trim is a manner of removing functionality from a function that is not required. For instance, to perform -RSA cryptography you only require exponentiation with odd moduli so even moduli support can be safely removed. -Build trims are meant to be defined on the last pass of the configuration which means they are to be defined -only if LTM\_LAST has been defined. - -\subsubsection{Moduli Related} -\begin{small} -\begin{center} -\begin{tabular}{|l|l|} -\hline \textbf{Restriction} & \textbf{Undefine} \\ -\hline Exponentiation with odd moduli only & BN\_S\_MP\_EXPTMOD\_C \\ - & BN\_MP\_REDUCE\_C \\ - & BN\_MP\_REDUCE\_SETUP\_C \\ - & BN\_S\_MP\_MUL\_HIGH\_DIGS\_C \\ - & BN\_FAST\_S\_MP\_MUL\_HIGH\_DIGS\_C \\ -\hline Exponentiation with random odd moduli & (The above plus the following) \\ - & BN\_MP\_REDUCE\_2K\_C \\ - & BN\_MP\_REDUCE\_2K\_SETUP\_C \\ - & BN\_MP\_REDUCE\_IS\_2K\_C \\ - & BN\_MP\_DR\_IS\_MODULUS\_C \\ - & BN\_MP\_DR\_REDUCE\_C \\ - & BN\_MP\_DR\_SETUP\_C \\ -\hline Modular inverse odd moduli only & BN\_MP\_INVMOD\_SLOW\_C \\ -\hline Modular inverse (both, smaller/slower) & BN\_FAST\_MP\_INVMOD\_C \\ -\hline -\end{tabular} -\end{center} -\end{small} - -\subsubsection{Operand Size Related} -\begin{small} -\begin{center} -\begin{tabular}{|l|l|} -\hline \textbf{Restriction} & \textbf{Undefine} \\ -\hline Moduli $\le 2560$ bits & BN\_MP\_MONTGOMERY\_REDUCE\_C \\ - & BN\_S\_MP\_MUL\_DIGS\_C \\ - & BN\_S\_MP\_MUL\_HIGH\_DIGS\_C \\ - & BN\_S\_MP\_SQR\_C \\ -\hline Polynomial Schmolynomial & BN\_MP\_KARATSUBA\_MUL\_C \\ - & BN\_MP\_KARATSUBA\_SQR\_C \\ - & BN\_MP\_TOOM\_MUL\_C \\ - & BN\_MP\_TOOM\_SQR\_C \\ - -\hline -\end{tabular} -\end{center} -\end{small} - - -\section{Purpose of LibTomMath} -Unlike GNU MP (GMP) Library, LIP, OpenSSL or various other commercial kits (Miracl), LibTomMath was not written with -bleeding edge performance in mind. First and foremost LibTomMath was written to be entirely open. Not only is the -source code public domain (unlike various other GPL/etc licensed code), not only is the code freely downloadable but the -source code is also accessible for computer science students attempting to learn ``BigNum'' or multiple precision -arithmetic techniques. - -LibTomMath was written to be an instructive collection of source code. This is why there are many comments, only one -function per source file and often I use a ``middle-road'' approach where I don't cut corners for an extra 2\% speed -increase. - -Source code alone cannot really teach how the algorithms work which is why I also wrote a textbook that accompanies -the library (beat that!). - -So you may be thinking ``should I use LibTomMath?'' and the answer is a definite maybe. Let me tabulate what I think -are the pros and cons of LibTomMath by comparing it to the math routines from GnuPG\footnote{GnuPG v1.2.3 versus LibTomMath v0.28}. - -\newpage\begin{figure}[here] -\begin{small} -\begin{center} -\begin{tabular}{|l|c|c|l|} -\hline \textbf{Criteria} & \textbf{Pro} & \textbf{Con} & \textbf{Notes} \\ -\hline Few lines of code per file & X & & GnuPG $ = 300.9$, LibTomMath $ = 71.97$ \\ -\hline Commented function prototypes & X && GnuPG function names are cryptic. \\ -\hline Speed && X & LibTomMath is slower. \\ -\hline Totally free & X & & GPL has unfavourable restrictions.\\ -\hline Large function base & X & & GnuPG is barebones. \\ -\hline Five modular reduction algorithms & X & & Faster modular exponentiation for a variety of moduli. \\ -\hline Portable & X & & GnuPG requires configuration to build. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{LibTomMath Valuation} -\end{figure} - -It may seem odd to compare LibTomMath to GnuPG since the math in GnuPG is only a small portion of the entire application. -However, LibTomMath was written with cryptography in mind. It provides essentially all of the functions a cryptosystem -would require when working with large integers. - -So it may feel tempting to just rip the math code out of GnuPG (or GnuMP where it was taken from originally) in your -own application but I think there are reasons not to. While LibTomMath is slower than libraries such as GnuMP it is -not normally significantly slower. On x86 machines the difference is normally a factor of two when performing modular -exponentiations. It depends largely on the processor, compiler and the moduli being used. - -Essentially the only time you wouldn't use LibTomMath is when blazing speed is the primary concern. However, -on the other side of the coin LibTomMath offers you a totally free (public domain) well structured math library -that is very flexible, complete and performs well in resource contrained environments. Fast RSA for example can -be performed with as little as 8KB of ram for data (again depending on build options). - -\chapter{Getting Started with LibTomMath} -\section{Building Programs} -In order to use LibTomMath you must include ``tommath.h'' and link against the appropriate library file (typically -libtommath.a). There is no library initialization required and the entire library is thread safe. - -\section{Return Codes} -There are three possible return codes a function may return. - -\index{MP\_OKAY}\index{MP\_YES}\index{MP\_NO}\index{MP\_VAL}\index{MP\_MEM} -\begin{figure}[here!] -\begin{center} -\begin{small} -\begin{tabular}{|l|l|} -\hline \textbf{Code} & \textbf{Meaning} \\ -\hline MP\_OKAY & The function succeeded. \\ -\hline MP\_VAL & The function input was invalid. \\ -\hline MP\_MEM & Heap memory exhausted. \\ -\hline &\\ -\hline MP\_YES & Response is yes. \\ -\hline MP\_NO & Response is no. \\ -\hline -\end{tabular} -\end{small} -\end{center} -\caption{Return Codes} -\end{figure} - -The last two codes listed are not actually ``return'ed'' by a function. They are placed in an integer (the caller must -provide the address of an integer it can store to) which the caller can access. To convert one of the three return codes -to a string use the following function. - -\index{mp\_error\_to\_string} -\begin{alltt} -char *mp_error_to_string(int code); -\end{alltt} - -This will return a pointer to a string which describes the given error code. It will not work for the return codes -MP\_YES and MP\_NO. - -\section{Data Types} -The basic ``multiple precision integer'' type is known as the ``mp\_int'' within LibTomMath. This data type is used to -organize all of the data required to manipulate the integer it represents. Within LibTomMath it has been prototyped -as the following. - -\index{mp\_int} -\begin{alltt} -typedef struct \{ - int used, alloc, sign; - mp_digit *dp; -\} mp_int; -\end{alltt} - -Where ``mp\_digit'' is a data type that represents individual digits of the integer. By default, an mp\_digit is the -ISO C ``unsigned long'' data type and each digit is $28-$bits long. The mp\_digit type can be configured to suit other -platforms by defining the appropriate macros. - -All LTM functions that use the mp\_int type will expect a pointer to mp\_int structure. You must allocate memory to -hold the structure itself by yourself (whether off stack or heap it doesn't matter). The very first thing that must be -done to use an mp\_int is that it must be initialized. - -\section{Function Organization} - -The arithmetic functions of the library are all organized to have the same style prototype. That is source operands -are passed on the left and the destination is on the right. For instance, - -\begin{alltt} -mp_add(&a, &b, &c); /* c = a + b */ -mp_mul(&a, &a, &c); /* c = a * a */ -mp_div(&a, &b, &c, &d); /* c = [a/b], d = a mod b */ -\end{alltt} - -Another feature of the way the functions have been implemented is that source operands can be destination operands as well. -For instance, - -\begin{alltt} -mp_add(&a, &b, &b); /* b = a + b */ -mp_div(&a, &b, &a, &c); /* a = [a/b], c = a mod b */ -\end{alltt} - -This allows operands to be re-used which can make programming simpler. - -\section{Initialization} -\subsection{Single Initialization} -A single mp\_int can be initialized with the ``mp\_init'' function. - -\index{mp\_init} -\begin{alltt} -int mp_init (mp_int * a); -\end{alltt} - -This function expects a pointer to an mp\_int structure and will initialize the members of the structure so the mp\_int -represents the default integer which is zero. If the functions returns MP\_OKAY then the mp\_int is ready to be used -by the other LibTomMath functions. - -\begin{small} \begin{alltt} -int main(void) -\{ - mp_int number; - int result; - - if ((result = mp_init(&number)) != MP_OKAY) \{ - printf("Error initializing the number. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* use the number */ - - return EXIT_SUCCESS; -\} -\end{alltt} \end{small} - -\subsection{Single Free} -When you are finished with an mp\_int it is ideal to return the heap it used back to the system. The following function -provides this functionality. - -\index{mp\_clear} -\begin{alltt} -void mp_clear (mp_int * a); -\end{alltt} - -The function expects a pointer to a previously initialized mp\_int structure and frees the heap it uses. It sets the -pointer\footnote{The ``dp'' member.} within the mp\_int to \textbf{NULL} which is used to prevent double free situations. -Is is legal to call mp\_clear() twice on the same mp\_int in a row. - -\begin{small} \begin{alltt} -int main(void) -\{ - mp_int number; - int result; - - if ((result = mp_init(&number)) != MP_OKAY) \{ - printf("Error initializing the number. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* use the number */ - - /* We're done with it. */ - mp_clear(&number); - - return EXIT_SUCCESS; -\} -\end{alltt} \end{small} - -\subsection{Multiple Initializations} -Certain algorithms require more than one large integer. In these instances it is ideal to initialize all of the mp\_int -variables in an ``all or nothing'' fashion. That is, they are either all initialized successfully or they are all -not initialized. - -The mp\_init\_multi() function provides this functionality. - -\index{mp\_init\_multi} \index{mp\_clear\_multi} -\begin{alltt} -int mp_init_multi(mp_int *mp, ...); -\end{alltt} - -It accepts a \textbf{NULL} terminated list of pointers to mp\_int structures. It will attempt to initialize them all -at once. If the function returns MP\_OKAY then all of the mp\_int variables are ready to use, otherwise none of them -are available for use. A complementary mp\_clear\_multi() function allows multiple mp\_int variables to be free'd -from the heap at the same time. - -\begin{small} \begin{alltt} -int main(void) -\{ - mp_int num1, num2, num3; - int result; - - if ((result = mp_init_multi(&num1, - &num2, - &num3, NULL)) != MP\_OKAY) \{ - printf("Error initializing the numbers. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* use the numbers */ - - /* We're done with them. */ - mp_clear_multi(&num1, &num2, &num3, NULL); - - return EXIT_SUCCESS; -\} -\end{alltt} \end{small} - -\subsection{Other Initializers} -To initialized and make a copy of an mp\_int the mp\_init\_copy() function has been provided. - -\index{mp\_init\_copy} -\begin{alltt} -int mp_init_copy (mp_int * a, mp_int * b); -\end{alltt} - -This function will initialize $a$ and make it a copy of $b$ if all goes well. - -\begin{small} \begin{alltt} -int main(void) -\{ - mp_int num1, num2; - int result; - - /* initialize and do work on num1 ... */ - - /* We want a copy of num1 in num2 now */ - if ((result = mp_init_copy(&num2, &num1)) != MP_OKAY) \{ - printf("Error initializing the copy. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* now num2 is ready and contains a copy of num1 */ - - /* We're done with them. */ - mp_clear_multi(&num1, &num2, NULL); - - return EXIT_SUCCESS; -\} -\end{alltt} \end{small} - -Another less common initializer is mp\_init\_size() which allows the user to initialize an mp\_int with a given -default number of digits. By default, all initializers allocate \textbf{MP\_PREC} digits. This function lets -you override this behaviour. - -\index{mp\_init\_size} -\begin{alltt} -int mp_init_size (mp_int * a, int size); -\end{alltt} - -The $size$ parameter must be greater than zero. If the function succeeds the mp\_int $a$ will be initialized -to have $size$ digits (which are all initially zero). - -\begin{small} \begin{alltt} -int main(void) -\{ - mp_int number; - int result; - - /* we need a 60-digit number */ - if ((result = mp_init_size(&number, 60)) != MP_OKAY) \{ - printf("Error initializing the number. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* use the number */ - - return EXIT_SUCCESS; -\} -\end{alltt} \end{small} - -\section{Maintenance Functions} - -\subsection{Reducing Memory Usage} -When an mp\_int is in a state where it won't be changed again\footnote{A Diffie-Hellman modulus for instance.} excess -digits can be removed to return memory to the heap with the mp\_shrink() function. - -\index{mp\_shrink} -\begin{alltt} -int mp_shrink (mp_int * a); -\end{alltt} - -This will remove excess digits of the mp\_int $a$. If the operation fails the mp\_int should be intact without the -excess digits being removed. Note that you can use a shrunk mp\_int in further computations, however, such operations -will require heap operations which can be slow. It is not ideal to shrink mp\_int variables that you will further -modify in the system (unless you are seriously low on memory). - -\begin{small} \begin{alltt} -int main(void) -\{ - mp_int number; - int result; - - if ((result = mp_init(&number)) != MP_OKAY) \{ - printf("Error initializing the number. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* use the number [e.g. pre-computation] */ - - /* We're done with it for now. */ - if ((result = mp_shrink(&number)) != MP_OKAY) \{ - printf("Error shrinking the number. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* use it .... */ - - - /* we're done with it. */ - mp_clear(&number); - - return EXIT_SUCCESS; -\} -\end{alltt} \end{small} - -\subsection{Adding additional digits} - -Within the mp\_int structure are two parameters which control the limitations of the array of digits that represent -the integer the mp\_int is meant to equal. The \textit{used} parameter dictates how many digits are significant, that is, -contribute to the value of the mp\_int. The \textit{alloc} parameter dictates how many digits are currently available in -the array. If you need to perform an operation that requires more digits you will have to mp\_grow() the mp\_int to -your desired size. - -\index{mp\_grow} -\begin{alltt} -int mp_grow (mp_int * a, int size); -\end{alltt} - -This will grow the array of digits of $a$ to $size$. If the \textit{alloc} parameter is already bigger than -$size$ the function will not do anything. - -\begin{small} \begin{alltt} -int main(void) -\{ - mp_int number; - int result; - - if ((result = mp_init(&number)) != MP_OKAY) \{ - printf("Error initializing the number. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* use the number */ - - /* We need to add 20 digits to the number */ - if ((result = mp_grow(&number, number.alloc + 20)) != MP_OKAY) \{ - printf("Error growing the number. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - - /* use the number */ - - /* we're done with it. */ - mp_clear(&number); - - return EXIT_SUCCESS; -\} -\end{alltt} \end{small} - -\chapter{Basic Operations} -\section{Small Constants} -Setting mp\_ints to small constants is a relatively common operation. To accomodate these instances there are two -small constant assignment functions. The first function is used to set a single digit constant while the second sets -an ISO C style ``unsigned long'' constant. The reason for both functions is efficiency. Setting a single digit is quick but the -domain of a digit can change (it's always at least $0 \ldots 127$). - -\subsection{Single Digit} - -Setting a single digit can be accomplished with the following function. - -\index{mp\_set} -\begin{alltt} -void mp_set (mp_int * a, mp_digit b); -\end{alltt} - -This will zero the contents of $a$ and make it represent an integer equal to the value of $b$. Note that this -function has a return type of \textbf{void}. It cannot cause an error so it is safe to assume the function -succeeded. - -\begin{small} \begin{alltt} -int main(void) -\{ - mp_int number; - int result; - - if ((result = mp_init(&number)) != MP_OKAY) \{ - printf("Error initializing the number. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* set the number to 5 */ - mp_set(&number, 5); - - /* we're done with it. */ - mp_clear(&number); - - return EXIT_SUCCESS; -\} -\end{alltt} \end{small} - -\subsection{Long Constants} - -To set a constant that is the size of an ISO C ``unsigned long'' and larger than a single digit the following function -can be used. - -\index{mp\_set\_int} -\begin{alltt} -int mp_set_int (mp_int * a, unsigned long b); -\end{alltt} - -This will assign the value of the 32-bit variable $b$ to the mp\_int $a$. Unlike mp\_set() this function will always -accept a 32-bit input regardless of the size of a single digit. However, since the value may span several digits -this function can fail if it runs out of heap memory. - -To get the ``unsigned long'' copy of an mp\_int the following function can be used. - -\index{mp\_get\_int} -\begin{alltt} -unsigned long mp_get_int (mp_int * a); -\end{alltt} - -This will return the 32 least significant bits of the mp\_int $a$. - -\begin{small} \begin{alltt} -int main(void) -\{ - mp_int number; - int result; - - if ((result = mp_init(&number)) != MP_OKAY) \{ - printf("Error initializing the number. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* set the number to 654321 (note this is bigger than 127) */ - if ((result = mp_set_int(&number, 654321)) != MP_OKAY) \{ - printf("Error setting the value of the number. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - printf("number == \%lu", mp_get_int(&number)); - - /* we're done with it. */ - mp_clear(&number); - - return EXIT_SUCCESS; -\} -\end{alltt} \end{small} - -This should output the following if the program succeeds. - -\begin{alltt} -number == 654321 -\end{alltt} - -\subsection{Long Constants - platform dependant} - -\index{mp\_set\_long} -\begin{alltt} -int mp_set_long (mp_int * a, unsigned long b); -\end{alltt} - -This will assign the value of the platform-dependant sized variable $b$ to the mp\_int $a$. - -To get the ``unsigned long'' copy of an mp\_int the following function can be used. - -\index{mp\_get\_long} -\begin{alltt} -unsigned long mp_get_long (mp_int * a); -\end{alltt} - -This will return the least significant bits of the mp\_int $a$ that fit into an ``unsigned long''. - -\subsection{Long Long Constants} - -\index{mp\_set\_long\_long} -\begin{alltt} -int mp_set_long_long (mp_int * a, unsigned long long b); -\end{alltt} - -This will assign the value of the 64-bit variable $b$ to the mp\_int $a$. - -To get the ``unsigned long long'' copy of an mp\_int the following function can be used. - -\index{mp\_get\_long\_long} -\begin{alltt} -unsigned long long mp_get_long_long (mp_int * a); -\end{alltt} - -This will return the 64 least significant bits of the mp\_int $a$. - -\subsection{Initialize and Setting Constants} -To both initialize and set small constants the following two functions are available. -\index{mp\_init\_set} \index{mp\_init\_set\_int} -\begin{alltt} -int mp_init_set (mp_int * a, mp_digit b); -int mp_init_set_int (mp_int * a, unsigned long b); -\end{alltt} - -Both functions work like the previous counterparts except they first mp\_init $a$ before setting the values. - -\begin{alltt} -int main(void) -\{ - mp_int number1, number2; - int result; - - /* initialize and set a single digit */ - if ((result = mp_init_set(&number1, 100)) != MP_OKAY) \{ - printf("Error setting number1: \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* initialize and set a long */ - if ((result = mp_init_set_int(&number2, 1023)) != MP_OKAY) \{ - printf("Error setting number2: \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* display */ - printf("Number1, Number2 == \%lu, \%lu", - mp_get_int(&number1), mp_get_int(&number2)); - - /* clear */ - mp_clear_multi(&number1, &number2, NULL); - - return EXIT_SUCCESS; -\} -\end{alltt} - -If this program succeeds it shall output. -\begin{alltt} -Number1, Number2 == 100, 1023 -\end{alltt} - -\section{Comparisons} - -Comparisons in LibTomMath are always performed in a ``left to right'' fashion. There are three possible return codes -for any comparison. - -\index{MP\_GT} \index{MP\_EQ} \index{MP\_LT} -\begin{figure}[here] -\begin{center} -\begin{tabular}{|c|c|} -\hline \textbf{Result Code} & \textbf{Meaning} \\ -\hline MP\_GT & $a > b$ \\ -\hline MP\_EQ & $a = b$ \\ -\hline MP\_LT & $a < b$ \\ -\hline -\end{tabular} -\end{center} -\caption{Comparison Codes for $a, b$} -\label{fig:CMP} -\end{figure} - -In figure \ref{fig:CMP} two integers $a$ and $b$ are being compared. In this case $a$ is said to be ``to the left'' of -$b$. - -\subsection{Unsigned comparison} - -An unsigned comparison considers only the digits themselves and not the associated \textit{sign} flag of the -mp\_int structures. This is analogous to an absolute comparison. The function mp\_cmp\_mag() will compare two -mp\_int variables based on their digits only. - -\index{mp\_cmp\_mag} -\begin{alltt} -int mp_cmp_mag(mp_int * a, mp_int * b); -\end{alltt} -This will compare $a$ to $b$ placing $a$ to the left of $b$. This function cannot fail and will return one of the -three compare codes listed in figure \ref{fig:CMP}. - -\begin{small} \begin{alltt} -int main(void) -\{ - mp_int number1, number2; - int result; - - if ((result = mp_init_multi(&number1, &number2, NULL)) != MP_OKAY) \{ - printf("Error initializing the numbers. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* set the number1 to 5 */ - mp_set(&number1, 5); - - /* set the number2 to -6 */ - mp_set(&number2, 6); - if ((result = mp_neg(&number2, &number2)) != MP_OKAY) \{ - printf("Error negating number2. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - switch(mp_cmp_mag(&number1, &number2)) \{ - case MP_GT: printf("|number1| > |number2|"); break; - case MP_EQ: printf("|number1| = |number2|"); break; - case MP_LT: printf("|number1| < |number2|"); break; - \} - - /* we're done with it. */ - mp_clear_multi(&number1, &number2, NULL); - - return EXIT_SUCCESS; -\} -\end{alltt} \end{small} - -If this program\footnote{This function uses the mp\_neg() function which is discussed in section \ref{sec:NEG}.} completes -successfully it should print the following. - -\begin{alltt} -|number1| < |number2| -\end{alltt} - -This is because $\vert -6 \vert = 6$ and obviously $5 < 6$. - -\subsection{Signed comparison} - -To compare two mp\_int variables based on their signed value the mp\_cmp() function is provided. - -\index{mp\_cmp} -\begin{alltt} -int mp_cmp(mp_int * a, mp_int * b); -\end{alltt} - -This will compare $a$ to the left of $b$. It will first compare the signs of the two mp\_int variables. If they -differ it will return immediately based on their signs. If the signs are equal then it will compare the digits -individually. This function will return one of the compare conditions codes listed in figure \ref{fig:CMP}. - -\begin{small} \begin{alltt} -int main(void) -\{ - mp_int number1, number2; - int result; - - if ((result = mp_init_multi(&number1, &number2, NULL)) != MP_OKAY) \{ - printf("Error initializing the numbers. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* set the number1 to 5 */ - mp_set(&number1, 5); - - /* set the number2 to -6 */ - mp_set(&number2, 6); - if ((result = mp_neg(&number2, &number2)) != MP_OKAY) \{ - printf("Error negating number2. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - switch(mp_cmp(&number1, &number2)) \{ - case MP_GT: printf("number1 > number2"); break; - case MP_EQ: printf("number1 = number2"); break; - case MP_LT: printf("number1 < number2"); break; - \} - - /* we're done with it. */ - mp_clear_multi(&number1, &number2, NULL); - - return EXIT_SUCCESS; -\} -\end{alltt} \end{small} - -If this program\footnote{This function uses the mp\_neg() function which is discussed in section \ref{sec:NEG}.} completes -successfully it should print the following. - -\begin{alltt} -number1 > number2 -\end{alltt} - -\subsection{Single Digit} - -To compare a single digit against an mp\_int the following function has been provided. - -\index{mp\_cmp\_d} -\begin{alltt} -int mp_cmp_d(mp_int * a, mp_digit b); -\end{alltt} - -This will compare $a$ to the left of $b$ using a signed comparison. Note that it will always treat $b$ as -positive. This function is rather handy when you have to compare against small values such as $1$ (which often -comes up in cryptography). The function cannot fail and will return one of the tree compare condition codes -listed in figure \ref{fig:CMP}. - - -\begin{small} \begin{alltt} -int main(void) -\{ - mp_int number; - int result; - - if ((result = mp_init(&number)) != MP_OKAY) \{ - printf("Error initializing the number. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* set the number to 5 */ - mp_set(&number, 5); - - switch(mp_cmp_d(&number, 7)) \{ - case MP_GT: printf("number > 7"); break; - case MP_EQ: printf("number = 7"); break; - case MP_LT: printf("number < 7"); break; - \} - - /* we're done with it. */ - mp_clear(&number); - - return EXIT_SUCCESS; -\} -\end{alltt} \end{small} - -If this program functions properly it will print out the following. - -\begin{alltt} -number < 7 -\end{alltt} - -\section{Logical Operations} - -Logical operations are operations that can be performed either with simple shifts or boolean operators such as -AND, XOR and OR directly. These operations are very quick. - -\subsection{Multiplication by two} - -Multiplications and divisions by any power of two can be performed with quick logical shifts either left or -right depending on the operation. - -When multiplying or dividing by two a special case routine can be used which are as follows. -\index{mp\_mul\_2} \index{mp\_div\_2} -\begin{alltt} -int mp_mul_2(mp_int * a, mp_int * b); -int mp_div_2(mp_int * a, mp_int * b); -\end{alltt} - -The former will assign twice $a$ to $b$ while the latter will assign half $a$ to $b$. These functions are fast -since the shift counts and maskes are hardcoded into the routines. - -\begin{small} \begin{alltt} -int main(void) -\{ - mp_int number; - int result; - - if ((result = mp_init(&number)) != MP_OKAY) \{ - printf("Error initializing the number. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* set the number to 5 */ - mp_set(&number, 5); - - /* multiply by two */ - if ((result = mp\_mul\_2(&number, &number)) != MP_OKAY) \{ - printf("Error multiplying the number. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - switch(mp_cmp_d(&number, 7)) \{ - case MP_GT: printf("2*number > 7"); break; - case MP_EQ: printf("2*number = 7"); break; - case MP_LT: printf("2*number < 7"); break; - \} - - /* now divide by two */ - if ((result = mp\_div\_2(&number, &number)) != MP_OKAY) \{ - printf("Error dividing the number. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - switch(mp_cmp_d(&number, 7)) \{ - case MP_GT: printf("2*number/2 > 7"); break; - case MP_EQ: printf("2*number/2 = 7"); break; - case MP_LT: printf("2*number/2 < 7"); break; - \} - - /* we're done with it. */ - mp_clear(&number); - - return EXIT_SUCCESS; -\} -\end{alltt} \end{small} - -If this program is successful it will print out the following text. - -\begin{alltt} -2*number > 7 -2*number/2 < 7 -\end{alltt} - -Since $10 > 7$ and $5 < 7$. - -To multiply by a power of two the following function can be used. - -\index{mp\_mul\_2d} -\begin{alltt} -int mp_mul_2d(mp_int * a, int b, mp_int * c); -\end{alltt} - -This will multiply $a$ by $2^b$ and store the result in ``c''. If the value of $b$ is less than or equal to -zero the function will copy $a$ to ``c'' without performing any further actions. The multiplication itself -is implemented as a right-shift operation of $a$ by $b$ bits. - -To divide by a power of two use the following. - -\index{mp\_div\_2d} -\begin{alltt} -int mp_div_2d (mp_int * a, int b, mp_int * c, mp_int * d); -\end{alltt} -Which will divide $a$ by $2^b$, store the quotient in ``c'' and the remainder in ``d'. If $b \le 0$ then the -function simply copies $a$ over to ``c'' and zeroes $d$. The variable $d$ may be passed as a \textbf{NULL} -value to signal that the remainder is not desired. The division itself is implemented as a left-shift -operation of $a$ by $b$ bits. - -\subsection{Polynomial Basis Operations} - -Strictly speaking the organization of the integers within the mp\_int structures is what is known as a -``polynomial basis''. This simply means a field element is stored by divisions of a radix. For example, if -$f(x) = \sum_{i=0}^{k} y_ix^k$ for any vector $\vec y$ then the array of digits in $\vec y$ are said to be -the polynomial basis representation of $z$ if $f(\beta) = z$ for a given radix $\beta$. - -To multiply by the polynomial $g(x) = x$ all you have todo is shift the digits of the basis left one place. The -following function provides this operation. - -\index{mp\_lshd} -\begin{alltt} -int mp_lshd (mp_int * a, int b); -\end{alltt} - -This will multiply $a$ in place by $x^b$ which is equivalent to shifting the digits left $b$ places and inserting zeroes -in the least significant digits. Similarly to divide by a power of $x$ the following function is provided. - -\index{mp\_rshd} -\begin{alltt} -void mp_rshd (mp_int * a, int b) -\end{alltt} -This will divide $a$ in place by $x^b$ and discard the remainder. This function cannot fail as it performs the operations -in place and no new digits are required to complete it. - -\subsection{AND, OR and XOR Operations} - -While AND, OR and XOR operations are not typical ``bignum functions'' they can be useful in several instances. The -three functions are prototyped as follows. - -\index{mp\_or} \index{mp\_and} \index{mp\_xor} -\begin{alltt} -int mp_or (mp_int * a, mp_int * b, mp_int * c); -int mp_and (mp_int * a, mp_int * b, mp_int * c); -int mp_xor (mp_int * a, mp_int * b, mp_int * c); -\end{alltt} - -Which compute $c = a \odot b$ where $\odot$ is one of OR, AND or XOR. - -\section{Addition and Subtraction} - -To compute an addition or subtraction the following two functions can be used. - -\index{mp\_add} \index{mp\_sub} -\begin{alltt} -int mp_add (mp_int * a, mp_int * b, mp_int * c); -int mp_sub (mp_int * a, mp_int * b, mp_int * c) -\end{alltt} - -Which perform $c = a \odot b$ where $\odot$ is one of signed addition or subtraction. The operations are fully sign -aware. - -\section{Sign Manipulation} -\subsection{Negation} -\label{sec:NEG} -Simple integer negation can be performed with the following. - -\index{mp\_neg} -\begin{alltt} -int mp_neg (mp_int * a, mp_int * b); -\end{alltt} - -Which assigns $-a$ to $b$. - -\subsection{Absolute} -Simple integer absolutes can be performed with the following. - -\index{mp\_neg} -\begin{alltt} -int mp_abs (mp_int * a, mp_int * b); -\end{alltt} - -Which assigns $\vert a \vert$ to $b$. - -\section{Integer Division and Remainder} -To perform a complete and general integer division with remainder use the following function. - -\index{mp\_div} -\begin{alltt} -int mp_div (mp_int * a, mp_int * b, mp_int * c, mp_int * d); -\end{alltt} - -This divides $a$ by $b$ and stores the quotient in $c$ and $d$. The signed quotient is computed such that -$bc + d = a$. Note that either of $c$ or $d$ can be set to \textbf{NULL} if their value is not required. If -$b$ is zero the function returns \textbf{MP\_VAL}. - - -\chapter{Multiplication and Squaring} -\section{Multiplication} -A full signed integer multiplication can be performed with the following. -\index{mp\_mul} -\begin{alltt} -int mp_mul (mp_int * a, mp_int * b, mp_int * c); -\end{alltt} -Which assigns the full signed product $ab$ to $c$. This function actually breaks into one of four cases which are -specific multiplication routines optimized for given parameters. First there are the Toom-Cook multiplications which -should only be used with very large inputs. This is followed by the Karatsuba multiplications which are for moderate -sized inputs. Then followed by the Comba and baseline multipliers. - -Fortunately for the developer you don't really need to know this unless you really want to fine tune the system. mp\_mul() -will determine on its own\footnote{Some tweaking may be required.} what routine to use automatically when it is called. - -\begin{alltt} -int main(void) -\{ - mp_int number1, number2; - int result; - - /* Initialize the numbers */ - if ((result = mp_init_multi(&number1, - &number2, NULL)) != MP_OKAY) \{ - printf("Error initializing the numbers. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* set the terms */ - if ((result = mp_set_int(&number, 257)) != MP_OKAY) \{ - printf("Error setting number1. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - if ((result = mp_set_int(&number2, 1023)) != MP_OKAY) \{ - printf("Error setting number2. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* multiply them */ - if ((result = mp_mul(&number1, &number2, - &number1)) != MP_OKAY) \{ - printf("Error multiplying terms. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* display */ - printf("number1 * number2 == \%lu", mp_get_int(&number1)); - - /* free terms and return */ - mp_clear_multi(&number1, &number2, NULL); - - return EXIT_SUCCESS; -\} -\end{alltt} - -If this program succeeds it shall output the following. - -\begin{alltt} -number1 * number2 == 262911 -\end{alltt} - -\section{Squaring} -Since squaring can be performed faster than multiplication it is performed it's own function instead of just using -mp\_mul(). - -\index{mp\_sqr} -\begin{alltt} -int mp_sqr (mp_int * a, mp_int * b); -\end{alltt} - -Will square $a$ and store it in $b$. Like the case of multiplication there are four different squaring -algorithms all which can be called from mp\_sqr(). It is ideal to use mp\_sqr over mp\_mul when squaring terms because -of the speed difference. - -\section{Tuning Polynomial Basis Routines} - -Both of the Toom-Cook and Karatsuba multiplication algorithms are faster than the traditional $O(n^2)$ approach that -the Comba and baseline algorithms use. At $O(n^{1.464973})$ and $O(n^{1.584962})$ running times respectively they require -considerably less work. For example, a 10000-digit multiplication would take roughly 724,000 single precision -multiplications with Toom-Cook or 100,000,000 single precision multiplications with the standard Comba (a factor -of 138). - -So why not always use Karatsuba or Toom-Cook? The simple answer is that they have so much overhead that they're not -actually faster than Comba until you hit distinct ``cutoff'' points. For Karatsuba with the default configuration, -GCC 3.3.1 and an Athlon XP processor the cutoff point is roughly 110 digits (about 70 for the Intel P4). That is, at -110 digits Karatsuba and Comba multiplications just about break even and for 110+ digits Karatsuba is faster. - -Toom-Cook has incredible overhead and is probably only useful for very large inputs. So far no known cutoff points -exist and for the most part I just set the cutoff points very high to make sure they're not called. - -A demo program in the ``etc/'' directory of the project called ``tune.c'' can be used to find the cutoff points. This -can be built with GCC as follows - -\begin{alltt} -make XXX -\end{alltt} -Where ``XXX'' is one of the following entries from the table \ref{fig:tuning}. - -\begin{figure}[here] -\begin{center} -\begin{small} -\begin{tabular}{|l|l|} -\hline \textbf{Value of XXX} & \textbf{Meaning} \\ -\hline tune & Builds portable tuning application \\ -\hline tune86 & Builds x86 (pentium and up) program for COFF \\ -\hline tune86c & Builds x86 program for Cygwin \\ -\hline tune86l & Builds x86 program for Linux (ELF format) \\ -\hline -\end{tabular} -\end{small} -\end{center} -\caption{Build Names for Tuning Programs} -\label{fig:tuning} -\end{figure} - -When the program is running it will output a series of measurements for different cutoff points. It will first find -good Karatsuba squaring and multiplication points. Then it proceeds to find Toom-Cook points. Note that the Toom-Cook -tuning takes a very long time as the cutoff points are likely to be very high. - -\chapter{Modular Reduction} - -Modular reduction is process of taking the remainder of one quantity divided by another. Expressed -as (\ref{eqn:mod}) the modular reduction is equivalent to the remainder of $b$ divided by $c$. - -\begin{equation} -a \equiv b \mbox{ (mod }c\mbox{)} -\label{eqn:mod} -\end{equation} - -Of particular interest to cryptography are reductions where $b$ is limited to the range $0 \le b < c^2$ since particularly -fast reduction algorithms can be written for the limited range. - -Note that one of the four optimized reduction algorithms are automatically chosen in the modular exponentiation -algorithm mp\_exptmod when an appropriate modulus is detected. - -\section{Straight Division} -In order to effect an arbitrary modular reduction the following algorithm is provided. - -\index{mp\_mod} -\begin{alltt} -int mp_mod(mp_int *a, mp_int *b, mp_int *c); -\end{alltt} - -This reduces $a$ modulo $b$ and stores the result in $c$. The sign of $c$ shall agree with the sign -of $b$. This algorithm accepts an input $a$ of any range and is not limited by $0 \le a < b^2$. - -\section{Barrett Reduction} - -Barrett reduction is a generic optimized reduction algorithm that requires pre--computation to achieve -a decent speedup over straight division. First a $\mu$ value must be precomputed with the following function. - -\index{mp\_reduce\_setup} -\begin{alltt} -int mp_reduce_setup(mp_int *a, mp_int *b); -\end{alltt} - -Given a modulus in $b$ this produces the required $\mu$ value in $a$. For any given modulus this only has to -be computed once. Modular reduction can now be performed with the following. - -\index{mp\_reduce} -\begin{alltt} -int mp_reduce(mp_int *a, mp_int *b, mp_int *c); -\end{alltt} - -This will reduce $a$ in place modulo $b$ with the precomputed $\mu$ value in $c$. $a$ must be in the range -$0 \le a < b^2$. - -\begin{alltt} -int main(void) -\{ - mp_int a, b, c, mu; - int result; - - /* initialize a,b to desired values, mp_init mu, - * c and set c to 1...we want to compute a^3 mod b - */ - - /* get mu value */ - if ((result = mp_reduce_setup(&mu, b)) != MP_OKAY) \{ - printf("Error getting mu. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* square a to get c = a^2 */ - if ((result = mp_sqr(&a, &c)) != MP_OKAY) \{ - printf("Error squaring. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* now reduce `c' modulo b */ - if ((result = mp_reduce(&c, &b, &mu)) != MP_OKAY) \{ - printf("Error reducing. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* multiply a to get c = a^3 */ - if ((result = mp_mul(&a, &c, &c)) != MP_OKAY) \{ - printf("Error reducing. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* now reduce `c' modulo b */ - if ((result = mp_reduce(&c, &b, &mu)) != MP_OKAY) \{ - printf("Error reducing. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* c now equals a^3 mod b */ - - return EXIT_SUCCESS; -\} -\end{alltt} - -This program will calculate $a^3 \mbox{ mod }b$ if all the functions succeed. - -\section{Montgomery Reduction} - -Montgomery is a specialized reduction algorithm for any odd moduli. Like Barrett reduction a pre--computation -step is required. This is accomplished with the following. - -\index{mp\_montgomery\_setup} -\begin{alltt} -int mp_montgomery_setup(mp_int *a, mp_digit *mp); -\end{alltt} - -For the given odd moduli $a$ the precomputation value is placed in $mp$. The reduction is computed with the -following. - -\index{mp\_montgomery\_reduce} -\begin{alltt} -int mp_montgomery_reduce(mp_int *a, mp_int *m, mp_digit mp); -\end{alltt} -This reduces $a$ in place modulo $m$ with the pre--computed value $mp$. $a$ must be in the range -$0 \le a < b^2$. - -Montgomery reduction is faster than Barrett reduction for moduli smaller than the ``comba'' limit. With the default -setup for instance, the limit is $127$ digits ($3556$--bits). Note that this function is not limited to -$127$ digits just that it falls back to a baseline algorithm after that point. - -An important observation is that this reduction does not return $a \mbox{ mod }m$ but $aR^{-1} \mbox{ mod }m$ -where $R = \beta^n$, $n$ is the n number of digits in $m$ and $\beta$ is radix used (default is $2^{28}$). - -To quickly calculate $R$ the following function was provided. - -\index{mp\_montgomery\_calc\_normalization} -\begin{alltt} -int mp_montgomery_calc_normalization(mp_int *a, mp_int *b); -\end{alltt} -Which calculates $a = R$ for the odd moduli $b$ without using multiplication or division. - -The normal modus operandi for Montgomery reductions is to normalize the integers before entering the system. For -example, to calculate $a^3 \mbox { mod }b$ using Montgomery reduction the value of $a$ can be normalized by -multiplying it by $R$. Consider the following code snippet. - -\begin{alltt} -int main(void) -\{ - mp_int a, b, c, R; - mp_digit mp; - int result; - - /* initialize a,b to desired values, - * mp_init R, c and set c to 1.... - */ - - /* get normalization */ - if ((result = mp_montgomery_calc_normalization(&R, b)) != MP_OKAY) \{ - printf("Error getting norm. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* get mp value */ - if ((result = mp_montgomery_setup(&c, &mp)) != MP_OKAY) \{ - printf("Error setting up montgomery. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* normalize `a' so now a is equal to aR */ - if ((result = mp_mulmod(&a, &R, &b, &a)) != MP_OKAY) \{ - printf("Error computing aR. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* square a to get c = a^2R^2 */ - if ((result = mp_sqr(&a, &c)) != MP_OKAY) \{ - printf("Error squaring. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* now reduce `c' back down to c = a^2R^2 * R^-1 == a^2R */ - if ((result = mp_montgomery_reduce(&c, &b, mp)) != MP_OKAY) \{ - printf("Error reducing. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* multiply a to get c = a^3R^2 */ - if ((result = mp_mul(&a, &c, &c)) != MP_OKAY) \{ - printf("Error reducing. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* now reduce `c' back down to c = a^3R^2 * R^-1 == a^3R */ - if ((result = mp_montgomery_reduce(&c, &b, mp)) != MP_OKAY) \{ - printf("Error reducing. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* now reduce (again) `c' back down to c = a^3R * R^-1 == a^3 */ - if ((result = mp_montgomery_reduce(&c, &b, mp)) != MP_OKAY) \{ - printf("Error reducing. \%s", - mp_error_to_string(result)); - return EXIT_FAILURE; - \} - - /* c now equals a^3 mod b */ - - return EXIT_SUCCESS; -\} -\end{alltt} - -This particular example does not look too efficient but it demonstrates the point of the algorithm. By -normalizing the inputs the reduced results are always of the form $aR$ for some variable $a$. This allows -a single final reduction to correct for the normalization and the fast reduction used within the algorithm. - -For more details consider examining the file \textit{bn\_mp\_exptmod\_fast.c}. - -\section{Restricted Dimminished Radix} - -``Dimminished Radix'' reduction refers to reduction with respect to moduli that are ameniable to simple -digit shifting and small multiplications. In this case the ``restricted'' variant refers to moduli of the -form $\beta^k - p$ for some $k \ge 0$ and $0 < p < \beta$ where $\beta$ is the radix (default to $2^{28}$). - -As in the case of Montgomery reduction there is a pre--computation phase required for a given modulus. - -\index{mp\_dr\_setup} -\begin{alltt} -void mp_dr_setup(mp_int *a, mp_digit *d); -\end{alltt} - -This computes the value required for the modulus $a$ and stores it in $d$. This function cannot fail -and does not return any error codes. After the pre--computation a reduction can be performed with the -following. - -\index{mp\_dr\_reduce} -\begin{alltt} -int mp_dr_reduce(mp_int *a, mp_int *b, mp_digit mp); -\end{alltt} - -This reduces $a$ in place modulo $b$ with the pre--computed value $mp$. $b$ must be of a restricted -dimminished radix form and $a$ must be in the range $0 \le a < b^2$. Dimminished radix reductions are -much faster than both Barrett and Montgomery reductions as they have a much lower asymtotic running time. - -Since the moduli are restricted this algorithm is not particularly useful for something like Rabin, RSA or -BBS cryptographic purposes. This reduction algorithm is useful for Diffie-Hellman and ECC where fixed -primes are acceptable. - -Note that unlike Montgomery reduction there is no normalization process. The result of this function is -equal to the correct residue. - -\section{Unrestricted Dimminshed Radix} - -Unrestricted reductions work much like the restricted counterparts except in this case the moduli is of the -form $2^k - p$ for $0 < p < \beta$. In this sense the unrestricted reductions are more flexible as they -can be applied to a wider range of numbers. - -\index{mp\_reduce\_2k\_setup} -\begin{alltt} -int mp_reduce_2k_setup(mp_int *a, mp_digit *d); -\end{alltt} - -This will compute the required $d$ value for the given moduli $a$. - -\index{mp\_reduce\_2k} -\begin{alltt} -int mp_reduce_2k(mp_int *a, mp_int *n, mp_digit d); -\end{alltt} - -This will reduce $a$ in place modulo $n$ with the pre--computed value $d$. From my experience this routine is -slower than mp\_dr\_reduce but faster for most moduli sizes than the Montgomery reduction. - -\chapter{Exponentiation} -\section{Single Digit Exponentiation} -\index{mp\_expt\_d\_ex} -\begin{alltt} -int mp_expt_d_ex (mp_int * a, mp_digit b, mp_int * c, int fast) -\end{alltt} -This function computes $c = a^b$. - -With parameter \textit{fast} set to $0$ the old version of the algorithm is used, -when \textit{fast} is $1$, a faster but not statically timed version of the algorithm is used. - -The old version uses a simple binary left-to-right algorithm. -It is faster than repeated multiplications by $a$ for all values of $b$ greater than three. - -The new version uses a binary right-to-left algorithm. - -The difference between the old and the new version is that the old version always -executes $DIGIT\_BIT$ iterations. The new algorithm executes only $n$ iterations -where $n$ is equal to the position of the highest bit that is set in $b$. - -\index{mp\_expt\_d} -\begin{alltt} -int mp_expt_d (mp_int * a, mp_digit b, mp_int * c) -\end{alltt} -mp\_expt\_d(a, b, c) is a wrapper function to mp\_expt\_d\_ex(a, b, c, 0). - -\section{Modular Exponentiation} -\index{mp\_exptmod} -\begin{alltt} -int mp_exptmod (mp_int * G, mp_int * X, mp_int * P, mp_int * Y) -\end{alltt} -This computes $Y \equiv G^X \mbox{ (mod }P\mbox{)}$ using a variable width sliding window algorithm. This function -will automatically detect the fastest modular reduction technique to use during the operation. For negative values of -$X$ the operation is performed as $Y \equiv (G^{-1} \mbox{ mod }P)^{\vert X \vert} \mbox{ (mod }P\mbox{)}$ provided that -$gcd(G, P) = 1$. - -This function is actually a shell around the two internal exponentiation functions. This routine will automatically -detect when Barrett, Montgomery, Restricted and Unrestricted Dimminished Radix based exponentiation can be used. Generally -moduli of the a ``restricted dimminished radix'' form lead to the fastest modular exponentiations. Followed by Montgomery -and the other two algorithms. - -\section{Root Finding} -\index{mp\_n\_root} -\begin{alltt} -int mp_n_root (mp_int * a, mp_digit b, mp_int * c) -\end{alltt} -This computes $c = a^{1/b}$ such that $c^b \le a$ and $(c+1)^b > a$. The implementation of this function is not -ideal for values of $b$ greater than three. It will work but become very slow. So unless you are working with very small -numbers (less than 1000 bits) I'd avoid $b > 3$ situations. Will return a positive root only for even roots and return -a root with the sign of the input for odd roots. For example, performing $4^{1/2}$ will return $2$ whereas $(-8)^{1/3}$ -will return $-2$. - -This algorithm uses the ``Newton Approximation'' method and will converge on the correct root fairly quickly. Since -the algorithm requires raising $a$ to the power of $b$ it is not ideal to attempt to find roots for large -values of $b$. If particularly large roots are required then a factor method could be used instead. For example, -$a^{1/16}$ is equivalent to $\left (a^{1/4} \right)^{1/4}$ or simply -$\left ( \left ( \left ( a^{1/2} \right )^{1/2} \right )^{1/2} \right )^{1/2}$ - -\chapter{Prime Numbers} -\section{Trial Division} -\index{mp\_prime\_is\_divisible} -\begin{alltt} -int mp_prime_is_divisible (mp_int * a, int *result) -\end{alltt} -This will attempt to evenly divide $a$ by a list of primes\footnote{Default is the first 256 primes.} and store the -outcome in ``result''. That is if $result = 0$ then $a$ is not divisible by the primes, otherwise it is. Note that -if the function does not return \textbf{MP\_OKAY} the value in ``result'' should be considered undefined\footnote{Currently -the default is to set it to zero first.}. - -\section{Fermat Test} -\index{mp\_prime\_fermat} -\begin{alltt} -int mp_prime_fermat (mp_int * a, mp_int * b, int *result) -\end{alltt} -Performs a Fermat primality test to the base $b$. That is it computes $b^a \mbox{ mod }a$ and tests whether the value is -equal to $b$ or not. If the values are equal then $a$ is probably prime and $result$ is set to one. Otherwise $result$ -is set to zero. - -\section{Miller-Rabin Test} -\index{mp\_prime\_miller\_rabin} -\begin{alltt} -int mp_prime_miller_rabin (mp_int * a, mp_int * b, int *result) -\end{alltt} -Performs a Miller-Rabin test to the base $b$ of $a$. This test is much stronger than the Fermat test and is very hard to -fool (besides with Carmichael numbers). If $a$ passes the test (therefore is probably prime) $result$ is set to one. -Otherwise $result$ is set to zero. - -Note that is suggested that you use the Miller-Rabin test instead of the Fermat test since all of the failures of -Miller-Rabin are a subset of the failures of the Fermat test. - -\subsection{Required Number of Tests} -Generally to ensure a number is very likely to be prime you have to perform the Miller-Rabin with at least a half-dozen -or so unique bases. However, it has been proven that the probability of failure goes down as the size of the input goes up. -This is why a simple function has been provided to help out. - -\index{mp\_prime\_rabin\_miller\_trials} -\begin{alltt} -int mp_prime_rabin_miller_trials(int size) -\end{alltt} -This returns the number of trials required for a $2^{-96}$ (or lower) probability of failure for a given ``size'' expressed -in bits. This comes in handy specially since larger numbers are slower to test. For example, a 512-bit number would -require ten tests whereas a 1024-bit number would only require four tests. - -You should always still perform a trial division before a Miller-Rabin test though. - -\section{Primality Testing} -\index{mp\_prime\_is\_prime} -\begin{alltt} -int mp_prime_is_prime (mp_int * a, int t, int *result) -\end{alltt} -This will perform a trial division followed by $t$ rounds of Miller-Rabin tests on $a$ and store the result in $result$. -If $a$ passes all of the tests $result$ is set to one, otherwise it is set to zero. Note that $t$ is bounded by -$1 \le t < PRIME\_SIZE$ where $PRIME\_SIZE$ is the number of primes in the prime number table (by default this is $256$). - -\section{Next Prime} -\index{mp\_prime\_next\_prime} -\begin{alltt} -int mp_prime_next_prime(mp_int *a, int t, int bbs_style) -\end{alltt} -This finds the next prime after $a$ that passes mp\_prime\_is\_prime() with $t$ tests. Set $bbs\_style$ to one if you -want only the next prime congruent to $3 \mbox{ mod } 4$, otherwise set it to zero to find any next prime. - -\section{Random Primes} -\index{mp\_prime\_random} -\begin{alltt} -int mp_prime_random(mp_int *a, int t, int size, int bbs, - ltm_prime_callback cb, void *dat) -\end{alltt} -This will find a prime greater than $256^{size}$ which can be ``bbs\_style'' or not depending on $bbs$ and must pass -$t$ rounds of tests. The ``ltm\_prime\_callback'' is a typedef for - -\begin{alltt} -typedef int ltm_prime_callback(unsigned char *dst, int len, void *dat); -\end{alltt} - -Which is a function that must read $len$ bytes (and return the amount stored) into $dst$. The $dat$ variable is simply -copied from the original input. It can be used to pass RNG context data to the callback. The function -mp\_prime\_random() is more suitable for generating primes which must be secret (as in the case of RSA) since there -is no skew on the least significant bits. - -\textit{Note:} As of v0.30 of the LibTomMath library this function has been deprecated. It is still available -but users are encouraged to use the new mp\_prime\_random\_ex() function instead. - -\subsection{Extended Generation} -\index{mp\_prime\_random\_ex} -\begin{alltt} -int mp_prime_random_ex(mp_int *a, int t, - int size, int flags, - ltm_prime_callback cb, void *dat); -\end{alltt} -This will generate a prime in $a$ using $t$ tests of the primality testing algorithms. The variable $size$ -specifies the bit length of the prime desired. The variable $flags$ specifies one of several options available -(see fig. \ref{fig:primeopts}) which can be OR'ed together. The callback parameters are used as in -mp\_prime\_random(). - -\begin{figure}[here] -\begin{center} -\begin{small} -\begin{tabular}{|r|l|} -\hline \textbf{Flag} & \textbf{Meaning} \\ -\hline LTM\_PRIME\_BBS & Make the prime congruent to $3$ modulo $4$ \\ -\hline LTM\_PRIME\_SAFE & Make a prime $p$ such that $(p - 1)/2$ is also prime. \\ - & This option implies LTM\_PRIME\_BBS as well. \\ -\hline LTM\_PRIME\_2MSB\_OFF & Makes sure that the bit adjacent to the most significant bit \\ - & Is forced to zero. \\ -\hline LTM\_PRIME\_2MSB\_ON & Makes sure that the bit adjacent to the most significant bit \\ - & Is forced to one. \\ -\hline -\end{tabular} -\end{small} -\end{center} -\caption{Primality Generation Options} -\label{fig:primeopts} -\end{figure} - -\chapter{Input and Output} -\section{ASCII Conversions} -\subsection{To ASCII} -\index{mp\_toradix} -\begin{alltt} -int mp_toradix (mp_int * a, char *str, int radix); -\end{alltt} -This still store $a$ in ``str'' as a base-``radix'' string of ASCII chars. This function appends a NUL character -to terminate the string. Valid values of ``radix'' line in the range $[2, 64]$. To determine the size (exact) required -by the conversion before storing any data use the following function. - -\index{mp\_radix\_size} -\begin{alltt} -int mp_radix_size (mp_int * a, int radix, int *size) -\end{alltt} -This stores in ``size'' the number of characters (including space for the NUL terminator) required. Upon error this -function returns an error code and ``size'' will be zero. - -\subsection{From ASCII} -\index{mp\_read\_radix} -\begin{alltt} -int mp_read_radix (mp_int * a, char *str, int radix); -\end{alltt} -This will read the base-``radix'' NUL terminated string from ``str'' into $a$. It will stop reading when it reads a -character it does not recognize (which happens to include th NUL char... imagine that...). A single leading $-$ sign -can be used to denote a negative number. - -\section{Binary Conversions} - -Converting an mp\_int to and from binary is another keen idea. - -\index{mp\_unsigned\_bin\_size} -\begin{alltt} -int mp_unsigned_bin_size(mp_int *a); -\end{alltt} - -This will return the number of bytes (octets) required to store the unsigned copy of the integer $a$. - -\index{mp\_to\_unsigned\_bin} -\begin{alltt} -int mp_to_unsigned_bin(mp_int *a, unsigned char *b); -\end{alltt} -This will store $a$ into the buffer $b$ in big--endian format. Fortunately this is exactly what DER (or is it ASN?) -requires. It does not store the sign of the integer. - -\index{mp\_read\_unsigned\_bin} -\begin{alltt} -int mp_read_unsigned_bin(mp_int *a, unsigned char *b, int c); -\end{alltt} -This will read in an unsigned big--endian array of bytes (octets) from $b$ of length $c$ into $a$. The resulting -integer $a$ will always be positive. - -For those who acknowledge the existence of negative numbers (heretic!) there are ``signed'' versions of the -previous functions. - -\begin{alltt} -int mp_signed_bin_size(mp_int *a); -int mp_read_signed_bin(mp_int *a, unsigned char *b, int c); -int mp_to_signed_bin(mp_int *a, unsigned char *b); -\end{alltt} -They operate essentially the same as the unsigned copies except they prefix the data with zero or non--zero -byte depending on the sign. If the sign is zpos (e.g. not negative) the prefix is zero, otherwise the prefix -is non--zero. - -\chapter{Algebraic Functions} -\section{Extended Euclidean Algorithm} -\index{mp\_exteuclid} -\begin{alltt} -int mp_exteuclid(mp_int *a, mp_int *b, - mp_int *U1, mp_int *U2, mp_int *U3); -\end{alltt} - -This finds the triple U1/U2/U3 using the Extended Euclidean algorithm such that the following equation holds. - -\begin{equation} -a \cdot U1 + b \cdot U2 = U3 -\end{equation} - -Any of the U1/U2/U3 paramters can be set to \textbf{NULL} if they are not desired. - -\section{Greatest Common Divisor} -\index{mp\_gcd} -\begin{alltt} -int mp_gcd (mp_int * a, mp_int * b, mp_int * c) -\end{alltt} -This will compute the greatest common divisor of $a$ and $b$ and store it in $c$. - -\section{Least Common Multiple} -\index{mp\_lcm} -\begin{alltt} -int mp_lcm (mp_int * a, mp_int * b, mp_int * c) -\end{alltt} -This will compute the least common multiple of $a$ and $b$ and store it in $c$. - -\section{Jacobi Symbol} -\index{mp\_jacobi} -\begin{alltt} -int mp_jacobi (mp_int * a, mp_int * p, int *c) -\end{alltt} -This will compute the Jacobi symbol for $a$ with respect to $p$. If $p$ is prime this essentially computes the Legendre -symbol. The result is stored in $c$ and can take on one of three values $\lbrace -1, 0, 1 \rbrace$. If $p$ is prime -then the result will be $-1$ when $a$ is not a quadratic residue modulo $p$. The result will be $0$ if $a$ divides $p$ -and the result will be $1$ if $a$ is a quadratic residue modulo $p$. - -\section{Modular square root} -\index{mp\_sqrtmod\_prime} -\begin{alltt} -int mp_sqrtmod_prime(mp_int *n, mp_int *p, mp_int *r) -\end{alltt} - -This will solve the modular equatioon $r^2 = n \mod p$ where $p$ is a prime number greater than 2 (odd prime). -The result is returned in the third argument $r$, the function returns \textbf{MP\_OKAY} on success, -other return values indicate failure. - -The implementation is split for two different cases: - -1. if $p \mod 4 == 3$ we apply \href{http://cacr.uwaterloo.ca/hac/}{Handbook of Applied Cryptography algorithm 3.36} and compute $r$ directly as -$r = n^{(p+1)/4} \mod p$ - -2. otherwise we use \href{https://en.wikipedia.org/wiki/Tonelli-Shanks_algorithm}{Tonelli-Shanks algorithm} - -The function does not check the primality of parameter $p$ thus it is up to the caller to assure that this parameter -is a prime number. When $p$ is a composite the function behaviour is undefined, it may even return a false-positive -\textbf{MP\_OKAY}. - -\section{Modular Inverse} -\index{mp\_invmod} -\begin{alltt} -int mp_invmod (mp_int * a, mp_int * b, mp_int * c) -\end{alltt} -Computes the multiplicative inverse of $a$ modulo $b$ and stores the result in $c$ such that $ac \equiv 1 \mbox{ (mod }b\mbox{)}$. - -\section{Single Digit Functions} - -For those using small numbers (\textit{snicker snicker}) there are several ``helper'' functions - -\index{mp\_add\_d} \index{mp\_sub\_d} \index{mp\_mul\_d} \index{mp\_div\_d} \index{mp\_mod\_d} -\begin{alltt} -int mp_add_d(mp_int *a, mp_digit b, mp_int *c); -int mp_sub_d(mp_int *a, mp_digit b, mp_int *c); -int mp_mul_d(mp_int *a, mp_digit b, mp_int *c); -int mp_div_d(mp_int *a, mp_digit b, mp_int *c, mp_digit *d); -int mp_mod_d(mp_int *a, mp_digit b, mp_digit *c); -\end{alltt} - -These work like the full mp\_int capable variants except the second parameter $b$ is a mp\_digit. These -functions fairly handy if you have to work with relatively small numbers since you will not have to allocate -an entire mp\_int to store a number like $1$ or $2$. - -\input{bn.ind} - -\end{document} diff --git a/libtommath/bn_mp_read_radix.c b/libtommath/bn_mp_read_radix.c index 03384e3..a4d1c8a 100644 --- a/libtommath/bn_mp_read_radix.c +++ b/libtommath/bn_mp_read_radix.c @@ -71,7 +71,13 @@ int mp_read_radix (mp_int * a, const char *str, int radix) } ++str; } - + + /* if an illegal character was found, fail. */ + if (!(*str == '\0' || *str == '\r' || *str == '\n')) { + mp_zero(a); + return MP_VAL; + } + /* set the sign only if a != 0 */ if (mp_iszero(a) != MP_YES) { a->sign = neg; diff --git a/libtommath/booker.pl b/libtommath/booker.pl deleted file mode 100644 index c2abae6..0000000 --- a/libtommath/booker.pl +++ /dev/null @@ -1,267 +0,0 @@ -#!/bin/perl -# -#Used to prepare the book "tommath.src" for LaTeX by pre-processing it into a .tex file -# -#Essentially you write the "tommath.src" as normal LaTex except where you want code snippets you put -# -#EXAM,file -# -#This preprocessor will then open "file" and insert it as a verbatim copy. -# -#Tom St Denis - -#get graphics type -if (shift =~ /PDF/) { - $graph = ""; -} else { - $graph = ".ps"; -} - -open(IN,"<tommath.src") or die "Can't open source file"; -open(OUT,">tommath.tex") or die "Can't open destination file"; - -print "Scanning for sections\n"; -$chapter = $section = $subsection = 0; -$x = 0; -while (<IN>) { - print "."; - if (!(++$x % 80)) { print "\n"; } - #update the headings - if (~($_ =~ /\*/)) { - if ($_ =~ /\\chapter\{.+}/) { - ++$chapter; - $section = $subsection = 0; - } elsif ($_ =~ /\\section\{.+}/) { - ++$section; - $subsection = 0; - } elsif ($_ =~ /\\subsection\{.+}/) { - ++$subsection; - } - } - - if ($_ =~ m/MARK/) { - @m = split(",",$_); - chomp(@m[1]); - $index1{@m[1]} = $chapter; - $index2{@m[1]} = $section; - $index3{@m[1]} = $subsection; - } -} -close(IN); - -open(IN,"<tommath.src") or die "Can't open source file"; -$readline = $wroteline = 0; -$srcline = 0; - -while (<IN>) { - ++$readline; - ++$srcline; - - if ($_ =~ m/MARK/) { - } elsif ($_ =~ m/EXAM/ || $_ =~ m/LIST/) { - if ($_ =~ m/EXAM/) { - $skipheader = 1; - } else { - $skipheader = 0; - } - - # EXAM,file - chomp($_); - @m = split(",",$_); - open(SRC,"<$m[1]") or die "Error:$srcline:Can't open source file $m[1]"; - - print "$srcline:Inserting $m[1]:"; - - $line = 0; - $tmp = $m[1]; - $tmp =~ s/_/"\\_"/ge; - print OUT "\\vspace{+3mm}\\begin{small}\n\\hspace{-5.1mm}{\\bf File}: $tmp\n\\vspace{-3mm}\n\\begin{alltt}\n"; - $wroteline += 5; - - if ($skipheader == 1) { - # scan till next end of comment, e.g. skip license - while (<SRC>) { - $text[$line++] = $_; - last if ($_ =~ /libtom\.org/); - } - <SRC>; - } - - $inline = 0; - while (<SRC>) { - next if ($_ =~ /\$Source/); - next if ($_ =~ /\$Revision/); - next if ($_ =~ /\$Date/); - $text[$line++] = $_; - ++$inline; - chomp($_); - $_ =~ s/\t/" "/ge; - $_ =~ s/{/"^{"/ge; - $_ =~ s/}/"^}"/ge; - $_ =~ s/\\/'\symbol{92}'/ge; - $_ =~ s/\^/"\\"/ge; - - printf OUT ("%03d ", $line); - for ($x = 0; $x < length($_); $x++) { - print OUT chr(vec($_, $x, 8)); - if ($x == 75) { - print OUT "\n "; - ++$wroteline; - } - } - print OUT "\n"; - ++$wroteline; - } - $totlines = $line; - print OUT "\\end{alltt}\n\\end{small}\n"; - close(SRC); - print "$inline lines\n"; - $wroteline += 2; - } elsif ($_ =~ m/@\d+,.+@/) { - # line contains [number,text] - # e.g. @14,for (ix = 0)@ - $txt = $_; - while ($txt =~ m/@\d+,.+@/) { - @m = split("@",$txt); # splits into text, one, two - @parms = split(",",$m[1]); # splits one,two into two elements - - # now search from $parms[0] down for $parms[1] - $found1 = 0; - $found2 = 0; - for ($i = $parms[0]; $i < $totlines && $found1 == 0; $i++) { - if ($text[$i] =~ m/\Q$parms[1]\E/) { - $foundline1 = $i + 1; - $found1 = 1; - } - } - - # now search backwards - for ($i = $parms[0] - 1; $i >= 0 && $found2 == 0; $i--) { - if ($text[$i] =~ m/\Q$parms[1]\E/) { - $foundline2 = $i + 1; - $found2 = 1; - } - } - - # now use the closest match or the first if tied - if ($found1 == 1 && $found2 == 0) { - $found = 1; - $foundline = $foundline1; - } elsif ($found1 == 0 && $found2 == 1) { - $found = 1; - $foundline = $foundline2; - } elsif ($found1 == 1 && $found2 == 1) { - $found = 1; - if (($foundline1 - $parms[0]) <= ($parms[0] - $foundline2)) { - $foundline = $foundline1; - } else { - $foundline = $foundline2; - } - } else { - $found = 0; - } - - # if found replace - if ($found == 1) { - $delta = $parms[0] - $foundline; - print "Found replacement tag for \"$parms[1]\" on line $srcline which refers to line $foundline (delta $delta)\n"; - $_ =~ s/@\Q$m[1]\E@/$foundline/; - } else { - print "ERROR: The tag \"$parms[1]\" on line $srcline was not found in the most recently parsed source!\n"; - } - - # remake the rest of the line - $cnt = @m; - $txt = ""; - for ($i = 2; $i < $cnt; $i++) { - $txt = $txt . $m[$i] . "@"; - } - } - print OUT $_; - ++$wroteline; - } elsif ($_ =~ /~.+~/) { - # line contains a ~text~ pair used to refer to indexing :-) - $txt = $_; - while ($txt =~ /~.+~/) { - @m = split("~", $txt); - - # word is the second position - $word = @m[1]; - $a = $index1{$word}; - $b = $index2{$word}; - $c = $index3{$word}; - - # if chapter (a) is zero it wasn't found - if ($a == 0) { - print "ERROR: the tag \"$word\" on line $srcline was not found previously marked.\n"; - } else { - # format the tag as x, x.y or x.y.z depending on the values - $str = $a; - $str = $str . ".$b" if ($b != 0); - $str = $str . ".$c" if ($c != 0); - - if ($b == 0 && $c == 0) { - # its a chapter - if ($a <= 10) { - if ($a == 1) { - $str = "chapter one"; - } elsif ($a == 2) { - $str = "chapter two"; - } elsif ($a == 3) { - $str = "chapter three"; - } elsif ($a == 4) { - $str = "chapter four"; - } elsif ($a == 5) { - $str = "chapter five"; - } elsif ($a == 6) { - $str = "chapter six"; - } elsif ($a == 7) { - $str = "chapter seven"; - } elsif ($a == 8) { - $str = "chapter eight"; - } elsif ($a == 9) { - $str = "chapter nine"; - } elsif ($a == 10) { - $str = "chapter ten"; - } - } else { - $str = "chapter " . $str; - } - } else { - $str = "section " . $str if ($b != 0 && $c == 0); - $str = "sub-section " . $str if ($b != 0 && $c != 0); - } - - #substitute - $_ =~ s/~\Q$word\E~/$str/; - - print "Found replacement tag for marker \"$word\" on line $srcline which refers to $str\n"; - } - - # remake rest of the line - $cnt = @m; - $txt = ""; - for ($i = 2; $i < $cnt; $i++) { - $txt = $txt . $m[$i] . "~"; - } - } - print OUT $_; - ++$wroteline; - } elsif ($_ =~ m/FIGU/) { - # FIGU,file,caption - chomp($_); - @m = split(",", $_); - print OUT "\\begin{center}\n\\begin{figure}[here]\n\\includegraphics{pics/$m[1]$graph}\n"; - print OUT "\\caption{$m[2]}\n\\label{pic:$m[1]}\n\\end{figure}\n\\end{center}\n"; - $wroteline += 4; - } else { - print OUT $_; - ++$wroteline; - } -} -print "Read $readline lines, wrote $wroteline lines\n"; - -close (OUT); -close (IN); - -system('perl -pli -e "s/\s*$//" tommath.tex'); diff --git a/libtommath/changes.txt b/libtommath/changes.txt index 3379f71..51da801 100644 --- a/libtommath/changes.txt +++ b/libtommath/changes.txt @@ -1,4 +1,4 @@ -XXX, 2017 +Aug 29th, 2017 v1.0.1 -- Dmitry Kovalenko provided fixes to mp_add_d() and mp_init_copy() -- Matt Johnston contributed some improvements to mp_div_2d(), diff --git a/libtommath/demo/demo.c b/libtommath/demo/demo.c deleted file mode 100644 index b46b7f8..0000000 --- a/libtommath/demo/demo.c +++ /dev/null @@ -1,986 +0,0 @@ -#include <string.h> -#include <time.h> - -#ifdef IOWNANATHLON -#include <unistd.h> -#define SLEEP sleep(4) -#else -#define SLEEP -#endif - -/* - * Configuration - */ -#ifndef LTM_DEMO_TEST_VS_MTEST -#define LTM_DEMO_TEST_VS_MTEST 1 -#endif - -#ifndef LTM_DEMO_TEST_REDUCE_2K_L -/* This test takes a moment so we disable it by default, but it can be: - * 0 to disable testing - * 1 to make the test with P = 2^1024 - 0x2A434 B9FDEC95 D8F9D550 FFFFFFFF FFFFFFFF - * 2 to make the test with P = 2^2048 - 0x1 00000000 00000000 00000000 00000000 4945DDBF 8EA2A91D 5776399B B83E188F - */ -#define LTM_DEMO_TEST_REDUCE_2K_L 0 -#endif - -#ifdef LTM_DEMO_REAL_RAND -#define LTM_DEMO_RAND_SEED time(NULL) -#else -#define LTM_DEMO_RAND_SEED 23 -#endif - -#include "tommath.h" - -void ndraw(mp_int * a, char *name) -{ - char buf[16000]; - - printf("%s: ", name); - mp_toradix(a, buf, 10); - printf("%s\n", buf); - mp_toradix(a, buf, 16); - printf("0x%s\n", buf); -} - -#if LTM_DEMO_TEST_VS_MTEST -static void draw(mp_int * a) -{ - ndraw(a, ""); -} -#endif - - -unsigned long lfsr = 0xAAAAAAAAUL; - -int lbit(void) -{ - if (lfsr & 0x80000000UL) { - lfsr = ((lfsr << 1) ^ 0x8000001BUL) & 0xFFFFFFFFUL; - return 1; - } else { - lfsr <<= 1; - return 0; - } -} - -#if defined(LTM_DEMO_REAL_RAND) && !defined(_WIN32) -static FILE* fd_urandom; -#endif -int myrng(unsigned char *dst, int len, void *dat) -{ - int x; - (void)dat; -#if defined(LTM_DEMO_REAL_RAND) - if (!fd_urandom) { -#if !defined(_WIN32) - fprintf(stderr, "\nno /dev/urandom\n"); -#endif - } - else { - return fread(dst, 1, len, fd_urandom); - } -#endif - for (x = 0; x < len; ) { - unsigned int r = (unsigned int)rand(); - do { - dst[x++] = r & 0xFF; - r >>= 8; - } while((r != 0) && (x < len)); - } - return len; -} - -#if LTM_DEMO_TEST_VS_MTEST != 0 -static void _panic(int l) -{ - fprintf(stderr, "\n%d: fgets failed\n", l); - exit(EXIT_FAILURE); -} -#endif - -mp_int a, b, c, d, e, f; - -static void _cleanup(void) -{ - mp_clear_multi(&a, &b, &c, &d, &e, &f, NULL); - printf("\n"); - -#ifdef LTM_DEMO_REAL_RAND - if(fd_urandom) - fclose(fd_urandom); -#endif -} -struct mp_sqrtmod_prime_st { - unsigned long p; - unsigned long n; - mp_digit r; -}; -struct mp_sqrtmod_prime_st sqrtmod_prime[] = { - { 5, 14, 3 }, - { 7, 9, 4 }, - { 113, 2, 62 } -}; -struct mp_jacobi_st { - unsigned long n; - int c[16]; -}; -struct mp_jacobi_st jacobi[] = { - { 3, { 1, -1, 0, 1, -1, 0, 1, -1, 0, 1, -1, 0, 1, -1, 0, 1 } }, - { 5, { 0, 1, -1, -1, 1, 0, 1, -1, -1, 1, 0, 1, -1, -1, 1, 0 } }, - { 7, { 1, -1, 1, -1, -1, 0, 1, 1, -1, 1, -1, -1, 0, 1, 1, -1 } }, - { 9, { -1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1 } }, -}; - -char cmd[4096], buf[4096]; -int main(void) -{ - unsigned rr; - int cnt, ix; -#if LTM_DEMO_TEST_VS_MTEST - unsigned long expt_n, add_n, sub_n, mul_n, div_n, sqr_n, mul2d_n, div2d_n, - gcd_n, lcm_n, inv_n, div2_n, mul2_n, add_d_n, sub_d_n; - char* ret; -#else - unsigned long s, t; - unsigned long long q, r; - mp_digit mp; - int i, n, err, should; -#endif - - if (mp_init_multi(&a, &b, &c, &d, &e, &f, NULL)!= MP_OKAY) - return EXIT_FAILURE; - - atexit(_cleanup); - -#if defined(LTM_DEMO_REAL_RAND) - if (!fd_urandom) { - fd_urandom = fopen("/dev/urandom", "r"); - if (!fd_urandom) { -#if !defined(_WIN32) - fprintf(stderr, "\ncould not open /dev/urandom\n"); -#endif - } - } -#endif - srand(LTM_DEMO_RAND_SEED); - -#ifdef MP_8BIT - printf("Digit size 8 Bit \n"); -#endif -#ifdef MP_16BIT - printf("Digit size 16 Bit \n"); -#endif -#ifdef MP_32BIT - printf("Digit size 32 Bit \n"); -#endif -#ifdef MP_64BIT - printf("Digit size 64 Bit \n"); -#endif - printf("Size of mp_digit: %u\n", (unsigned int)sizeof(mp_digit)); - printf("Size of mp_word: %u\n", (unsigned int)sizeof(mp_word)); - printf("DIGIT_BIT: %d\n", DIGIT_BIT); - printf("MP_PREC: %d\n", MP_PREC); - -#if LTM_DEMO_TEST_VS_MTEST == 0 - // trivial stuff - mp_set_int(&a, 5); - mp_neg(&a, &b); - if (mp_cmp(&a, &b) != MP_GT) { - return EXIT_FAILURE; - } - if (mp_cmp(&b, &a) != MP_LT) { - return EXIT_FAILURE; - } - mp_neg(&a, &a); - if (mp_cmp(&b, &a) != MP_EQ) { - return EXIT_FAILURE; - } - mp_abs(&a, &b); - if (mp_isneg(&b) != MP_NO) { - return EXIT_FAILURE; - } - mp_add_d(&a, 1, &b); - mp_add_d(&a, 6, &b); - - - mp_set_int(&a, 0); - mp_set_int(&b, 1); - if ((err = mp_jacobi(&a, &b, &i)) != MP_OKAY) { - printf("Failed executing mp_jacobi(0 | 1) %s.\n", mp_error_to_string(err)); - return EXIT_FAILURE; - } - if (i != 1) { - printf("Failed trivial mp_jacobi(0 | 1) %d != 1\n", i); - return EXIT_FAILURE; - } - for (cnt = 0; cnt < (int)(sizeof(jacobi)/sizeof(jacobi[0])); ++cnt) { - mp_set_int(&b, jacobi[cnt].n); - /* only test positive values of a */ - for (n = -5; n <= 10; ++n) { - mp_set_int(&a, abs(n)); - should = MP_OKAY; - if (n < 0) { - mp_neg(&a, &a); - /* Until #44 is fixed the negative a's must fail */ - should = MP_VAL; - } - if ((err = mp_jacobi(&a, &b, &i)) != should) { - printf("Failed executing mp_jacobi(%d | %lu) %s.\n", n, jacobi[cnt].n, mp_error_to_string(err)); - return EXIT_FAILURE; - } - if (err == MP_OKAY && i != jacobi[cnt].c[n + 5]) { - printf("Failed trivial mp_jacobi(%d | %lu) %d != %d\n", n, jacobi[cnt].n, i, jacobi[cnt].c[n + 5]); - return EXIT_FAILURE; - } - } - } - - // test mp_get_int - printf("\n\nTesting: mp_get_int"); - for (i = 0; i < 1000; ++i) { - t = ((unsigned long) rand () * rand () + 1) & 0xFFFFFFFF; - mp_set_int (&a, t); - if (t != mp_get_int (&a)) { - printf ("\nmp_get_int() bad result!"); - return EXIT_FAILURE; - } - } - mp_set_int(&a, 0); - if (mp_get_int(&a) != 0) { - printf("\nmp_get_int() bad result!"); - return EXIT_FAILURE; - } - mp_set_int(&a, 0xffffffff); - if (mp_get_int(&a) != 0xffffffff) { - printf("\nmp_get_int() bad result!"); - return EXIT_FAILURE; - } - - printf("\n\nTesting: mp_get_long\n"); - for (i = 0; i < (int)(sizeof(unsigned long)*CHAR_BIT) - 1; ++i) { - t = (1ULL << (i+1)) - 1; - if (!t) - t = -1; - printf(" t = 0x%lx i = %d\r", t, i); - do { - if (mp_set_long(&a, t) != MP_OKAY) { - printf("\nmp_set_long() error!"); - return EXIT_FAILURE; - } - s = mp_get_long(&a); - if (s != t) { - printf("\nmp_get_long() bad result! 0x%lx != 0x%lx", s, t); - return EXIT_FAILURE; - } - t <<= 1; - } while(t); - } - - printf("\n\nTesting: mp_get_long_long\n"); - for (i = 0; i < (int)(sizeof(unsigned long long)*CHAR_BIT) - 1; ++i) { - r = (1ULL << (i+1)) - 1; - if (!r) - r = -1; - printf(" r = 0x%llx i = %d\r", r, i); - do { - if (mp_set_long_long(&a, r) != MP_OKAY) { - printf("\nmp_set_long_long() error!"); - return EXIT_FAILURE; - } - q = mp_get_long_long(&a); - if (q != r) { - printf("\nmp_get_long_long() bad result! 0x%llx != 0x%llx", q, r); - return EXIT_FAILURE; - } - r <<= 1; - } while(r); - } - - // test mp_sqrt - printf("\n\nTesting: mp_sqrt\n"); - for (i = 0; i < 1000; ++i) { - printf ("%6d\r", i); - fflush (stdout); - n = (rand () & 15) + 1; - mp_rand (&a, n); - if (mp_sqrt (&a, &b) != MP_OKAY) { - printf ("\nmp_sqrt() error!"); - return EXIT_FAILURE; - } - mp_n_root_ex (&a, 2, &c, 0); - mp_n_root_ex (&a, 2, &d, 1); - if (mp_cmp_mag (&c, &d) != MP_EQ) { - printf ("\nmp_n_root_ex() bad result!"); - return EXIT_FAILURE; - } - if (mp_cmp_mag (&b, &c) != MP_EQ) { - printf ("mp_sqrt() bad result!\n"); - return EXIT_FAILURE; - } - } - - printf("\n\nTesting: mp_is_square\n"); - for (i = 0; i < 1000; ++i) { - printf ("%6d\r", i); - fflush (stdout); - - /* test mp_is_square false negatives */ - n = (rand () & 7) + 1; - mp_rand (&a, n); - mp_sqr (&a, &a); - if (mp_is_square (&a, &n) != MP_OKAY) { - printf ("\nfn:mp_is_square() error!"); - return EXIT_FAILURE; - } - if (n == 0) { - printf ("\nfn:mp_is_square() bad result!"); - return EXIT_FAILURE; - } - - /* test for false positives */ - mp_add_d (&a, 1, &a); - if (mp_is_square (&a, &n) != MP_OKAY) { - printf ("\nfp:mp_is_square() error!"); - return EXIT_FAILURE; - } - if (n == 1) { - printf ("\nfp:mp_is_square() bad result!"); - return EXIT_FAILURE; - } - - } - printf("\n\n"); - - // r^2 = n (mod p) - for (i = 0; i < (int)(sizeof(sqrtmod_prime)/sizeof(sqrtmod_prime[0])); ++i) { - mp_set_int(&a, sqrtmod_prime[i].p); - mp_set_int(&b, sqrtmod_prime[i].n); - if (mp_sqrtmod_prime(&b, &a, &c) != MP_OKAY) { - printf("Failed executing %d. mp_sqrtmod_prime\n", (i+1)); - return EXIT_FAILURE; - } - if (mp_cmp_d(&c, sqrtmod_prime[i].r) != MP_EQ) { - printf("Failed %d. trivial mp_sqrtmod_prime\n", (i+1)); - ndraw(&c, "r"); - return EXIT_FAILURE; - } - } - - /* test for size */ - for (ix = 10; ix < 128; ix++) { - printf ("Testing (not safe-prime): %9d bits \r", ix); - fflush (stdout); - err = mp_prime_random_ex (&a, 8, ix, - (rand () & 1) ? 0 : LTM_PRIME_2MSB_ON, myrng, - NULL); - if (err != MP_OKAY) { - printf ("failed with err code %d\n", err); - return EXIT_FAILURE; - } - if (mp_count_bits (&a) != ix) { - printf ("Prime is %d not %d bits!!!\n", mp_count_bits (&a), ix); - return EXIT_FAILURE; - } - } - printf("\n"); - - for (ix = 16; ix < 128; ix++) { - printf ("Testing ( safe-prime): %9d bits \r", ix); - fflush (stdout); - err = mp_prime_random_ex ( - &a, 8, ix, ((rand () & 1) ? 0 : LTM_PRIME_2MSB_ON) | LTM_PRIME_SAFE, - myrng, NULL); - if (err != MP_OKAY) { - printf ("failed with err code %d\n", err); - return EXIT_FAILURE; - } - if (mp_count_bits (&a) != ix) { - printf ("Prime is %d not %d bits!!!\n", mp_count_bits (&a), ix); - return EXIT_FAILURE; - } - /* let's see if it's really a safe prime */ - mp_sub_d (&a, 1, &a); - mp_div_2 (&a, &a); - mp_prime_is_prime (&a, 8, &cnt); - if (cnt != MP_YES) { - printf ("sub is not prime!\n"); - return EXIT_FAILURE; - } - } - - printf("\n\n"); - - // test montgomery - printf("Testing: montgomery...\n"); - for (i = 1; i <= 10; i++) { - if (i == 10) - i = 1000; - printf(" digit size: %2d\r", i); - fflush(stdout); - for (n = 0; n < 1000; n++) { - mp_rand(&a, i); - a.dp[0] |= 1; - - // let's see if R is right - mp_montgomery_calc_normalization(&b, &a); - mp_montgomery_setup(&a, &mp); - - // now test a random reduction - for (ix = 0; ix < 100; ix++) { - mp_rand(&c, 1 + abs(rand()) % (2*i)); - mp_copy(&c, &d); - mp_copy(&c, &e); - - mp_mod(&d, &a, &d); - mp_montgomery_reduce(&c, &a, mp); - mp_mulmod(&c, &b, &a, &c); - - if (mp_cmp(&c, &d) != MP_EQ) { -printf("d = e mod a, c = e MOD a\n"); -mp_todecimal(&a, buf); printf("a = %s\n", buf); -mp_todecimal(&e, buf); printf("e = %s\n", buf); -mp_todecimal(&d, buf); printf("d = %s\n", buf); -mp_todecimal(&c, buf); printf("c = %s\n", buf); -printf("compare no compare!\n"); return EXIT_FAILURE; } - /* only one big montgomery reduction */ - if (i > 10) - { - n = 1000; - ix = 100; - } - } - } - } - - printf("\n\n"); - - mp_read_radix(&a, "123456", 10); - mp_toradix_n(&a, buf, 10, 3); - printf("a == %s\n", buf); - mp_toradix_n(&a, buf, 10, 4); - printf("a == %s\n", buf); - mp_toradix_n(&a, buf, 10, 30); - printf("a == %s\n", buf); - - -#if 0 - for (;;) { - fgets(buf, sizeof(buf), stdin); - mp_read_radix(&a, buf, 10); - mp_prime_next_prime(&a, 5, 1); - mp_toradix(&a, buf, 10); - printf("%s, %lu\n", buf, a.dp[0] & 3); - } -#endif - - /* test mp_cnt_lsb */ - printf("\n\nTesting: mp_cnt_lsb"); - mp_set(&a, 1); - for (ix = 0; ix < 1024; ix++) { - if (mp_cnt_lsb (&a) != ix) { - printf ("Failed at %d, %d\n", ix, mp_cnt_lsb (&a)); - return EXIT_FAILURE; - } - mp_mul_2 (&a, &a); - } - -/* test mp_reduce_2k */ - printf("\n\nTesting: mp_reduce_2k\n"); - for (cnt = 3; cnt <= 128; ++cnt) { - mp_digit tmp; - - mp_2expt (&a, cnt); - mp_sub_d (&a, 2, &a); /* a = 2**cnt - 2 */ - - printf ("\r %4d bits", cnt); - printf ("(%d)", mp_reduce_is_2k (&a)); - mp_reduce_2k_setup (&a, &tmp); - printf ("(%lu)", (unsigned long) tmp); - for (ix = 0; ix < 1000; ix++) { - if (!(ix & 127)) { - printf ("."); - fflush (stdout); - } - mp_rand (&b, (cnt / DIGIT_BIT + 1) * 2); - mp_copy (&c, &b); - mp_mod (&c, &a, &c); - mp_reduce_2k (&b, &a, 2); - if (mp_cmp (&c, &b)) { - printf ("FAILED\n"); - return EXIT_FAILURE; - } - } - } - -/* test mp_div_3 */ - printf("\n\nTesting: mp_div_3...\n"); - mp_set(&d, 3); - for (cnt = 0; cnt < 10000;) { - mp_digit r2; - - if (!(++cnt & 127)) - { - printf("%9d\r", cnt); - fflush(stdout); - } - mp_rand(&a, abs(rand()) % 128 + 1); - mp_div(&a, &d, &b, &e); - mp_div_3(&a, &c, &r2); - - if (mp_cmp(&b, &c) || mp_cmp_d(&e, r2)) { - printf("\nmp_div_3 => Failure\n"); - } - } - printf("\nPassed div_3 testing"); - -/* test the DR reduction */ - printf("\n\nTesting: mp_dr_reduce...\n"); - for (cnt = 2; cnt < 32; cnt++) { - printf ("\r%d digit modulus", cnt); - mp_grow (&a, cnt); - mp_zero (&a); - for (ix = 1; ix < cnt; ix++) { - a.dp[ix] = MP_MASK; - } - a.used = cnt; - a.dp[0] = 3; - - mp_rand (&b, cnt - 1); - mp_copy (&b, &c); - - rr = 0; - do { - if (!(rr & 127)) { - printf ("."); - fflush (stdout); - } - mp_sqr (&b, &b); - mp_add_d (&b, 1, &b); - mp_copy (&b, &c); - - mp_mod (&b, &a, &b); - mp_dr_setup(&a, &mp), - mp_dr_reduce (&c, &a, mp); - - if (mp_cmp (&b, &c) != MP_EQ) { - printf ("Failed on trial %u\n", rr); - return EXIT_FAILURE; - } - } while (++rr < 500); - printf (" passed"); - fflush (stdout); - } - -#if LTM_DEMO_TEST_REDUCE_2K_L -/* test the mp_reduce_2k_l code */ -#if LTM_DEMO_TEST_REDUCE_2K_L == 1 -/* first load P with 2^1024 - 0x2A434 B9FDEC95 D8F9D550 FFFFFFFF FFFFFFFF */ - mp_2expt(&a, 1024); - mp_read_radix(&b, "2A434B9FDEC95D8F9D550FFFFFFFFFFFFFFFF", 16); - mp_sub(&a, &b, &a); -#elif LTM_DEMO_TEST_REDUCE_2K_L == 2 -/* p = 2^2048 - 0x1 00000000 00000000 00000000 00000000 4945DDBF 8EA2A91D 5776399B B83E188F */ - mp_2expt(&a, 2048); - mp_read_radix(&b, - "1000000000000000000000000000000004945DDBF8EA2A91D5776399BB83E188F", - 16); - mp_sub(&a, &b, &a); -#else -#error oops -#endif - - mp_todecimal(&a, buf); - printf("\n\np==%s\n", buf); -/* now mp_reduce_is_2k_l() should return */ - if (mp_reduce_is_2k_l(&a) != 1) { - printf("mp_reduce_is_2k_l() return 0, should be 1\n"); - return EXIT_FAILURE; - } - mp_reduce_2k_setup_l(&a, &d); - /* now do a million square+1 to see if it varies */ - mp_rand(&b, 64); - mp_mod(&b, &a, &b); - mp_copy(&b, &c); - printf("Testing: mp_reduce_2k_l..."); - fflush(stdout); - for (cnt = 0; cnt < (int)(1UL << 20); cnt++) { - mp_sqr(&b, &b); - mp_add_d(&b, 1, &b); - mp_reduce_2k_l(&b, &a, &d); - mp_sqr(&c, &c); - mp_add_d(&c, 1, &c); - mp_mod(&c, &a, &c); - if (mp_cmp(&b, &c) != MP_EQ) { - printf("mp_reduce_2k_l() failed at step %d\n", cnt); - mp_tohex(&b, buf); - printf("b == %s\n", buf); - mp_tohex(&c, buf); - printf("c == %s\n", buf); - return EXIT_FAILURE; - } - } - printf("...Passed\n"); -#endif /* LTM_DEMO_TEST_REDUCE_2K_L */ - -#else - - div2_n = mul2_n = inv_n = expt_n = lcm_n = gcd_n = add_n = - sub_n = mul_n = div_n = sqr_n = mul2d_n = div2d_n = cnt = add_d_n = - sub_d_n = 0; - - /* force KARA and TOOM to enable despite cutoffs */ - KARATSUBA_SQR_CUTOFF = KARATSUBA_MUL_CUTOFF = 8; - TOOM_SQR_CUTOFF = TOOM_MUL_CUTOFF = 16; - - for (;;) { - /* randomly clear and re-init one variable, this has the affect of triming the alloc space */ - switch (abs(rand()) % 7) { - case 0: - mp_clear(&a); - mp_init(&a); - break; - case 1: - mp_clear(&b); - mp_init(&b); - break; - case 2: - mp_clear(&c); - mp_init(&c); - break; - case 3: - mp_clear(&d); - mp_init(&d); - break; - case 4: - mp_clear(&e); - mp_init(&e); - break; - case 5: - mp_clear(&f); - mp_init(&f); - break; - case 6: - break; /* don't clear any */ - } - - - printf - ("%4lu/%4lu/%4lu/%4lu/%4lu/%4lu/%4lu/%4lu/%4lu/%4lu/%4lu/%4lu/%4lu/%4lu/%4lu ", - add_n, sub_n, mul_n, div_n, sqr_n, mul2d_n, div2d_n, gcd_n, lcm_n, - expt_n, inv_n, div2_n, mul2_n, add_d_n, sub_d_n); - ret=fgets(cmd, 4095, stdin); if(!ret){_panic(__LINE__);} - cmd[strlen(cmd) - 1] = 0; - printf("%-6s ]\r", cmd); - fflush(stdout); - if (!strcmp(cmd, "mul2d")) { - ++mul2d_n; - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&a, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - sscanf(buf, "%d", &rr); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&b, buf, 64); - - mp_mul_2d(&a, rr, &a); - a.sign = b.sign; - if (mp_cmp(&a, &b) != MP_EQ) { - printf("mul2d failed, rr == %d\n", rr); - draw(&a); - draw(&b); - return EXIT_FAILURE; - } - } else if (!strcmp(cmd, "div2d")) { - ++div2d_n; - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&a, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - sscanf(buf, "%d", &rr); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&b, buf, 64); - - mp_div_2d(&a, rr, &a, &e); - a.sign = b.sign; - if (a.used == b.used && a.used == 0) { - a.sign = b.sign = MP_ZPOS; - } - if (mp_cmp(&a, &b) != MP_EQ) { - printf("div2d failed, rr == %d\n", rr); - draw(&a); - draw(&b); - return EXIT_FAILURE; - } - } else if (!strcmp(cmd, "add")) { - ++add_n; - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&a, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&b, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&c, buf, 64); - mp_copy(&a, &d); - mp_add(&d, &b, &d); - if (mp_cmp(&c, &d) != MP_EQ) { - printf("add %lu failure!\n", add_n); - draw(&a); - draw(&b); - draw(&c); - draw(&d); - return EXIT_FAILURE; - } - - /* test the sign/unsigned storage functions */ - - rr = mp_signed_bin_size(&c); - mp_to_signed_bin(&c, (unsigned char *) cmd); - memset(cmd + rr, rand() & 255, sizeof(cmd) - rr); - mp_read_signed_bin(&d, (unsigned char *) cmd, rr); - if (mp_cmp(&c, &d) != MP_EQ) { - printf("mp_signed_bin failure!\n"); - draw(&c); - draw(&d); - return EXIT_FAILURE; - } - - - rr = mp_unsigned_bin_size(&c); - mp_to_unsigned_bin(&c, (unsigned char *) cmd); - memset(cmd + rr, rand() & 255, sizeof(cmd) - rr); - mp_read_unsigned_bin(&d, (unsigned char *) cmd, rr); - if (mp_cmp_mag(&c, &d) != MP_EQ) { - printf("mp_unsigned_bin failure!\n"); - draw(&c); - draw(&d); - return EXIT_FAILURE; - } - - } else if (!strcmp(cmd, "sub")) { - ++sub_n; - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&a, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&b, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&c, buf, 64); - mp_copy(&a, &d); - mp_sub(&d, &b, &d); - if (mp_cmp(&c, &d) != MP_EQ) { - printf("sub %lu failure!\n", sub_n); - draw(&a); - draw(&b); - draw(&c); - draw(&d); - return EXIT_FAILURE; - } - } else if (!strcmp(cmd, "mul")) { - ++mul_n; - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&a, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&b, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&c, buf, 64); - mp_copy(&a, &d); - mp_mul(&d, &b, &d); - if (mp_cmp(&c, &d) != MP_EQ) { - printf("mul %lu failure!\n", mul_n); - draw(&a); - draw(&b); - draw(&c); - draw(&d); - return EXIT_FAILURE; - } - } else if (!strcmp(cmd, "div")) { - ++div_n; - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&a, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&b, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&c, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&d, buf, 64); - - mp_div(&a, &b, &e, &f); - if (mp_cmp(&c, &e) != MP_EQ || mp_cmp(&d, &f) != MP_EQ) { - printf("div %lu %d, %d, failure!\n", div_n, mp_cmp(&c, &e), - mp_cmp(&d, &f)); - draw(&a); - draw(&b); - draw(&c); - draw(&d); - draw(&e); - draw(&f); - return EXIT_FAILURE; - } - - } else if (!strcmp(cmd, "sqr")) { - ++sqr_n; - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&a, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&b, buf, 64); - mp_copy(&a, &c); - mp_sqr(&c, &c); - if (mp_cmp(&b, &c) != MP_EQ) { - printf("sqr %lu failure!\n", sqr_n); - draw(&a); - draw(&b); - draw(&c); - return EXIT_FAILURE; - } - } else if (!strcmp(cmd, "gcd")) { - ++gcd_n; - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&a, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&b, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&c, buf, 64); - mp_copy(&a, &d); - mp_gcd(&d, &b, &d); - d.sign = c.sign; - if (mp_cmp(&c, &d) != MP_EQ) { - printf("gcd %lu failure!\n", gcd_n); - draw(&a); - draw(&b); - draw(&c); - draw(&d); - return EXIT_FAILURE; - } - } else if (!strcmp(cmd, "lcm")) { - ++lcm_n; - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&a, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&b, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&c, buf, 64); - mp_copy(&a, &d); - mp_lcm(&d, &b, &d); - d.sign = c.sign; - if (mp_cmp(&c, &d) != MP_EQ) { - printf("lcm %lu failure!\n", lcm_n); - draw(&a); - draw(&b); - draw(&c); - draw(&d); - return EXIT_FAILURE; - } - } else if (!strcmp(cmd, "expt")) { - ++expt_n; - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&a, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&b, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&c, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&d, buf, 64); - mp_copy(&a, &e); - mp_exptmod(&e, &b, &c, &e); - if (mp_cmp(&d, &e) != MP_EQ) { - printf("expt %lu failure!\n", expt_n); - draw(&a); - draw(&b); - draw(&c); - draw(&d); - draw(&e); - return EXIT_FAILURE; - } - } else if (!strcmp(cmd, "invmod")) { - ++inv_n; - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&a, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&b, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&c, buf, 64); - mp_invmod(&a, &b, &d); - mp_mulmod(&d, &a, &b, &e); - if (mp_cmp_d(&e, 1) != MP_EQ) { - printf("inv [wrong value from MPI?!] failure\n"); - draw(&a); - draw(&b); - draw(&c); - draw(&d); - draw(&e); - mp_gcd(&a, &b, &e); - draw(&e); - return EXIT_FAILURE; - } - - } else if (!strcmp(cmd, "div2")) { - ++div2_n; - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&a, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&b, buf, 64); - mp_div_2(&a, &c); - if (mp_cmp(&c, &b) != MP_EQ) { - printf("div_2 %lu failure\n", div2_n); - draw(&a); - draw(&b); - draw(&c); - return EXIT_FAILURE; - } - } else if (!strcmp(cmd, "mul2")) { - ++mul2_n; - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&a, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&b, buf, 64); - mp_mul_2(&a, &c); - if (mp_cmp(&c, &b) != MP_EQ) { - printf("mul_2 %lu failure\n", mul2_n); - draw(&a); - draw(&b); - draw(&c); - return EXIT_FAILURE; - } - } else if (!strcmp(cmd, "add_d")) { - ++add_d_n; - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&a, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - sscanf(buf, "%d", &ix); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&b, buf, 64); - mp_add_d(&a, ix, &c); - if (mp_cmp(&b, &c) != MP_EQ) { - printf("add_d %lu failure\n", add_d_n); - draw(&a); - draw(&b); - draw(&c); - printf("d == %d\n", ix); - return EXIT_FAILURE; - } - } else if (!strcmp(cmd, "sub_d")) { - ++sub_d_n; - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&a, buf, 64); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - sscanf(buf, "%d", &ix); - ret=fgets(buf, 4095, stdin); if(!ret){_panic(__LINE__);} - mp_read_radix(&b, buf, 64); - mp_sub_d(&a, ix, &c); - if (mp_cmp(&b, &c) != MP_EQ) { - printf("sub_d %lu failure\n", sub_d_n); - draw(&a); - draw(&b); - draw(&c); - printf("d == %d\n", ix); - return EXIT_FAILURE; - } - } else if (!strcmp(cmd, "exit")) { - printf("\nokay, exiting now\n"); - break; - } - } -#endif - return 0; -} - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ diff --git a/libtommath/demo/timing.c b/libtommath/demo/timing.c deleted file mode 100644 index 1bd8489..0000000 --- a/libtommath/demo/timing.c +++ /dev/null @@ -1,339 +0,0 @@ -#include <tommath.h> -#include <time.h> -#include <unistd.h> - -ulong64 _tt; - -#ifdef IOWNANATHLON -#include <unistd.h> -#define SLEEP sleep(4) -#else -#define SLEEP -#endif - -#ifdef LTM_TIMING_REAL_RAND -#define LTM_TIMING_RAND_SEED time(NULL) -#else -#define LTM_TIMING_RAND_SEED 23 -#endif - - -void ndraw(mp_int * a, char *name) -{ - char buf[4096]; - - printf("%s: ", name); - mp_toradix(a, buf, 64); - printf("%s\n", buf); -} - -static void draw(mp_int * a) -{ - ndraw(a, ""); -} - - -unsigned long lfsr = 0xAAAAAAAAUL; - -int lbit(void) -{ - if (lfsr & 0x80000000UL) { - lfsr = ((lfsr << 1) ^ 0x8000001BUL) & 0xFFFFFFFFUL; - return 1; - } else { - lfsr <<= 1; - return 0; - } -} - -/* RDTSC from Scott Duplichan */ -static ulong64 TIMFUNC(void) -{ -#if defined __GNUC__ -#if defined(__i386__) || defined(__x86_64__) - /* version from http://www.mcs.anl.gov/~kazutomo/rdtsc.html - * the old code always got a warning issued by gcc, clang did not complain... - */ - unsigned hi, lo; - __asm__ __volatile__ ("rdtsc" : "=a"(lo), "=d"(hi)); - return ((ulong64)lo)|( ((ulong64)hi)<<32); -#else /* gcc-IA64 version */ - unsigned long result; - __asm__ __volatile__("mov %0=ar.itc":"=r"(result)::"memory"); - - while (__builtin_expect((int) result == -1, 0)) - __asm__ __volatile__("mov %0=ar.itc":"=r"(result)::"memory"); - - return result; -#endif - - // Microsoft and Intel Windows compilers -#elif defined _M_IX86 - __asm rdtsc -#elif defined _M_AMD64 - return __rdtsc(); -#elif defined _M_IA64 -#if defined __INTEL_COMPILER -#include <ia64intrin.h> -#endif - return __getReg(3116); -#else -#error need rdtsc function for this build -#endif -} - -#define DO(x) x; x; -//#define DO4(x) DO2(x); DO2(x); -//#define DO8(x) DO4(x); DO4(x); -//#define DO(x) DO8(x); DO8(x); - -#ifdef TIMING_NO_LOGS -#define FOPEN(a, b) NULL -#define FPRINTF(a,b,c,d) -#define FFLUSH(a) -#define FCLOSE(a) (void)(a) -#else -#define FOPEN(a,b) fopen(a,b) -#define FPRINTF(a,b,c,d) fprintf(a,b,c,d) -#define FFLUSH(a) fflush(a) -#define FCLOSE(a) fclose(a) -#endif - -int main(void) -{ - ulong64 tt, gg, CLK_PER_SEC; - FILE *log, *logb, *logc, *logd; - mp_int a, b, c, d, e, f; - int n, cnt, ix, old_kara_m, old_kara_s, old_toom_m, old_toom_s; - unsigned rr; - - mp_init(&a); - mp_init(&b); - mp_init(&c); - mp_init(&d); - mp_init(&e); - mp_init(&f); - - srand(LTM_TIMING_RAND_SEED); - - - CLK_PER_SEC = TIMFUNC(); - sleep(1); - CLK_PER_SEC = TIMFUNC() - CLK_PER_SEC; - - printf("CLK_PER_SEC == %llu\n", CLK_PER_SEC); - log = FOPEN("logs/add.log", "w"); - for (cnt = 8; cnt <= 128; cnt += 8) { - SLEEP; - mp_rand(&a, cnt); - mp_rand(&b, cnt); - rr = 0; - tt = -1; - do { - gg = TIMFUNC(); - DO(mp_add(&a, &b, &c)); - gg = (TIMFUNC() - gg) >> 1; - if (tt > gg) - tt = gg; - } while (++rr < 100000); - printf("Adding\t\t%4d-bit => %9llu/sec, %9llu cycles\n", - mp_count_bits(&a), CLK_PER_SEC / tt, tt); - FPRINTF(log, "%d %9llu\n", cnt * DIGIT_BIT, tt); - FFLUSH(log); - } - FCLOSE(log); - - log = FOPEN("logs/sub.log", "w"); - for (cnt = 8; cnt <= 128; cnt += 8) { - SLEEP; - mp_rand(&a, cnt); - mp_rand(&b, cnt); - rr = 0; - tt = -1; - do { - gg = TIMFUNC(); - DO(mp_sub(&a, &b, &c)); - gg = (TIMFUNC() - gg) >> 1; - if (tt > gg) - tt = gg; - } while (++rr < 100000); - - printf("Subtracting\t\t%4d-bit => %9llu/sec, %9llu cycles\n", - mp_count_bits(&a), CLK_PER_SEC / tt, tt); - FPRINTF(log, "%d %9llu\n", cnt * DIGIT_BIT, tt); - FFLUSH(log); - } - FCLOSE(log); - - /* do mult/square twice, first without karatsuba and second with */ - old_kara_m = KARATSUBA_MUL_CUTOFF; - old_kara_s = KARATSUBA_SQR_CUTOFF; - /* currently toom-cook cut-off is too high to kick in, so we just use the karatsuba values */ - old_toom_m = old_kara_m; - old_toom_s = old_kara_m; - for (ix = 0; ix < 3; ix++) { - printf("With%s Karatsuba, With%s Toom\n", (ix == 0) ? "out" : "", (ix == 1) ? "out" : ""); - - KARATSUBA_MUL_CUTOFF = (ix == 1) ? old_kara_m : 9999; - KARATSUBA_SQR_CUTOFF = (ix == 1) ? old_kara_s : 9999; - TOOM_MUL_CUTOFF = (ix == 2) ? old_toom_m : 9999; - TOOM_SQR_CUTOFF = (ix == 2) ? old_toom_s : 9999; - - log = FOPEN((ix == 0) ? "logs/mult.log" : (ix == 1) ? "logs/mult_kara.log" : "logs/mult_toom.log", "w"); - for (cnt = 4; cnt <= 10240 / DIGIT_BIT; cnt += 2) { - SLEEP; - mp_rand(&a, cnt); - mp_rand(&b, cnt); - rr = 0; - tt = -1; - do { - gg = TIMFUNC(); - DO(mp_mul(&a, &b, &c)); - gg = (TIMFUNC() - gg) >> 1; - if (tt > gg) - tt = gg; - } while (++rr < 100); - printf("Multiplying\t%4d-bit => %9llu/sec, %9llu cycles\n", - mp_count_bits(&a), CLK_PER_SEC / tt, tt); - FPRINTF(log, "%d %9llu\n", mp_count_bits(&a), tt); - FFLUSH(log); - } - FCLOSE(log); - - log = FOPEN((ix == 0) ? "logs/sqr.log" : (ix == 1) ? "logs/sqr_kara.log" : "logs/sqr_toom.log", "w"); - for (cnt = 4; cnt <= 10240 / DIGIT_BIT; cnt += 2) { - SLEEP; - mp_rand(&a, cnt); - rr = 0; - tt = -1; - do { - gg = TIMFUNC(); - DO(mp_sqr(&a, &b)); - gg = (TIMFUNC() - gg) >> 1; - if (tt > gg) - tt = gg; - } while (++rr < 100); - printf("Squaring\t%4d-bit => %9llu/sec, %9llu cycles\n", - mp_count_bits(&a), CLK_PER_SEC / tt, tt); - FPRINTF(log, "%d %9llu\n", mp_count_bits(&a), tt); - FFLUSH(log); - } - FCLOSE(log); - - } - - { - char *primes[] = { - /* 2K large moduli */ - "179769313486231590772930519078902473361797697894230657273430081157732675805500963132708477322407536021120113879871393357658789768814416622492847430639474124377767893424865485276302219601246094119453082952085005768838150682342462881473913110540827237163350510684586239334100047359817950870678242457666208137217", - "32317006071311007300714876688669951960444102669715484032130345427524655138867890893197201411522913463688717960921898019494119559150490921095088152386448283120630877367300996091750197750389652106796057638384067568276792218642619756161838094338476170470581645852036305042887575891541065808607552399123930385521914333389668342420684974786564569494856176035326322058077805659331026192708460314150258592864177116725943603718461857357598351152301645904403697613233287231227125684710820209725157101726931323469678542580656697935045997268352998638099733077152121140120031150424541696791951097529546801429027668869927491725169", - "1044388881413152506691752710716624382579964249047383780384233483283953907971557456848826811934997558340890106714439262837987573438185793607263236087851365277945956976543709998340361590134383718314428070011855946226376318839397712745672334684344586617496807908705803704071284048740118609114467977783598029006686938976881787785946905630190260940599579453432823469303026696443059025015972399867714215541693835559885291486318237914434496734087811872639496475100189041349008417061675093668333850551032972088269550769983616369411933015213796825837188091833656751221318492846368125550225998300412344784862595674492194617023806505913245610825731835380087608622102834270197698202313169017678006675195485079921636419370285375124784014907159135459982790513399611551794271106831134090584272884279791554849782954323534517065223269061394905987693002122963395687782878948440616007412945674919823050571642377154816321380631045902916136926708342856440730447899971901781465763473223850267253059899795996090799469201774624817718449867455659250178329070473119433165550807568221846571746373296884912819520317457002440926616910874148385078411929804522981857338977648103126085902995208257421855249796721729039744118165938433694823325696642096892124547425283", - /* 2K moduli mersenne primes */ - "6864797660130609714981900799081393217269435300143305409394463459185543183397656052122559640661454554977296311391480858037121987999716643812574028291115057151", - "531137992816767098689588206552468627329593117727031923199444138200403559860852242739162502265229285668889329486246501015346579337652707239409519978766587351943831270835393219031728127", - "10407932194664399081925240327364085538615262247266704805319112350403608059673360298012239441732324184842421613954281007791383566248323464908139906605677320762924129509389220345773183349661583550472959420547689811211693677147548478866962501384438260291732348885311160828538416585028255604666224831890918801847068222203140521026698435488732958028878050869736186900714720710555703168729087", - "1475979915214180235084898622737381736312066145333169775147771216478570297878078949377407337049389289382748507531496480477281264838760259191814463365330269540496961201113430156902396093989090226259326935025281409614983499388222831448598601834318536230923772641390209490231836446899608210795482963763094236630945410832793769905399982457186322944729636418890623372171723742105636440368218459649632948538696905872650486914434637457507280441823676813517852099348660847172579408422316678097670224011990280170474894487426924742108823536808485072502240519452587542875349976558572670229633962575212637477897785501552646522609988869914013540483809865681250419497686697771007", - "259117086013202627776246767922441530941818887553125427303974923161874019266586362086201209516800483406550695241733194177441689509238807017410377709597512042313066624082916353517952311186154862265604547691127595848775610568757931191017711408826252153849035830401185072116424747461823031471398340229288074545677907941037288235820705892351068433882986888616658650280927692080339605869308790500409503709875902119018371991620994002568935113136548829739112656797303241986517250116412703509705427773477972349821676443446668383119322540099648994051790241624056519054483690809616061625743042361721863339415852426431208737266591962061753535748892894599629195183082621860853400937932839420261866586142503251450773096274235376822938649407127700846077124211823080804139298087057504713825264571448379371125032081826126566649084251699453951887789613650248405739378594599444335231188280123660406262468609212150349937584782292237144339628858485938215738821232393687046160677362909315071", - "190797007524439073807468042969529173669356994749940177394741882673528979787005053706368049835514900244303495954950709725762186311224148828811920216904542206960744666169364221195289538436845390250168663932838805192055137154390912666527533007309292687539092257043362517857366624699975402375462954490293259233303137330643531556539739921926201438606439020075174723029056838272505051571967594608350063404495977660656269020823960825567012344189908927956646011998057988548630107637380993519826582389781888135705408653045219655801758081251164080554609057468028203308718724654081055323215860189611391296030471108443146745671967766308925858547271507311563765171008318248647110097614890313562856541784154881743146033909602737947385055355960331855614540900081456378659068370317267696980001187750995491090350108417050917991562167972281070161305972518044872048331306383715094854938415738549894606070722584737978176686422134354526989443028353644037187375385397838259511833166416134323695660367676897722287918773420968982326089026150031515424165462111337527431154890666327374921446276833564519776797633875503548665093914556482031482248883127023777039667707976559857333357013727342079099064400455741830654320379350833236245819348824064783585692924881021978332974949906122664421376034687815350484991", - - /* DR moduli */ - "14059105607947488696282932836518693308967803494693489478439861164411992439598399594747002144074658928593502845729752797260025831423419686528151609940203368612079", - "101745825697019260773923519755878567461315282017759829107608914364075275235254395622580447400994175578963163918967182013639660669771108475957692810857098847138903161308502419410142185759152435680068435915159402496058513611411688900243039", - "736335108039604595805923406147184530889923370574768772191969612422073040099331944991573923112581267542507986451953227192970402893063850485730703075899286013451337291468249027691733891486704001513279827771740183629161065194874727962517148100775228363421083691764065477590823919364012917984605619526140821797602431", - "38564998830736521417281865696453025806593491967131023221754800625044118265468851210705360385717536794615180260494208076605798671660719333199513807806252394423283413430106003596332513246682903994829528690198205120921557533726473585751382193953592127439965050261476810842071573684505878854588706623484573925925903505747545471088867712185004135201289273405614415899438276535626346098904241020877974002916168099951885406379295536200413493190419727789712076165162175783", - "542189391331696172661670440619180536749994166415993334151601745392193484590296600979602378676624808129613777993466242203025054573692562689251250471628358318743978285860720148446448885701001277560572526947619392551574490839286458454994488665744991822837769918095117129546414124448777033941223565831420390846864429504774477949153794689948747680362212954278693335653935890352619041936727463717926744868338358149568368643403037768649616778526013610493696186055899318268339432671541328195724261329606699831016666359440874843103020666106568222401047720269951530296879490444224546654729111504346660859907296364097126834834235287147", - "1487259134814709264092032648525971038895865645148901180585340454985524155135260217788758027400478312256339496385275012465661575576202252063145698732079880294664220579764848767704076761853197216563262660046602703973050798218246170835962005598561669706844469447435461092542265792444947706769615695252256130901271870341005768912974433684521436211263358097522726462083917939091760026658925757076733484173202927141441492573799914240222628795405623953109131594523623353044898339481494120112723445689647986475279242446083151413667587008191682564376412347964146113898565886683139407005941383669325997475076910488086663256335689181157957571445067490187939553165903773554290260531009121879044170766615232300936675369451260747671432073394867530820527479172464106442450727640226503746586340279816318821395210726268291535648506190714616083163403189943334431056876038286530365757187367147446004855912033137386225053275419626102417236133948503", - "1095121115716677802856811290392395128588168592409109494900178008967955253005183831872715423151551999734857184538199864469605657805519106717529655044054833197687459782636297255219742994736751541815269727940751860670268774903340296040006114013971309257028332849679096824800250742691718610670812374272414086863715763724622797509437062518082383056050144624962776302147890521249477060215148275163688301275847155316042279405557632639366066847442861422164832655874655824221577849928863023018366835675399949740429332468186340518172487073360822220449055340582568461568645259954873303616953776393853174845132081121976327462740354930744487429617202585015510744298530101547706821590188733515880733527449780963163909830077616357506845523215289297624086914545378511082534229620116563260168494523906566709418166011112754529766183554579321224940951177394088465596712620076240067370589036924024728375076210477267488679008016579588696191194060127319035195370137160936882402244399699172017835144537488486396906144217720028992863941288217185353914991583400421682751000603596655790990815525126154394344641336397793791497068253936771017031980867706707490224041075826337383538651825493679503771934836094655802776331664261631740148281763487765852746577808019633679", - - /* generic unrestricted moduli */ - "17933601194860113372237070562165128350027320072176844226673287945873370751245439587792371960615073855669274087805055507977323024886880985062002853331424203", - "2893527720709661239493896562339544088620375736490408468011883030469939904368086092336458298221245707898933583190713188177399401852627749210994595974791782790253946539043962213027074922559572312141181787434278708783207966459019479487", - "347743159439876626079252796797422223177535447388206607607181663903045907591201940478223621722118173270898487582987137708656414344685816179420855160986340457973820182883508387588163122354089264395604796675278966117567294812714812796820596564876450716066283126720010859041484786529056457896367683122960411136319", - "47266428956356393164697365098120418976400602706072312735924071745438532218237979333351774907308168340693326687317443721193266215155735814510792148768576498491199122744351399489453533553203833318691678263241941706256996197460424029012419012634671862283532342656309677173602509498417976091509154360039893165037637034737020327399910409885798185771003505320583967737293415979917317338985837385734747478364242020380416892056650841470869294527543597349250299539682430605173321029026555546832473048600327036845781970289288898317888427517364945316709081173840186150794397479045034008257793436817683392375274635794835245695887", - "436463808505957768574894870394349739623346440601945961161254440072143298152040105676491048248110146278752857839930515766167441407021501229924721335644557342265864606569000117714935185566842453630868849121480179691838399545644365571106757731317371758557990781880691336695584799313313687287468894148823761785582982549586183756806449017542622267874275103877481475534991201849912222670102069951687572917937634467778042874315463238062009202992087620963771759666448266532858079402669920025224220613419441069718482837399612644978839925207109870840278194042158748845445131729137117098529028886770063736487420613144045836803985635654192482395882603511950547826439092832800532152534003936926017612446606135655146445620623395788978726744728503058670046885876251527122350275750995227", - "11424167473351836398078306042624362277956429440521137061889702611766348760692206243140413411077394583180726863277012016602279290144126785129569474909173584789822341986742719230331946072730319555984484911716797058875905400999504305877245849119687509023232790273637466821052576859232452982061831009770786031785669030271542286603956118755585683996118896215213488875253101894663403069677745948305893849505434201763745232895780711972432011344857521691017896316861403206449421332243658855453435784006517202894181640562433575390821384210960117518650374602256601091379644034244332285065935413233557998331562749140202965844219336298970011513882564935538704289446968322281451907487362046511461221329799897350993370560697505809686438782036235372137015731304779072430260986460269894522159103008260495503005267165927542949439526272736586626709581721032189532726389643625590680105784844246152702670169304203783072275089194754889511973916207", - "1214855636816562637502584060163403830270705000634713483015101384881871978446801224798536155406895823305035467591632531067547890948695117172076954220727075688048751022421198712032848890056357845974246560748347918630050853933697792254955890439720297560693579400297062396904306270145886830719309296352765295712183040773146419022875165382778007040109957609739589875590885701126197906063620133954893216612678838507540777138437797705602453719559017633986486649523611975865005712371194067612263330335590526176087004421363598470302731349138773205901447704682181517904064735636518462452242791676541725292378925568296858010151852326316777511935037531017413910506921922450666933202278489024521263798482237150056835746454842662048692127173834433089016107854491097456725016327709663199738238442164843147132789153725513257167915555162094970853584447993125488607696008169807374736711297007473812256272245489405898470297178738029484459690836250560495461579533254473316340608217876781986188705928270735695752830825527963838355419762516246028680280988020401914551825487349990306976304093109384451438813251211051597392127491464898797406789175453067960072008590614886532333015881171367104445044718144312416815712216611576221546455968770801413440778423979", - NULL - }; - log = FOPEN("logs/expt.log", "w"); - logb = FOPEN("logs/expt_dr.log", "w"); - logc = FOPEN("logs/expt_2k.log", "w"); - logd = FOPEN("logs/expt_2kl.log", "w"); - for (n = 0; primes[n]; n++) { - SLEEP; - mp_read_radix(&a, primes[n], 10); - mp_zero(&b); - for (rr = 0; rr < (unsigned) mp_count_bits(&a); rr++) { - mp_mul_2(&b, &b); - b.dp[0] |= lbit(); - b.used += 1; - } - mp_sub_d(&a, 1, &c); - mp_mod(&b, &c, &b); - mp_set(&c, 3); - rr = 0; - tt = -1; - do { - gg = TIMFUNC(); - DO(mp_exptmod(&c, &b, &a, &d)); - gg = (TIMFUNC() - gg) >> 1; - if (tt > gg) - tt = gg; - } while (++rr < 10); - mp_sub_d(&a, 1, &e); - mp_sub(&e, &b, &b); - mp_exptmod(&c, &b, &a, &e); /* c^(p-1-b) mod a */ - mp_mulmod(&e, &d, &a, &d); /* c^b * c^(p-1-b) == c^p-1 == 1 */ - if (mp_cmp_d(&d, 1)) { - printf("Different (%d)!!!\n", mp_count_bits(&a)); - draw(&d); - exit(0); - } - printf("Exponentiating\t%4d-bit => %9llu/sec, %9llu cycles\n", - mp_count_bits(&a), CLK_PER_SEC / tt, tt); - FPRINTF(n < 4 ? logd : (n < 9) ? logc : (n < 16) ? logb : log, - "%d %9llu\n", mp_count_bits(&a), tt); - } - } - FCLOSE(log); - FCLOSE(logb); - FCLOSE(logc); - FCLOSE(logd); - - log = FOPEN("logs/invmod.log", "w"); - for (cnt = 4; cnt <= 32; cnt += 4) { - SLEEP; - mp_rand(&a, cnt); - mp_rand(&b, cnt); - - do { - mp_add_d(&b, 1, &b); - mp_gcd(&a, &b, &c); - } while (mp_cmp_d(&c, 1) != MP_EQ); - - rr = 0; - tt = -1; - do { - gg = TIMFUNC(); - DO(mp_invmod(&b, &a, &c)); - gg = (TIMFUNC() - gg) >> 1; - if (tt > gg) - tt = gg; - } while (++rr < 1000); - mp_mulmod(&b, &c, &a, &d); - if (mp_cmp_d(&d, 1) != MP_EQ) { - printf("Failed to invert\n"); - return 0; - } - printf("Inverting mod\t%4d-bit => %9llu/sec, %9llu cycles\n", - mp_count_bits(&a), CLK_PER_SEC / tt, tt); - FPRINTF(log, "%d %9llu\n", cnt * DIGIT_BIT, tt); - } - FCLOSE(log); - - return 0; -} - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ diff --git a/libtommath/dep.pl b/libtommath/dep.pl deleted file mode 100644 index 0a5d19a..0000000 --- a/libtommath/dep.pl +++ /dev/null @@ -1,123 +0,0 @@ -#!/usr/bin/perl -# -# Walk through source, add labels and make classes -# -#use strict; - -my %deplist; - -#open class file and write preamble -open(CLASS, ">tommath_class.h") or die "Couldn't open tommath_class.h for writing\n"; -print CLASS "#if !(defined(LTM1) && defined(LTM2) && defined(LTM3))\n#if defined(LTM2)\n#define LTM3\n#endif\n#if defined(LTM1)\n#define LTM2\n#endif\n#define LTM1\n\n#if defined(LTM_ALL)\n"; - -foreach my $filename (glob "bn*.c") { - my $define = $filename; - -print "Processing $filename\n"; - - # convert filename to upper case so we can use it as a define - $define =~ tr/[a-z]/[A-Z]/; - $define =~ tr/\./_/; - print CLASS "#define $define\n"; - - # now copy text and apply #ifdef as required - my $apply = 0; - open(SRC, "<$filename"); - open(OUT, ">tmp"); - - # first line will be the #ifdef - my $line = <SRC>; - if ($line =~ /include/) { - print OUT $line; - } else { - print OUT "#include <tommath.h>\n#ifdef $define\n$line"; - $apply = 1; - } - while (<SRC>) { - if (!($_ =~ /tommath\.h/)) { - print OUT $_; - } - } - if ($apply == 1) { - print OUT "#endif\n"; - } - close SRC; - close OUT; - - unlink($filename); - rename("tmp", $filename); -} -print CLASS "#endif\n\n"; - -# now do classes - -foreach my $filename (glob "bn*.c") { - open(SRC, "<$filename") or die "Can't open source file!\n"; - - # convert filename to upper case so we can use it as a define - $filename =~ tr/[a-z]/[A-Z]/; - $filename =~ tr/\./_/; - - print CLASS "#if defined($filename)\n"; - my $list = $filename; - - # scan for mp_* and make classes - while (<SRC>) { - my $line = $_; - while ($line =~ m/(fast_)*(s_)*mp\_[a-z_0-9]*/) { - $line = $'; - # now $& is the match, we want to skip over LTM keywords like - # mp_int, mp_word, mp_digit - if (!($& eq "mp_digit") && !($& eq "mp_word") && !($& eq "mp_int") && !($& eq "mp_min_u32")) { - my $a = $&; - $a =~ tr/[a-z]/[A-Z]/; - $a = "BN_" . $a . "_C"; - if (!($list =~ /$a/)) { - print CLASS " #define $a\n"; - } - $list = $list . "," . $a; - } - } - } - @deplist{$filename} = $list; - - print CLASS "#endif\n\n"; - close SRC; -} - -print CLASS "#ifdef LTM3\n#define LTM_LAST\n#endif\n#include <tommath_superclass.h>\n#include <tommath_class.h>\n#else\n#define LTM_LAST\n#endif\n"; -close CLASS; - -#now let's make a cool call graph... - -open(OUT,">callgraph.txt"); -$indent = 0; -foreach (keys %deplist) { - $list = ""; - draw_func(@deplist{$_}); - print OUT "\n\n"; -} -close(OUT); - -sub draw_func() -{ - my @funcs = split(",", $_[0]); - if ($list =~ /@funcs[0]/) { - return; - } else { - $list = $list . @funcs[0]; - } - if ($indent == 0) { } - elsif ($indent >= 1) { print OUT "| " x ($indent - 1) . "+--->"; } - print OUT @funcs[0] . "\n"; - shift @funcs; - my $temp = $list; - foreach my $i (@funcs) { - ++$indent; - draw_func(@deplist{$i}); - --$indent; - } - $list = $temp; -} - - diff --git a/libtommath/etc/2kprime.1 b/libtommath/etc/2kprime.1 deleted file mode 100644 index c41ded1..0000000 --- a/libtommath/etc/2kprime.1 +++ /dev/null @@ -1,2 +0,0 @@ -256-bits (k = 36113) = 115792089237316195423570985008687907853269984665640564039457584007913129603823 -512-bits (k = 38117) = 13407807929942597099574024998205846127479365820592393377723561443721764030073546976801874298166903427690031858186486050853753882811946569946433649006045979 diff --git a/libtommath/etc/2kprime.c b/libtommath/etc/2kprime.c deleted file mode 100644 index 9450283..0000000 --- a/libtommath/etc/2kprime.c +++ /dev/null @@ -1,84 +0,0 @@ -/* Makes safe primes of a 2k nature */ -#include <tommath.h> -#include <time.h> - -int sizes[] = {256, 512, 768, 1024, 1536, 2048, 3072, 4096}; - -int main(void) -{ - char buf[2000]; - int x, y; - mp_int q, p; - FILE *out; - clock_t t1; - mp_digit z; - - mp_init_multi(&q, &p, NULL); - - out = fopen("2kprime.1", "w"); - for (x = 0; x < (int)(sizeof(sizes) / sizeof(sizes[0])); x++) { - top: - mp_2expt(&q, sizes[x]); - mp_add_d(&q, 3, &q); - z = -3; - - t1 = clock(); - for(;;) { - mp_sub_d(&q, 4, &q); - z += 4; - - if (z > MP_MASK) { - printf("No primes of size %d found\n", sizes[x]); - break; - } - - if (clock() - t1 > CLOCKS_PER_SEC) { - printf("."); fflush(stdout); -// sleep((clock() - t1 + CLOCKS_PER_SEC/2)/CLOCKS_PER_SEC); - t1 = clock(); - } - - /* quick test on q */ - mp_prime_is_prime(&q, 1, &y); - if (y == 0) { - continue; - } - - /* find (q-1)/2 */ - mp_sub_d(&q, 1, &p); - mp_div_2(&p, &p); - mp_prime_is_prime(&p, 3, &y); - if (y == 0) { - continue; - } - - /* test on q */ - mp_prime_is_prime(&q, 3, &y); - if (y == 0) { - continue; - } - - break; - } - - if (y == 0) { - ++sizes[x]; - goto top; - } - - mp_toradix(&q, buf, 10); - printf("\n\n%d-bits (k = %lu) = %s\n", sizes[x], z, buf); - fprintf(out, "%d-bits (k = %lu) = %s\n", sizes[x], z, buf); fflush(out); - } - - return 0; -} - - - - - - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ diff --git a/libtommath/etc/drprime.c b/libtommath/etc/drprime.c deleted file mode 100644 index c7d253f..0000000 --- a/libtommath/etc/drprime.c +++ /dev/null @@ -1,64 +0,0 @@ -/* Makes safe primes of a DR nature */ -#include <tommath.h> - -int sizes[] = { 1+256/DIGIT_BIT, 1+512/DIGIT_BIT, 1+768/DIGIT_BIT, 1+1024/DIGIT_BIT, 1+2048/DIGIT_BIT, 1+4096/DIGIT_BIT }; -int main(void) -{ - int res, x, y; - char buf[4096]; - FILE *out; - mp_int a, b; - - mp_init(&a); - mp_init(&b); - - out = fopen("drprimes.txt", "w"); - for (x = 0; x < (int)(sizeof(sizes)/sizeof(sizes[0])); x++) { - top: - printf("Seeking a %d-bit safe prime\n", sizes[x] * DIGIT_BIT); - mp_grow(&a, sizes[x]); - mp_zero(&a); - for (y = 1; y < sizes[x]; y++) { - a.dp[y] = MP_MASK; - } - - /* make a DR modulus */ - a.dp[0] = -1; - a.used = sizes[x]; - - /* now loop */ - res = 0; - for (;;) { - a.dp[0] += 4; - if (a.dp[0] >= MP_MASK) break; - mp_prime_is_prime(&a, 1, &res); - if (res == 0) continue; - printf("."); fflush(stdout); - mp_sub_d(&a, 1, &b); - mp_div_2(&b, &b); - mp_prime_is_prime(&b, 3, &res); - if (res == 0) continue; - mp_prime_is_prime(&a, 3, &res); - if (res == 1) break; - } - - if (res != 1) { - printf("Error not DR modulus\n"); sizes[x] += 1; goto top; - } else { - mp_toradix(&a, buf, 10); - printf("\n\np == %s\n\n", buf); - fprintf(out, "%d-bit prime:\np == %s\n\n", mp_count_bits(&a), buf); fflush(out); - } - } - fclose(out); - - mp_clear(&a); - mp_clear(&b); - - return 0; -} - - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ diff --git a/libtommath/etc/drprimes.28 b/libtommath/etc/drprimes.28 deleted file mode 100644 index 9d438ad..0000000 --- a/libtommath/etc/drprimes.28 +++ /dev/null @@ -1,25 +0,0 @@ -DR safe primes for 28-bit digits. - -224-bit prime: -p == 26959946667150639794667015087019630673637144422540572481103341844143 - -532-bit prime: -p == 14059105607947488696282932836518693308967803494693489478439861164411992439598399594747002144074658928593502845729752797260025831423419686528151609940203368691747 - -784-bit prime: -p == 101745825697019260773923519755878567461315282017759829107608914364075275235254395622580447400994175578963163918967182013639660669771108475957692810857098847138903161308502419410142185759152435680068435915159402496058513611411688900243039 - -1036-bit prime: -p == 736335108039604595805923406147184530889923370574768772191969612422073040099331944991573923112581267542507986451953227192970402893063850485730703075899286013451337291468249027691733891486704001513279827771740183629161065194874727962517148100775228363421083691764065477590823919364012917984605619526140821798437127 - -1540-bit prime: -p == 38564998830736521417281865696453025806593491967131023221754800625044118265468851210705360385717536794615180260494208076605798671660719333199513807806252394423283413430106003596332513246682903994829528690198205120921557533726473585751382193953592127439965050261476810842071573684505878854588706623484573925925903505747545471088867712185004135201289273405614415899438276535626346098904241020877974002916168099951885406379295536200413493190419727789712076165162175783 - -2072-bit prime: -p == 542189391331696172661670440619180536749994166415993334151601745392193484590296600979602378676624808129613777993466242203025054573692562689251250471628358318743978285860720148446448885701001277560572526947619392551574490839286458454994488665744991822837769918095117129546414124448777033941223565831420390846864429504774477949153794689948747680362212954278693335653935890352619041936727463717926744868338358149568368643403037768649616778526013610493696186055899318268339432671541328195724261329606699831016666359440874843103020666106568222401047720269951530296879490444224546654729111504346660859907296364097126834834235287147 - -3080-bit prime: -p == 1487259134814709264092032648525971038895865645148901180585340454985524155135260217788758027400478312256339496385275012465661575576202252063145698732079880294664220579764848767704076761853197216563262660046602703973050798218246170835962005598561669706844469447435461092542265792444947706769615695252256130901271870341005768912974433684521436211263358097522726462083917939091760026658925757076733484173202927141441492573799914240222628795405623953109131594523623353044898339481494120112723445689647986475279242446083151413667587008191682564376412347964146113898565886683139407005941383669325997475076910488086663256335689181157957571445067490187939553165903773554290260531009121879044170766615232300936675369451260747671432073394867530820527479172464106442450727640226503746586340279816318821395210726268291535648506190714616083163403189943334431056876038286530365757187367147446004855912033137386225053275419626102417236133948503 - -4116-bit prime: -p == 1095121115716677802856811290392395128588168592409109494900178008967955253005183831872715423151551999734857184538199864469605657805519106717529655044054833197687459782636297255219742994736751541815269727940751860670268774903340296040006114013971309257028332849679096824800250742691718610670812374272414086863715763724622797509437062518082383056050144624962776302147890521249477060215148275163688301275847155316042279405557632639366066847442861422164832655874655824221577849928863023018366835675399949740429332468186340518172487073360822220449055340582568461568645259954873303616953776393853174845132081121976327462740354930744487429617202585015510744298530101547706821590188733515880733527449780963163909830077616357506845523215289297624086914545378511082534229620116563260168494523906566709418166011112754529766183554579321224940951177394088465596712620076240067370589036924024728375076210477267488679008016579588696191194060127319035195370137160936882402244399699172017835144537488486396906144217720028992863941288217185353914991583400421682751000603596655790990815525126154394344641336397793791497068253936771017031980867706707490224041075826337383538651825493679503771934836094655802776331664261631740148281763487765852746577808019633679 diff --git a/libtommath/etc/drprimes.txt b/libtommath/etc/drprimes.txt deleted file mode 100644 index 7c97f67..0000000 --- a/libtommath/etc/drprimes.txt +++ /dev/null @@ -1,9 +0,0 @@ -300-bit prime: -p == 2037035976334486086268445688409378161051468393665936250636140449354381298610415201576637819 - -540-bit prime: -p == 3599131035634557106248430806148785487095757694641533306480604458089470064537190296255232548883112685719936728506816716098566612844395439751206810991770626477344739 - -780-bit prime: -p == 6359114106063703798370219984742410466332205126109989319225557147754704702203399726411277962562135973685197744935448875852478791860694279747355800678568677946181447581781401213133886609947027230004277244697462656003655947791725966271167 - diff --git a/libtommath/etc/makefile b/libtommath/etc/makefile deleted file mode 100644 index 99154d8..0000000 --- a/libtommath/etc/makefile +++ /dev/null @@ -1,50 +0,0 @@ -CFLAGS += -Wall -W -Wshadow -O3 -fomit-frame-pointer -funroll-loops -I../ - -# default lib name (requires install with root) -# LIBNAME=-ltommath - -# libname when you can't install the lib with install -LIBNAME=../libtommath.a - -#provable primes -pprime: pprime.o - $(CC) pprime.o $(LIBNAME) -o pprime - -# portable [well requires clock()] tuning app -tune: tune.o - $(CC) tune.o $(LIBNAME) -o tune - -# same app but using RDTSC for higher precision [requires 80586+], coff based gcc installs [e.g. ming, cygwin, djgpp] -tune86: tune.c - nasm -f coff timer.asm - $(CC) -DX86_TIMER $(CFLAGS) tune.c timer.o $(LIBNAME) -o tune86 - -# for cygwin -tune86c: tune.c - nasm -f gnuwin32 timer.asm - $(CC) -DX86_TIMER $(CFLAGS) tune.c timer.o $(LIBNAME) -o tune86 - -#make tune86 for linux or any ELF format -tune86l: tune.c - nasm -f elf -DUSE_ELF timer.asm - $(CC) -DX86_TIMER $(CFLAGS) tune.c timer.o $(LIBNAME) -o tune86l - -# spits out mersenne primes -mersenne: mersenne.o - $(CC) mersenne.o $(LIBNAME) -o mersenne - -# fines DR safe primes for the given config -drprime: drprime.o - $(CC) drprime.o $(LIBNAME) -o drprime - -# fines 2k safe primes for the given config -2kprime: 2kprime.o - $(CC) 2kprime.o $(LIBNAME) -o 2kprime - -mont: mont.o - $(CC) mont.o $(LIBNAME) -o mont - - -clean: - rm -f *.log *.o *.obj *.exe pprime tune mersenne drprime tune86 tune86l mont 2kprime pprime.dat \ - *.da *.dyn *.dpi *~ diff --git a/libtommath/etc/makefile.icc b/libtommath/etc/makefile.icc deleted file mode 100644 index 8a1ffff..0000000 --- a/libtommath/etc/makefile.icc +++ /dev/null @@ -1,67 +0,0 @@ -CC = icc - -CFLAGS += -I../ - -# optimize for SPEED -# -# -mcpu= can be pentium, pentiumpro (covers PII through PIII) or pentium4 -# -ax? specifies make code specifically for ? but compatible with IA-32 -# -x? specifies compile solely for ? [not specifically IA-32 compatible] -# -# where ? is -# K - PIII -# W - first P4 [Williamette] -# N - P4 Northwood -# P - P4 Prescott -# B - Blend of P4 and PM [mobile] -# -# Default to just generic max opts -CFLAGS += -O3 -xP -ip - -# default lib name (requires install with root) -# LIBNAME=-ltommath - -# libname when you can't install the lib with install -LIBNAME=../libtommath.a - -#provable primes -pprime: pprime.o - $(CC) pprime.o $(LIBNAME) -o pprime - -# portable [well requires clock()] tuning app -tune: tune.o - $(CC) tune.o $(LIBNAME) -o tune - -# same app but using RDTSC for higher precision [requires 80586+], coff based gcc installs [e.g. ming, cygwin, djgpp] -tune86: tune.c - nasm -f coff timer.asm - $(CC) -DX86_TIMER $(CFLAGS) tune.c timer.o $(LIBNAME) -o tune86 - -# for cygwin -tune86c: tune.c - nasm -f gnuwin32 timer.asm - $(CC) -DX86_TIMER $(CFLAGS) tune.c timer.o $(LIBNAME) -o tune86 - -#make tune86 for linux or any ELF format -tune86l: tune.c - nasm -f elf -DUSE_ELF timer.asm - $(CC) -DX86_TIMER $(CFLAGS) tune.c timer.o $(LIBNAME) -o tune86l - -# spits out mersenne primes -mersenne: mersenne.o - $(CC) mersenne.o $(LIBNAME) -o mersenne - -# fines DR safe primes for the given config -drprime: drprime.o - $(CC) drprime.o $(LIBNAME) -o drprime - -# fines 2k safe primes for the given config -2kprime: 2kprime.o - $(CC) 2kprime.o $(LIBNAME) -o 2kprime - -mont: mont.o - $(CC) mont.o $(LIBNAME) -o mont - - -clean: - rm -f *.log *.o *.obj *.exe pprime tune mersenne drprime tune86 tune86l mont 2kprime pprime.dat *.il diff --git a/libtommath/etc/makefile.msvc b/libtommath/etc/makefile.msvc deleted file mode 100644 index 2833372..0000000 --- a/libtommath/etc/makefile.msvc +++ /dev/null @@ -1,23 +0,0 @@ -#MSVC Makefile -# -#Tom St Denis - -CFLAGS = /I../ /Ox /DWIN32 /W3 - -pprime: pprime.obj - cl pprime.obj ../tommath.lib - -mersenne: mersenne.obj - cl mersenne.obj ../tommath.lib - -tune: tune.obj - cl tune.obj ../tommath.lib - -mont: mont.obj - cl mont.obj ../tommath.lib - -drprime: drprime.obj - cl drprime.obj ../tommath.lib - -2kprime: 2kprime.obj - cl 2kprime.obj ../tommath.lib diff --git a/libtommath/etc/mersenne.c b/libtommath/etc/mersenne.c deleted file mode 100644 index ae6725a..0000000 --- a/libtommath/etc/mersenne.c +++ /dev/null @@ -1,144 +0,0 @@ -/* Finds Mersenne primes using the Lucas-Lehmer test - * - * Tom St Denis, tomstdenis@gmail.com - */ -#include <time.h> -#include <tommath.h> - -int -is_mersenne (long s, int *pp) -{ - mp_int n, u; - int res, k; - - *pp = 0; - - if ((res = mp_init (&n)) != MP_OKAY) { - return res; - } - - if ((res = mp_init (&u)) != MP_OKAY) { - goto LBL_N; - } - - /* n = 2^s - 1 */ - if ((res = mp_2expt(&n, s)) != MP_OKAY) { - goto LBL_MU; - } - if ((res = mp_sub_d (&n, 1, &n)) != MP_OKAY) { - goto LBL_MU; - } - - /* set u=4 */ - mp_set (&u, 4); - - /* for k=1 to s-2 do */ - for (k = 1; k <= s - 2; k++) { - /* u = u^2 - 2 mod n */ - if ((res = mp_sqr (&u, &u)) != MP_OKAY) { - goto LBL_MU; - } - if ((res = mp_sub_d (&u, 2, &u)) != MP_OKAY) { - goto LBL_MU; - } - - /* make sure u is positive */ - while (u.sign == MP_NEG) { - if ((res = mp_add (&u, &n, &u)) != MP_OKAY) { - goto LBL_MU; - } - } - - /* reduce */ - if ((res = mp_reduce_2k (&u, &n, 1)) != MP_OKAY) { - goto LBL_MU; - } - } - - /* if u == 0 then its prime */ - if (mp_iszero (&u) == 1) { - mp_prime_is_prime(&n, 8, pp); - if (*pp != 1) printf("FAILURE\n"); - } - - res = MP_OKAY; -LBL_MU:mp_clear (&u); -LBL_N:mp_clear (&n); - return res; -} - -/* square root of a long < 65536 */ -long -i_sqrt (long x) -{ - long x1, x2; - - x2 = 16; - do { - x1 = x2; - x2 = x1 - ((x1 * x1) - x) / (2 * x1); - } while (x1 != x2); - - if (x1 * x1 > x) { - --x1; - } - - return x1; -} - -/* is the long prime by brute force */ -int -isprime (long k) -{ - long y, z; - - y = i_sqrt (k); - for (z = 2; z <= y; z++) { - if ((k % z) == 0) - return 0; - } - return 1; -} - - -int -main (void) -{ - int pp; - long k; - clock_t tt; - - k = 3; - - for (;;) { - /* start time */ - tt = clock (); - - /* test if 2^k - 1 is prime */ - if (is_mersenne (k, &pp) != MP_OKAY) { - printf ("Whoa error\n"); - return -1; - } - - if (pp == 1) { - /* count time */ - tt = clock () - tt; - - /* display if prime */ - printf ("2^%-5ld - 1 is prime, test took %ld ticks\n", k, tt); - } - - /* goto next odd exponent */ - k += 2; - - /* but make sure its prime */ - while (isprime (k) == 0) { - k += 2; - } - } - return 0; -} - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ diff --git a/libtommath/etc/mont.c b/libtommath/etc/mont.c deleted file mode 100644 index 45cf3fd..0000000 --- a/libtommath/etc/mont.c +++ /dev/null @@ -1,50 +0,0 @@ -/* tests the montgomery routines */ -#include <tommath.h> - -int main(void) -{ - mp_int modulus, R, p, pp; - mp_digit mp; - long x, y; - - srand(time(NULL)); - mp_init_multi(&modulus, &R, &p, &pp, NULL); - - /* loop through various sizes */ - for (x = 4; x < 256; x++) { - printf("DIGITS == %3ld...", x); fflush(stdout); - - /* make up the odd modulus */ - mp_rand(&modulus, x); - modulus.dp[0] |= 1; - - /* now find the R value */ - mp_montgomery_calc_normalization(&R, &modulus); - mp_montgomery_setup(&modulus, &mp); - - /* now run through a bunch tests */ - for (y = 0; y < 1000; y++) { - mp_rand(&p, x/2); /* p = random */ - mp_mul(&p, &R, &pp); /* pp = R * p */ - mp_montgomery_reduce(&pp, &modulus, mp); - - /* should be equal to p */ - if (mp_cmp(&pp, &p) != MP_EQ) { - printf("FAILURE!\n"); - exit(-1); - } - } - printf("PASSED\n"); - } - - return 0; -} - - - - - - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ diff --git a/libtommath/etc/pprime.c b/libtommath/etc/pprime.c deleted file mode 100644 index 9f94423..0000000 --- a/libtommath/etc/pprime.c +++ /dev/null @@ -1,400 +0,0 @@ -/* Generates provable primes - * - * See http://gmail.com:8080/papers/pp.pdf for more info. - * - * Tom St Denis, tomstdenis@gmail.com, http://tom.gmail.com - */ -#include <time.h> -#include "tommath.h" - -int n_prime; -FILE *primes; - -/* fast square root */ -static mp_digit -i_sqrt (mp_word x) -{ - mp_word x1, x2; - - x2 = x; - do { - x1 = x2; - x2 = x1 - ((x1 * x1) - x) / (2 * x1); - } while (x1 != x2); - - if (x1 * x1 > x) { - --x1; - } - - return x1; -} - - -/* generates a prime digit */ -static void gen_prime (void) -{ - mp_digit r, x, y, next; - FILE *out; - - out = fopen("pprime.dat", "wb"); - - /* write first set of primes */ - r = 3; fwrite(&r, 1, sizeof(mp_digit), out); - r = 5; fwrite(&r, 1, sizeof(mp_digit), out); - r = 7; fwrite(&r, 1, sizeof(mp_digit), out); - r = 11; fwrite(&r, 1, sizeof(mp_digit), out); - r = 13; fwrite(&r, 1, sizeof(mp_digit), out); - r = 17; fwrite(&r, 1, sizeof(mp_digit), out); - r = 19; fwrite(&r, 1, sizeof(mp_digit), out); - r = 23; fwrite(&r, 1, sizeof(mp_digit), out); - r = 29; fwrite(&r, 1, sizeof(mp_digit), out); - r = 31; fwrite(&r, 1, sizeof(mp_digit), out); - - /* get square root, since if 'r' is composite its factors must be < than this */ - y = i_sqrt (r); - next = (y + 1) * (y + 1); - - for (;;) { - do { - r += 2; /* next candidate */ - r &= MP_MASK; - if (r < 31) break; - - /* update sqrt ? */ - if (next <= r) { - ++y; - next = (y + 1) * (y + 1); - } - - /* loop if divisible by 3,5,7,11,13,17,19,23,29 */ - if ((r % 3) == 0) { - x = 0; - continue; - } - if ((r % 5) == 0) { - x = 0; - continue; - } - if ((r % 7) == 0) { - x = 0; - continue; - } - if ((r % 11) == 0) { - x = 0; - continue; - } - if ((r % 13) == 0) { - x = 0; - continue; - } - if ((r % 17) == 0) { - x = 0; - continue; - } - if ((r % 19) == 0) { - x = 0; - continue; - } - if ((r % 23) == 0) { - x = 0; - continue; - } - if ((r % 29) == 0) { - x = 0; - continue; - } - - /* now check if r is divisible by x + k={1,7,11,13,17,19,23,29} */ - for (x = 30; x <= y; x += 30) { - if ((r % (x + 1)) == 0) { - x = 0; - break; - } - if ((r % (x + 7)) == 0) { - x = 0; - break; - } - if ((r % (x + 11)) == 0) { - x = 0; - break; - } - if ((r % (x + 13)) == 0) { - x = 0; - break; - } - if ((r % (x + 17)) == 0) { - x = 0; - break; - } - if ((r % (x + 19)) == 0) { - x = 0; - break; - } - if ((r % (x + 23)) == 0) { - x = 0; - break; - } - if ((r % (x + 29)) == 0) { - x = 0; - break; - } - } - } while (x == 0); - if (r > 31) { fwrite(&r, 1, sizeof(mp_digit), out); printf("%9d\r", r); fflush(stdout); } - if (r < 31) break; - } - - fclose(out); -} - -void load_tab(void) -{ - primes = fopen("pprime.dat", "rb"); - if (primes == NULL) { - gen_prime(); - primes = fopen("pprime.dat", "rb"); - } - fseek(primes, 0, SEEK_END); - n_prime = ftell(primes) / sizeof(mp_digit); -} - -mp_digit prime_digit(void) -{ - int n; - mp_digit d; - - n = abs(rand()) % n_prime; - fseek(primes, n * sizeof(mp_digit), SEEK_SET); - fread(&d, 1, sizeof(mp_digit), primes); - return d; -} - - -/* makes a prime of at least k bits */ -int -pprime (int k, int li, mp_int * p, mp_int * q) -{ - mp_int a, b, c, n, x, y, z, v; - int res, ii; - static const mp_digit bases[] = { 2, 3, 5, 7, 11, 13, 17, 19 }; - - /* single digit ? */ - if (k <= (int) DIGIT_BIT) { - mp_set (p, prime_digit ()); - return MP_OKAY; - } - - if ((res = mp_init (&c)) != MP_OKAY) { - return res; - } - - if ((res = mp_init (&v)) != MP_OKAY) { - goto LBL_C; - } - - /* product of first 50 primes */ - if ((res = - mp_read_radix (&v, - "19078266889580195013601891820992757757219839668357012055907516904309700014933909014729740190", - 10)) != MP_OKAY) { - goto LBL_V; - } - - if ((res = mp_init (&a)) != MP_OKAY) { - goto LBL_V; - } - - /* set the prime */ - mp_set (&a, prime_digit ()); - - if ((res = mp_init (&b)) != MP_OKAY) { - goto LBL_A; - } - - if ((res = mp_init (&n)) != MP_OKAY) { - goto LBL_B; - } - - if ((res = mp_init (&x)) != MP_OKAY) { - goto LBL_N; - } - - if ((res = mp_init (&y)) != MP_OKAY) { - goto LBL_X; - } - - if ((res = mp_init (&z)) != MP_OKAY) { - goto LBL_Y; - } - - /* now loop making the single digit */ - while (mp_count_bits (&a) < k) { - fprintf (stderr, "prime has %4d bits left\r", k - mp_count_bits (&a)); - fflush (stderr); - top: - mp_set (&b, prime_digit ()); - - /* now compute z = a * b * 2 */ - if ((res = mp_mul (&a, &b, &z)) != MP_OKAY) { /* z = a * b */ - goto LBL_Z; - } - - if ((res = mp_copy (&z, &c)) != MP_OKAY) { /* c = a * b */ - goto LBL_Z; - } - - if ((res = mp_mul_2 (&z, &z)) != MP_OKAY) { /* z = 2 * a * b */ - goto LBL_Z; - } - - /* n = z + 1 */ - if ((res = mp_add_d (&z, 1, &n)) != MP_OKAY) { /* n = z + 1 */ - goto LBL_Z; - } - - /* check (n, v) == 1 */ - if ((res = mp_gcd (&n, &v, &y)) != MP_OKAY) { /* y = (n, v) */ - goto LBL_Z; - } - - if (mp_cmp_d (&y, 1) != MP_EQ) - goto top; - - /* now try base x=bases[ii] */ - for (ii = 0; ii < li; ii++) { - mp_set (&x, bases[ii]); - - /* compute x^a mod n */ - if ((res = mp_exptmod (&x, &a, &n, &y)) != MP_OKAY) { /* y = x^a mod n */ - goto LBL_Z; - } - - /* if y == 1 loop */ - if (mp_cmp_d (&y, 1) == MP_EQ) - continue; - - /* now x^2a mod n */ - if ((res = mp_sqrmod (&y, &n, &y)) != MP_OKAY) { /* y = x^2a mod n */ - goto LBL_Z; - } - - if (mp_cmp_d (&y, 1) == MP_EQ) - continue; - - /* compute x^b mod n */ - if ((res = mp_exptmod (&x, &b, &n, &y)) != MP_OKAY) { /* y = x^b mod n */ - goto LBL_Z; - } - - /* if y == 1 loop */ - if (mp_cmp_d (&y, 1) == MP_EQ) - continue; - - /* now x^2b mod n */ - if ((res = mp_sqrmod (&y, &n, &y)) != MP_OKAY) { /* y = x^2b mod n */ - goto LBL_Z; - } - - if (mp_cmp_d (&y, 1) == MP_EQ) - continue; - - /* compute x^c mod n == x^ab mod n */ - if ((res = mp_exptmod (&x, &c, &n, &y)) != MP_OKAY) { /* y = x^ab mod n */ - goto LBL_Z; - } - - /* if y == 1 loop */ - if (mp_cmp_d (&y, 1) == MP_EQ) - continue; - - /* now compute (x^c mod n)^2 */ - if ((res = mp_sqrmod (&y, &n, &y)) != MP_OKAY) { /* y = x^2ab mod n */ - goto LBL_Z; - } - - /* y should be 1 */ - if (mp_cmp_d (&y, 1) != MP_EQ) - continue; - break; - } - - /* no bases worked? */ - if (ii == li) - goto top; - -{ - char buf[4096]; - - mp_toradix(&n, buf, 10); - printf("Certificate of primality for:\n%s\n\n", buf); - mp_toradix(&a, buf, 10); - printf("A == \n%s\n\n", buf); - mp_toradix(&b, buf, 10); - printf("B == \n%s\n\nG == %d\n", buf, bases[ii]); - printf("----------------------------------------------------------------\n"); -} - - /* a = n */ - mp_copy (&n, &a); - } - - /* get q to be the order of the large prime subgroup */ - mp_sub_d (&n, 1, q); - mp_div_2 (q, q); - mp_div (q, &b, q, NULL); - - mp_exch (&n, p); - - res = MP_OKAY; -LBL_Z:mp_clear (&z); -LBL_Y:mp_clear (&y); -LBL_X:mp_clear (&x); -LBL_N:mp_clear (&n); -LBL_B:mp_clear (&b); -LBL_A:mp_clear (&a); -LBL_V:mp_clear (&v); -LBL_C:mp_clear (&c); - return res; -} - - -int -main (void) -{ - mp_int p, q; - char buf[4096]; - int k, li; - clock_t t1; - - srand (time (NULL)); - load_tab(); - - printf ("Enter # of bits: \n"); - fgets (buf, sizeof (buf), stdin); - sscanf (buf, "%d", &k); - - printf ("Enter number of bases to try (1 to 8):\n"); - fgets (buf, sizeof (buf), stdin); - sscanf (buf, "%d", &li); - - - mp_init (&p); - mp_init (&q); - - t1 = clock (); - pprime (k, li, &p, &q); - t1 = clock () - t1; - - printf ("\n\nTook %ld ticks, %d bits\n", t1, mp_count_bits (&p)); - - mp_toradix (&p, buf, 10); - printf ("P == %s\n", buf); - mp_toradix (&q, buf, 10); - printf ("Q == %s\n", buf); - - return 0; -} - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ diff --git a/libtommath/etc/prime.1024 b/libtommath/etc/prime.1024 deleted file mode 100644 index 5636e2d..0000000 --- a/libtommath/etc/prime.1024 +++ /dev/null @@ -1,414 +0,0 @@ -Enter # of bits: -Enter number of bases to try (1 to 8): -Certificate of primality for: -36360080703173363 - -A == -89963569 - -B == -202082249 - -G == 2 ----------------------------------------------------------------- -Certificate of primality for: -4851595597739856136987139 - -A == -36360080703173363 - -B == -66715963 - -G == 2 ----------------------------------------------------------------- -Certificate of primality for: -19550639734462621430325731591027 - -A == -4851595597739856136987139 - -B == -2014867 - -G == 2 ----------------------------------------------------------------- -Certificate of primality for: -10409036141344317165691858509923818734539 - -A == -19550639734462621430325731591027 - -B == -266207047 - -G == 2 ----------------------------------------------------------------- -Certificate of primality for: -1049829549988285012736475602118094726647504414203 - -A == -10409036141344317165691858509923818734539 - -B == -50428759 - -G == 2 ----------------------------------------------------------------- -Certificate of primality for: -77194737385528288387712399596835459931920358844586615003 - -A == -1049829549988285012736475602118094726647504414203 - -B == -36765367 - -G == 2 ----------------------------------------------------------------- -Certificate of primality for: -35663756695365208574443215955488689578374232732893628896541201763 - -A == -77194737385528288387712399596835459931920358844586615003 - -B == -230998627 - -G == 2 ----------------------------------------------------------------- -Certificate of primality for: -16711831463502165169495622246023119698415848120292671294127567620396469803 - -A == -35663756695365208574443215955488689578374232732893628896541201763 - -B == -234297127 - -G == 2 ----------------------------------------------------------------- -Certificate of primality for: -6163534781560285962890718925972249753147470953579266394395432475622345597103528739 - -A == -16711831463502165169495622246023119698415848120292671294127567620396469803 - -B == -184406323 - -G == 2 ----------------------------------------------------------------- -Certificate of primality for: -814258256205243497704094951432575867360065658372158511036259934640748088306764553488803787 - -A == -6163534781560285962890718925972249753147470953579266394395432475622345597103528739 - -B == -66054487 - -G == 2 ----------------------------------------------------------------- -Certificate of primality for: -176469695533271657902814176811660357049007467856432383037590673407330246967781451723764079581998187 - -A == -814258256205243497704094951432575867360065658372158511036259934640748088306764553488803787 - -B == -108362239 - -G == 2 ----------------------------------------------------------------- -Certificate of primality for: -44924492859445516541759485198544012102424796403707253610035148063863073596051272171194806669756971406400419 - 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-B == -5920567 - -G == 2 ----------------------------------------------------------------- - - -Took 3454 ticks, 521 bits -P == 5290203010849586596974953717018896543907195901082056939587768479377028575911127944611236020459652034082251335583308070846379514569838984811187823420951275243 -Q == 446764896913554613686067036908702877942872355053329937790398156069936255759889884246832779737114032666318220500106499161852193765380831330106375235763 diff --git a/libtommath/etc/timer.asm b/libtommath/etc/timer.asm deleted file mode 100644 index 326a947..0000000 --- a/libtommath/etc/timer.asm +++ /dev/null @@ -1,37 +0,0 @@ -; x86 timer in NASM -; -; Tom St Denis, tomstdenis@iahu.ca -[bits 32] -[section .data] -time dd 0, 0 - -[section .text] - -%ifdef USE_ELF -[global t_start] -t_start: -%else -[global _t_start] -_t_start: -%endif - push edx - push eax - rdtsc - mov [time+0],edx - mov [time+4],eax - pop eax - pop edx - ret - -%ifdef USE_ELF -[global t_read] -t_read: -%else -[global _t_read] -_t_read: -%endif - rdtsc - sub eax,[time+4] - sbb edx,[time+0] - ret -
\ No newline at end of file diff --git a/libtommath/etc/tune.c b/libtommath/etc/tune.c deleted file mode 100644 index c2ac998..0000000 --- a/libtommath/etc/tune.c +++ /dev/null @@ -1,145 +0,0 @@ -/* Tune the Karatsuba parameters - * - * Tom St Denis, tomstdenis@gmail.com - */ -#include <tommath.h> -#include <time.h> - -/* how many times todo each size mult. Depends on your computer. For slow computers - * this can be low like 5 or 10. For fast [re: Athlon] should be 25 - 50 or so - */ -#define TIMES (1UL<<14UL) - -#ifndef X86_TIMER - -/* RDTSC from Scott Duplichan */ -static ulong64 TIMFUNC (void) - { - #if defined __GNUC__ - #if defined(__i386__) || defined(__x86_64__) - /* version from http://www.mcs.anl.gov/~kazutomo/rdtsc.html - * the old code always got a warning issued by gcc, clang did not complain... - */ - unsigned hi, lo; - __asm__ __volatile__ ("rdtsc" : "=a"(lo), "=d"(hi)); - return ((ulong64)lo)|( ((ulong64)hi)<<32); - #else /* gcc-IA64 version */ - unsigned long result; - __asm__ __volatile__("mov %0=ar.itc" : "=r"(result) :: "memory"); - while (__builtin_expect ((int) result == -1, 0)) - __asm__ __volatile__("mov %0=ar.itc" : "=r"(result) :: "memory"); - return result; - #endif - - // Microsoft and Intel Windows compilers - #elif defined _M_IX86 - __asm rdtsc - #elif defined _M_AMD64 - return __rdtsc (); - #elif defined _M_IA64 - #if defined __INTEL_COMPILER - #include <ia64intrin.h> - #endif - return __getReg (3116); - #else - #error need rdtsc function for this build - #endif - } - - -/* generic ISO C timer */ -ulong64 LBL_T; -void t_start(void) { LBL_T = TIMFUNC(); } -ulong64 t_read(void) { return TIMFUNC() - LBL_T; } - -#else -extern void t_start(void); -extern ulong64 t_read(void); -#endif - -ulong64 time_mult(int size, int s) -{ - unsigned long x; - mp_int a, b, c; - ulong64 t1; - - mp_init (&a); - mp_init (&b); - mp_init (&c); - - mp_rand (&a, size); - mp_rand (&b, size); - - if (s == 1) { - KARATSUBA_MUL_CUTOFF = size; - } else { - KARATSUBA_MUL_CUTOFF = 100000; - } - - t_start(); - for (x = 0; x < TIMES; x++) { - mp_mul(&a,&b,&c); - } - t1 = t_read(); - mp_clear (&a); - mp_clear (&b); - mp_clear (&c); - return t1; -} - -ulong64 time_sqr(int size, int s) -{ - unsigned long x; - mp_int a, b; - ulong64 t1; - - mp_init (&a); - mp_init (&b); - - mp_rand (&a, size); - - if (s == 1) { - KARATSUBA_SQR_CUTOFF = size; - } else { - KARATSUBA_SQR_CUTOFF = 100000; - } - - t_start(); - for (x = 0; x < TIMES; x++) { - mp_sqr(&a,&b); - } - t1 = t_read(); - mp_clear (&a); - mp_clear (&b); - return t1; -} - -int -main (void) -{ - ulong64 t1, t2; - int x, y; - - for (x = 8; ; x += 2) { - t1 = time_mult(x, 0); - t2 = time_mult(x, 1); - printf("%d: %9llu %9llu, %9llu\n", x, t1, t2, t2 - t1); - if (t2 < t1) break; - } - y = x; - - for (x = 8; ; x += 2) { - t1 = time_sqr(x, 0); - t2 = time_sqr(x, 1); - printf("%d: %9llu %9llu, %9llu\n", x, t1, t2, t2 - t1); - if (t2 < t1) break; - } - printf("KARATSUBA_MUL_CUTOFF = %d\n", y); - printf("KARATSUBA_SQR_CUTOFF = %d\n", x); - - return 0; -} - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ diff --git a/libtommath/filter.pl b/libtommath/filter.pl deleted file mode 100755 index a8a50c7..0000000 --- a/libtommath/filter.pl +++ /dev/null @@ -1,34 +0,0 @@ -#!/usr/bin/perl - -# we want to filter every between START_INS and END_INS out and then insert crap from another file (this is fun) - -$dst = shift; -$ins = shift; - -open(SRC,"<$dst"); -open(INS,"<$ins"); -open(TMP,">tmp.delme"); - -$l = 0; -while (<SRC>) { - if ($_ =~ /START_INS/) { - print TMP $_; - $l = 1; - while (<INS>) { - print TMP $_; - } - close INS; - } elsif ($_ =~ /END_INS/) { - print TMP $_; - $l = 0; - } elsif ($l == 0) { - print TMP $_; - } -} - -close TMP; -close SRC; - -# $Source$ -# $Revision$ -# $Date$ diff --git a/libtommath/gen.pl b/libtommath/gen.pl deleted file mode 100644 index 57f65ac..0000000 --- a/libtommath/gen.pl +++ /dev/null @@ -1,19 +0,0 @@ -#!/usr/bin/perl -w -# -# Generates a "single file" you can use to quickly -# add the whole source without any makefile troubles -# -use strict; - -open( OUT, ">mpi.c" ) or die "Couldn't open mpi.c for writing: $!"; -foreach my $filename (glob "bn*.c") { - open( SRC, "<$filename" ) or die "Couldn't open $filename for reading: $!"; - print OUT "/* Start: $filename */\n"; - print OUT while <SRC>; - print OUT "\n/* End: $filename */\n\n"; - close SRC or die "Error closing $filename after reading: $!"; -} -print OUT "\n/* EOF */\n"; -close OUT or die "Error closing mpi.c after writing: $!"; - -system('perl -pli -e "s/\s*$//" mpi.c'); diff --git a/libtommath/genlist.sh b/libtommath/genlist.sh deleted file mode 100755 index 1f53b66..0000000 --- a/libtommath/genlist.sh +++ /dev/null @@ -1,8 +0,0 @@ -#!/bin/bash - -export a=`find . -maxdepth 1 -type f -name '*.c' | sort | sed -e 'sE\./EE' | sed -e 's/\.c/\.o/' | xargs` -perl ./parsenames.pl OBJECTS "$a" - -# $Source$ -# $Revision$ -# $Date$ diff --git a/libtommath/libtommath.dsp b/libtommath/libtommath.dsp deleted file mode 100644 index 71ac243..0000000 --- a/libtommath/libtommath.dsp +++ /dev/null @@ -1,572 +0,0 @@ -# Microsoft Developer Studio Project File - Name="libtommath" - Package Owner=<4>
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PreprocessorDefinitions="" - /> - </FileConfiguration> - <FileConfiguration - Name="Release|Win32" - > - <Tool - Name="VCCLCompilerTool" - AdditionalIncludeDirectories="" - PreprocessorDefinitions="" - /> - </FileConfiguration> - </File> - <File - RelativePath="bn_s_mp_mul_high_digs.c" - > - <FileConfiguration - Name="Debug|Win32" - > - <Tool - Name="VCCLCompilerTool" - AdditionalIncludeDirectories="" - PreprocessorDefinitions="" - /> - </FileConfiguration> - <FileConfiguration - Name="Release|Win32" - > - <Tool - Name="VCCLCompilerTool" - AdditionalIncludeDirectories="" - PreprocessorDefinitions="" - /> - </FileConfiguration> - </File> - <File - RelativePath="bn_s_mp_sqr.c" - > - <FileConfiguration - Name="Debug|Win32" - > - <Tool - Name="VCCLCompilerTool" - AdditionalIncludeDirectories="" - PreprocessorDefinitions="" - /> - </FileConfiguration> - <FileConfiguration - Name="Release|Win32" - > - <Tool - Name="VCCLCompilerTool" - AdditionalIncludeDirectories="" - PreprocessorDefinitions="" - /> - </FileConfiguration> - </File> - <File - RelativePath="bn_s_mp_sub.c" - > - <FileConfiguration - Name="Debug|Win32" - > - <Tool - Name="VCCLCompilerTool" - AdditionalIncludeDirectories="" - PreprocessorDefinitions="" - /> - </FileConfiguration> - <FileConfiguration - Name="Release|Win32" - > - <Tool - Name="VCCLCompilerTool" - AdditionalIncludeDirectories="" - PreprocessorDefinitions="" - /> - </FileConfiguration> - </File> - <File - RelativePath="bncore.c" - > - <FileConfiguration - Name="Debug|Win32" - > - <Tool - Name="VCCLCompilerTool" - AdditionalIncludeDirectories="" - PreprocessorDefinitions="" - /> - </FileConfiguration> - <FileConfiguration - Name="Release|Win32" - > - <Tool - Name="VCCLCompilerTool" - AdditionalIncludeDirectories="" - PreprocessorDefinitions="" - /> - </FileConfiguration> - </File> - <File - RelativePath="tommath.h" - > - </File> - <File - RelativePath="tommath_class.h" - > - </File> - <File - RelativePath="tommath_superclass.h" - > - </File> - </Files> - <Globals> - </Globals> -</VisualStudioProject> diff --git a/libtommath/logs/README b/libtommath/logs/README deleted file mode 100644 index 965e7c8..0000000 --- a/libtommath/logs/README +++ /dev/null @@ -1,13 +0,0 @@ -To use the pretty graphs you have to first build/run the ltmtest from the root directory of the package. -Todo this type - -make timing ; ltmtest - -in the root. It will run for a while [about ten minutes on most PCs] and produce a series of .log files in logs/. - -After doing that run "gnuplot graphs.dem" to make the PNGs. If you managed todo that all so far just open index.html to view -them all :-) - -Have fun - -Tom
\ No newline at end of file diff --git a/libtommath/logs/add.log b/libtommath/logs/add.log deleted file mode 100644 index 43503ac..0000000 --- a/libtommath/logs/add.log +++ /dev/null @@ -1,16 +0,0 @@ -480 87 -960 111 -1440 135 -1920 159 -2400 200 -2880 224 -3360 248 -3840 272 -4320 296 -4800 320 -5280 344 -5760 368 -6240 392 -6720 416 -7200 440 -7680 464 diff --git a/libtommath/logs/addsub.png b/libtommath/logs/addsub.png Binary files differdeleted file mode 100644 index a5679ac..0000000 --- a/libtommath/logs/addsub.png +++ /dev/null diff --git a/libtommath/logs/expt.log b/libtommath/logs/expt.log deleted file mode 100644 index 70932ab..0000000 --- a/libtommath/logs/expt.log +++ /dev/null @@ -1,7 +0,0 @@ -513 1435869 -769 3544970 -1025 7791638 -2049 46902238 -2561 85334899 -3073 141451412 -4097 308770310 diff --git a/libtommath/logs/expt.png b/libtommath/logs/expt.png Binary files differdeleted file mode 100644 index 9ee8bb7..0000000 --- a/libtommath/logs/expt.png +++ /dev/null diff --git a/libtommath/logs/expt_2k.log b/libtommath/logs/expt_2k.log deleted file mode 100644 index 97d325f..0000000 --- a/libtommath/logs/expt_2k.log +++ /dev/null @@ -1,5 +0,0 @@ -607 2109225 -1279 10148314 -2203 34126877 -3217 82716424 -4253 161569606 diff --git a/libtommath/logs/expt_2kl.log b/libtommath/logs/expt_2kl.log deleted file mode 100644 index d9ad4be..0000000 --- a/libtommath/logs/expt_2kl.log +++ /dev/null @@ -1,4 +0,0 @@ -1024 7705271 -2048 34286851 -4096 165207491 -521 1618631 diff --git a/libtommath/logs/expt_dr.log b/libtommath/logs/expt_dr.log deleted file mode 100644 index c6bbe07..0000000 --- a/libtommath/logs/expt_dr.log +++ /dev/null @@ -1,7 +0,0 @@ -532 1928550 -784 3763908 -1036 7564221 -1540 16566059 -2072 32283784 -3080 79851565 -4116 157843530 diff --git a/libtommath/logs/graphs.dem b/libtommath/logs/graphs.dem deleted file mode 100644 index dfaf613..0000000 --- a/libtommath/logs/graphs.dem +++ /dev/null @@ -1,17 +0,0 @@ -set terminal png -set size 1.75 -set ylabel "Cycles per Operation" -set xlabel "Operand size (bits)" - -set output "addsub.png" -plot 'add.log' smooth bezier title "Addition", 'sub.log' smooth bezier title "Subtraction" - -set output "mult.png" -plot 'sqr.log' smooth bezier title "Squaring (without Karatsuba)", 'sqr_kara.log' smooth bezier title "Squaring (Karatsuba)", 'mult.log' smooth bezier title "Multiplication (without Karatsuba)", 'mult_kara.log' smooth bezier title "Multiplication (Karatsuba)" - -set output "expt.png" -plot 'expt.log' smooth bezier title "Exptmod (Montgomery)", 'expt_dr.log' smooth bezier title "Exptmod (Dimminished Radix)", 'expt_2k.log' smooth bezier title "Exptmod (2k Reduction)" - -set output "invmod.png" -plot 'invmod.log' smooth bezier title "Modular Inverse" - diff --git a/libtommath/logs/index.html b/libtommath/logs/index.html deleted file mode 100644 index 4b68c25..0000000 --- a/libtommath/logs/index.html +++ /dev/null @@ -1,27 +0,0 @@ -<html> -<head> -<title>LibTomMath Log Plots</title> -</head> -<body> - -<h1>Addition and Subtraction</h1> -<center><img src=addsub.png></center> -<hr> - -<h1>Multipliers</h1> -<center><img src=mult.png></center> -<hr> - -<h1>Exptmod</h1> -<center><img src=expt.png></center> -<hr> - -<h1>Modular Inverse</h1> -<center><img src=invmod.png></center> -<hr> - -</body> -</html> -/* $Source: /cvs/libtom/libtommath/logs/index.html,v $ */ -/* $Revision: 1.2 $ */ -/* $Date: 2005/05/05 14:38:47 $ */ diff --git a/libtommath/logs/invmod.log b/libtommath/logs/invmod.log deleted file mode 100644 index e69de29..0000000 --- a/libtommath/logs/invmod.log +++ /dev/null diff --git a/libtommath/logs/invmod.png b/libtommath/logs/invmod.png Binary files differdeleted file mode 100644 index 0a8a4ad..0000000 --- a/libtommath/logs/invmod.png +++ /dev/null diff --git a/libtommath/logs/mult.log b/libtommath/logs/mult.log deleted file mode 100644 index 33563fc..0000000 --- a/libtommath/logs/mult.log +++ /dev/null @@ -1,84 +0,0 @@ -271 555 -390 855 -508 1161 -631 1605 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a/libtommath/logs/mult.png b/libtommath/logs/mult.png Binary files differdeleted file mode 100644 index 4f7a4ee..0000000 --- a/libtommath/logs/mult.png +++ /dev/null diff --git a/libtommath/logs/mult_kara.log b/libtommath/logs/mult_kara.log deleted file mode 100644 index 7136c79..0000000 --- a/libtommath/logs/mult_kara.log +++ /dev/null @@ -1,84 +0,0 @@ -271 560 -391 870 -511 1159 -631 1605 -750 2111 -871 2737 -991 3361 -1111 4054 -1231 4778 -1351 5600 -1471 6404 -1591 7323 -1710 8255 -1831 9239 -1948 10257 -2070 11397 -2190 12531 -2308 13665 -2429 14870 -2550 16175 -2671 17539 -2787 18879 -2911 20350 -3031 21807 -3150 23415 -3270 24897 -3388 26567 -3511 28205 -3627 30076 -3751 31744 -3869 33657 -3991 35425 -4111 37522 -4229 39363 -4351 41503 -4470 43491 -4590 45827 -4711 47795 -4828 50166 -4951 52318 -5070 54911 -5191 57036 -5308 58237 -5431 60248 -5551 62678 -5671 64786 -5791 67294 -5908 69343 -6031 71607 -6151 74166 -6271 76590 -6391 78734 -6511 81175 -6631 83742 -6750 86403 -6868 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299 -4800 321 -5280 345 -5760 371 -6240 395 -6720 419 -7200 441 -7680 465 diff --git a/libtommath/makefile_include.mk b/libtommath/makefile_include.mk new file mode 100644 index 0000000..3a599e8 --- /dev/null +++ b/libtommath/makefile_include.mk @@ -0,0 +1,117 @@ +# +# Include makefile for libtommath +# + +#version of library +VERSION=1.0.1 +VERSION_PC=1.0.1 +VERSION_SO=1:1 + +PLATFORM := $(shell uname | sed -e 's/_.*//') + +# default make target +default: ${LIBNAME} + +# Compiler and Linker Names +ifndef CROSS_COMPILE + CROSS_COMPILE= +endif + +ifeq ($(CC),cc) + CC = $(CROSS_COMPILE)gcc +endif +LD=$(CROSS_COMPILE)ld +AR=$(CROSS_COMPILE)ar +RANLIB=$(CROSS_COMPILE)ranlib + +ifndef MAKE + MAKE=make +endif + +CFLAGS += -I./ -Wall -Wsign-compare -Wextra -Wshadow + +ifndef NO_ADDTL_WARNINGS +# additional warnings +CFLAGS += -Wsystem-headers -Wdeclaration-after-statement -Wbad-function-cast -Wcast-align +CFLAGS += -Wstrict-prototypes -Wpointer-arith +endif + +ifdef COMPILE_DEBUG +#debug +CFLAGS += -g3 +else + +ifdef COMPILE_SIZE +#for size +CFLAGS += -Os +else + +ifndef IGNORE_SPEED +#for speed +CFLAGS += -O3 -funroll-loops + +#x86 optimizations [should be valid for any GCC install though] +CFLAGS += -fomit-frame-pointer +endif + +endif # COMPILE_SIZE +endif # COMPILE_DEBUG + +ifneq ($(findstring clang,$(CC)),) +CFLAGS += -Wno-typedef-redefinition -Wno-tautological-compare -Wno-builtin-requires-header +endif +ifeq ($(PLATFORM), Darwin) +CFLAGS += -Wno-nullability-completeness +endif + +# adjust coverage set +ifneq ($(filter $(shell arch), i386 i686 x86_64 amd64 ia64),) + COVERAGE = test_standalone timing + COVERAGE_APP = ./test && ./ltmtest +else + COVERAGE = test_standalone + COVERAGE_APP = ./test +endif + +HEADERS_PUB=tommath.h tommath_class.h tommath_superclass.h +HEADERS=tommath_private.h $(HEADERS_PUB) + +test_standalone: CFLAGS+=-DLTM_DEMO_TEST_VS_MTEST=0 + +#LIBPATH The directory for libtommath to be installed to. +#INCPATH The directory to install the header files for libtommath. +#DATAPATH The directory to install the pdf docs. +DESTDIR ?= +PREFIX ?= /usr/local +LIBPATH ?= $(PREFIX)/lib +INCPATH ?= $(PREFIX)/include +DATAPATH ?= $(PREFIX)/share/doc/libtommath/pdf + +#make the code coverage of the library +# +coverage: CFLAGS += -fprofile-arcs -ftest-coverage -DTIMING_NO_LOGS +coverage: LFLAGS += -lgcov +coverage: LDFLAGS += -lgcov + +coverage: $(COVERAGE) + $(COVERAGE_APP) + +lcov: coverage + rm -f coverage.info + lcov --capture --no-external --no-recursion $(LCOV_ARGS) --output-file coverage.info -q + genhtml coverage.info --output-directory coverage -q + +# target that removes all coverage output +cleancov-clean: + rm -f `find . -type f -name "*.info" | xargs` + rm -rf coverage/ + +# cleans everything - coverage output and standard 'clean' +cleancov: cleancov-clean clean + +clean: + rm -f *.gcda *.gcno *.gcov *.bat *.o *.a *.obj *.lib *.exe *.dll etclib/*.o demo/demo.o test ltmtest mpitest mtest/mtest mtest/mtest.exe \ + *.idx *.toc *.log *.aux *.dvi *.lof *.ind *.ilg *.ps *.log *.s mpi.c *.da *.dyn *.dpi tommath.tex `find . -type f | grep [~] | xargs` *.lo *.la + rm -rf .libs/ + ${MAKE} -C etc/ clean MAKE=${MAKE} + ${MAKE} -C doc/ clean MAKE=${MAKE} diff --git a/libtommath/mess.sh b/libtommath/mess.sh deleted file mode 100644 index bf639ce..0000000 --- a/libtommath/mess.sh +++ /dev/null @@ -1,4 +0,0 @@ -#!/bin/bash -if cvs log $1 >/dev/null 2>/dev/null; then exit 0; else echo "$1 shouldn't be here" ; exit 1; fi - - diff --git a/libtommath/mtest/logtab.h b/libtommath/mtest/logtab.h deleted file mode 100644 index 751111e..0000000 --- a/libtommath/mtest/logtab.h +++ /dev/null @@ -1,24 +0,0 @@ -const float s_logv_2[] = { - 0.000000000, 0.000000000, 1.000000000, 0.630929754, /* 0 1 2 3 */ - 0.500000000, 0.430676558, 0.386852807, 0.356207187, /* 4 5 6 7 */ - 0.333333333, 0.315464877, 0.301029996, 0.289064826, /* 8 9 10 11 */ - 0.278942946, 0.270238154, 0.262649535, 0.255958025, /* 12 13 14 15 */ - 0.250000000, 0.244650542, 0.239812467, 0.235408913, /* 16 17 18 19 */ - 0.231378213, 0.227670249, 0.224243824, 0.221064729, /* 20 21 22 23 */ - 0.218104292, 0.215338279, 0.212746054, 0.210309918, /* 24 25 26 27 */ - 0.208014598, 0.205846832, 0.203795047, 0.201849087, /* 28 29 30 31 */ - 0.200000000, 0.198239863, 0.196561632, 0.194959022, /* 32 33 34 35 */ - 0.193426404, 0.191958720, 0.190551412, 0.189200360, /* 36 37 38 39 */ - 0.187901825, 0.186652411, 0.185449023, 0.184288833, /* 40 41 42 43 */ - 0.183169251, 0.182087900, 0.181042597, 0.180031327, /* 44 45 46 47 */ - 0.179052232, 0.178103594, 0.177183820, 0.176291434, /* 48 49 50 51 */ - 0.175425064, 0.174583430, 0.173765343, 0.172969690, /* 52 53 54 55 */ - 0.172195434, 0.171441601, 0.170707280, 0.169991616, /* 56 57 58 59 */ - 0.169293808, 0.168613099, 0.167948779, 0.167300179, /* 60 61 62 63 */ - 0.166666667 -}; - - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ diff --git a/libtommath/mtest/mpi-config.h b/libtommath/mtest/mpi-config.h deleted file mode 100644 index fc2a885..0000000 --- a/libtommath/mtest/mpi-config.h +++ /dev/null @@ -1,90 +0,0 @@ -/* Default configuration for MPI library */ -/* $Id$ */ - -#ifndef MPI_CONFIG_H_ -#define MPI_CONFIG_H_ - -/* - For boolean options, - 0 = no - 1 = yes - - Other options are documented individually. - - */ - -#ifndef MP_IOFUNC -#define MP_IOFUNC 0 /* include mp_print() ? */ -#endif - -#ifndef MP_MODARITH -#define MP_MODARITH 1 /* include modular arithmetic ? */ -#endif - -#ifndef MP_NUMTH -#define MP_NUMTH 1 /* include number theoretic functions? */ -#endif - -#ifndef MP_LOGTAB -#define MP_LOGTAB 1 /* use table of logs instead of log()? */ -#endif - -#ifndef MP_MEMSET -#define MP_MEMSET 1 /* use memset() to zero buffers? */ -#endif - -#ifndef MP_MEMCPY -#define MP_MEMCPY 1 /* use memcpy() to copy buffers? */ -#endif - -#ifndef MP_CRYPTO -#define MP_CRYPTO 1 /* erase memory on free? */ -#endif - -#ifndef MP_ARGCHK -/* - 0 = no parameter checks - 1 = runtime checks, continue execution and return an error to caller - 2 = assertions; dump core on parameter errors - */ -#define MP_ARGCHK 2 /* how to check input arguments */ -#endif - -#ifndef MP_DEBUG -#define MP_DEBUG 0 /* print diagnostic output? */ -#endif - -#ifndef MP_DEFPREC -#define MP_DEFPREC 64 /* default precision, in digits */ -#endif - -#ifndef MP_MACRO -#define MP_MACRO 1 /* use macros for frequent calls? */ -#endif - -#ifndef MP_SQUARE -#define MP_SQUARE 1 /* use separate squaring code? */ -#endif - -#ifndef MP_PTAB_SIZE -/* - When building mpprime.c, we build in a table of small prime - values to use for primality testing. The more you include, - the more space they take up. See primes.c for the possible - values (currently 16, 32, 64, 128, 256, and 6542) - */ -#define MP_PTAB_SIZE 128 /* how many built-in primes? */ -#endif - -#ifndef MP_COMPAT_MACROS -#define MP_COMPAT_MACROS 1 /* define compatibility macros? */ -#endif - -#endif /* ifndef MPI_CONFIG_H_ */ - - -/* crc==3287762869, version==2, Sat Feb 02 06:43:53 2002 */ - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ diff --git a/libtommath/mtest/mpi-types.h b/libtommath/mtest/mpi-types.h deleted file mode 100644 index f99d7ee..0000000 --- a/libtommath/mtest/mpi-types.h +++ /dev/null @@ -1,20 +0,0 @@ -/* Type definitions generated by 'types.pl' */ -typedef char mp_sign; -typedef unsigned short mp_digit; /* 2 byte type */ -typedef unsigned int mp_word; /* 4 byte type */ -typedef unsigned int mp_size; -typedef int mp_err; - -#define MP_DIGIT_BIT (CHAR_BIT*sizeof(mp_digit)) -#define MP_DIGIT_MAX USHRT_MAX -#define MP_WORD_BIT (CHAR_BIT*sizeof(mp_word)) -#define MP_WORD_MAX UINT_MAX - -#define MP_DIGIT_SIZE 2 -#define DIGIT_FMT "%04X" -#define RADIX (MP_DIGIT_MAX+1) - - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ diff --git a/libtommath/mtest/mpi.c b/libtommath/mtest/mpi.c deleted file mode 100644 index 48dbe27..0000000 --- a/libtommath/mtest/mpi.c +++ /dev/null @@ -1,3985 +0,0 @@ -/* - mpi.c - - by Michael J. Fromberger <sting@linguist.dartmouth.edu> - Copyright (C) 1998 Michael J. Fromberger, All Rights Reserved - - Arbitrary precision integer arithmetic library - - $Id$ - */ - -#include "mpi.h" -#include <stdlib.h> -#include <string.h> -#include <ctype.h> - -#if MP_DEBUG -#include <stdio.h> - -#define DIAG(T,V) {fprintf(stderr,T);mp_print(V,stderr);fputc('\n',stderr);} -#else -#define DIAG(T,V) -#endif - -/* - If MP_LOGTAB is not defined, use the math library to compute the - logarithms on the fly. Otherwise, use the static table below. - Pick which works best for your system. - */ -#if MP_LOGTAB - -/* {{{ s_logv_2[] - log table for 2 in various bases */ - -/* - A table of the logs of 2 for various bases (the 0 and 1 entries of - this table are meaningless and should not be referenced). - - This table is used to compute output lengths for the mp_toradix() - function. Since a number n in radix r takes up about log_r(n) - digits, we estimate the output size by taking the least integer - greater than log_r(n), where: - - log_r(n) = log_2(n) * log_r(2) - - This table, therefore, is a table of log_r(2) for 2 <= r <= 36, - which are the output bases supported. - */ - -#include "logtab.h" - -/* }}} */ -#define LOG_V_2(R) s_logv_2[(R)] - -#else - -#include <math.h> -#define LOG_V_2(R) (log(2.0)/log(R)) - -#endif - -/* Default precision for newly created mp_int's */ -static unsigned int s_mp_defprec = MP_DEFPREC; - -/* {{{ Digit arithmetic macros */ - -/* - When adding and multiplying digits, the results can be larger than - can be contained in an mp_digit. Thus, an mp_word is used. These - macros mask off the upper and lower digits of the mp_word (the - mp_word may be more than 2 mp_digits wide, but we only concern - ourselves with the low-order 2 mp_digits) - - If your mp_word DOES have more than 2 mp_digits, you need to - uncomment the first line, and comment out the second. - */ - -/* #define CARRYOUT(W) (((W)>>DIGIT_BIT)&MP_DIGIT_MAX) */ -#define CARRYOUT(W) ((W)>>DIGIT_BIT) -#define ACCUM(W) ((W)&MP_DIGIT_MAX) - -/* }}} */ - -/* {{{ Comparison constants */ - -#define MP_LT -1 -#define MP_EQ 0 -#define MP_GT 1 - -/* }}} */ - -/* {{{ Constant strings */ - -/* Constant strings returned by mp_strerror() */ -static const char *mp_err_string[] = { - "unknown result code", /* say what? */ - "boolean true", /* MP_OKAY, MP_YES */ - "boolean false", /* MP_NO */ - "out of memory", /* MP_MEM */ - "argument out of range", /* MP_RANGE */ - "invalid input parameter", /* MP_BADARG */ - "result is undefined" /* MP_UNDEF */ -}; - -/* Value to digit maps for radix conversion */ - -/* s_dmap_1 - standard digits and letters */ -static const char *s_dmap_1 = - "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz+/"; - -#if 0 -/* s_dmap_2 - base64 ordering for digits */ -static const char *s_dmap_2 = - "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"; -#endif - -/* }}} */ - -/* {{{ Static function declarations */ - -/* - If MP_MACRO is false, these will be defined as actual functions; - otherwise, suitable macro definitions will be used. This works - around the fact that ANSI C89 doesn't support an 'inline' keyword - (although I hear C9x will ... about bloody time). At present, the - macro definitions are identical to the function bodies, but they'll - expand in place, instead of generating a function call. - - I chose these particular functions to be made into macros because - some profiling showed they are called a lot on a typical workload, - and yet they are primarily housekeeping. - */ -#if MP_MACRO == 0 - void s_mp_setz(mp_digit *dp, mp_size count); /* zero digits */ - void s_mp_copy(mp_digit *sp, mp_digit *dp, mp_size count); /* copy */ - void *s_mp_alloc(size_t nb, size_t ni); /* general allocator */ - void s_mp_free(void *ptr); /* general free function */ -#else - - /* Even if these are defined as macros, we need to respect the settings - of the MP_MEMSET and MP_MEMCPY configuration options... - */ - #if MP_MEMSET == 0 - #define s_mp_setz(dp, count) \ - {int ix;for(ix=0;ix<(count);ix++)(dp)[ix]=0;} - #else - #define s_mp_setz(dp, count) memset(dp, 0, (count) * sizeof(mp_digit)) - #endif /* MP_MEMSET */ - - #if MP_MEMCPY == 0 - #define s_mp_copy(sp, dp, count) \ - {int ix;for(ix=0;ix<(count);ix++)(dp)[ix]=(sp)[ix];} - #else - #define s_mp_copy(sp, dp, count) memcpy(dp, sp, (count) * sizeof(mp_digit)) - #endif /* MP_MEMCPY */ - - #define s_mp_alloc(nb, ni) calloc(nb, ni) - #define s_mp_free(ptr) {if(ptr) free(ptr);} -#endif /* MP_MACRO */ - -mp_err s_mp_grow(mp_int *mp, mp_size min); /* increase allocated size */ -mp_err s_mp_pad(mp_int *mp, mp_size min); /* left pad with zeroes */ - -void s_mp_clamp(mp_int *mp); /* clip leading zeroes */ - -void s_mp_exch(mp_int *a, mp_int *b); /* swap a and b in place */ - -mp_err s_mp_lshd(mp_int *mp, mp_size p); /* left-shift by p digits */ -void s_mp_rshd(mp_int *mp, mp_size p); /* right-shift by p digits */ -void s_mp_div_2d(mp_int *mp, mp_digit d); /* divide by 2^d in place */ -void s_mp_mod_2d(mp_int *mp, mp_digit d); /* modulo 2^d in place */ -mp_err s_mp_mul_2d(mp_int *mp, mp_digit d); /* multiply by 2^d in place*/ -void s_mp_div_2(mp_int *mp); /* divide by 2 in place */ -mp_err s_mp_mul_2(mp_int *mp); /* multiply by 2 in place */ -mp_digit s_mp_norm(mp_int *a, mp_int *b); /* normalize for division */ -mp_err s_mp_add_d(mp_int *mp, mp_digit d); /* unsigned digit addition */ -mp_err s_mp_sub_d(mp_int *mp, mp_digit d); /* unsigned digit subtract */ -mp_err s_mp_mul_d(mp_int *mp, mp_digit d); /* unsigned digit multiply */ -mp_err s_mp_div_d(mp_int *mp, mp_digit d, mp_digit *r); - /* unsigned digit divide */ -mp_err s_mp_reduce(mp_int *x, mp_int *m, mp_int *mu); - /* Barrett reduction */ -mp_err s_mp_add(mp_int *a, mp_int *b); /* magnitude addition */ -mp_err s_mp_sub(mp_int *a, mp_int *b); /* magnitude subtract */ -mp_err s_mp_mul(mp_int *a, mp_int *b); /* magnitude multiply */ -#if 0 -void s_mp_kmul(mp_digit *a, mp_digit *b, mp_digit *out, mp_size len); - /* multiply buffers in place */ -#endif -#if MP_SQUARE -mp_err s_mp_sqr(mp_int *a); /* magnitude square */ -#else -#define s_mp_sqr(a) s_mp_mul(a, a) -#endif -mp_err s_mp_div(mp_int *a, mp_int *b); /* magnitude divide */ -mp_err s_mp_2expt(mp_int *a, mp_digit k); /* a = 2^k */ -int s_mp_cmp(mp_int *a, mp_int *b); /* magnitude comparison */ -int s_mp_cmp_d(mp_int *a, mp_digit d); /* magnitude digit compare */ -int s_mp_ispow2(mp_int *v); /* is v a power of 2? */ -int s_mp_ispow2d(mp_digit d); /* is d a power of 2? */ - -int s_mp_tovalue(char ch, int r); /* convert ch to value */ -char s_mp_todigit(int val, int r, int low); /* convert val to digit */ -int s_mp_outlen(int bits, int r); /* output length in bytes */ - -/* }}} */ - -/* {{{ Default precision manipulation */ - -unsigned int mp_get_prec(void) -{ - return s_mp_defprec; - -} /* end mp_get_prec() */ - -void mp_set_prec(unsigned int prec) -{ - if(prec == 0) - s_mp_defprec = MP_DEFPREC; - else - s_mp_defprec = prec; - -} /* end mp_set_prec() */ - -/* }}} */ - -/*------------------------------------------------------------------------*/ -/* {{{ mp_init(mp) */ - -/* - mp_init(mp) - - Initialize a new zero-valued mp_int. Returns MP_OKAY if successful, - MP_MEM if memory could not be allocated for the structure. - */ - -mp_err mp_init(mp_int *mp) -{ - return mp_init_size(mp, s_mp_defprec); - -} /* end mp_init() */ - -/* }}} */ - -/* {{{ mp_init_array(mp[], count) */ - -mp_err mp_init_array(mp_int mp[], int count) -{ - mp_err res; - int pos; - - ARGCHK(mp !=NULL && count > 0, MP_BADARG); - - for(pos = 0; pos < count; ++pos) { - if((res = mp_init(&mp[pos])) != MP_OKAY) - goto CLEANUP; - } - - return MP_OKAY; - - CLEANUP: - while(--pos >= 0) - mp_clear(&mp[pos]); - - return res; - -} /* end mp_init_array() */ - -/* }}} */ - -/* {{{ mp_init_size(mp, prec) */ - -/* - mp_init_size(mp, prec) - - Initialize a new zero-valued mp_int with at least the given - precision; returns MP_OKAY if successful, or MP_MEM if memory could - not be allocated for the structure. - */ - -mp_err mp_init_size(mp_int *mp, mp_size prec) -{ - ARGCHK(mp != NULL && prec > 0, MP_BADARG); - - if((DIGITS(mp) = s_mp_alloc(prec, sizeof(mp_digit))) == NULL) - return MP_MEM; - - SIGN(mp) = MP_ZPOS; - USED(mp) = 1; - ALLOC(mp) = prec; - - return MP_OKAY; - -} /* end mp_init_size() */ - -/* }}} */ - -/* {{{ mp_init_copy(mp, from) */ - -/* - mp_init_copy(mp, from) - - Initialize mp as an exact copy of from. Returns MP_OKAY if - successful, MP_MEM if memory could not be allocated for the new - structure. - */ - -mp_err mp_init_copy(mp_int *mp, mp_int *from) -{ - ARGCHK(mp != NULL && from != NULL, MP_BADARG); - - if(mp == from) - return MP_OKAY; - - if((DIGITS(mp) = s_mp_alloc(USED(from), sizeof(mp_digit))) == NULL) - return MP_MEM; - - s_mp_copy(DIGITS(from), DIGITS(mp), USED(from)); - USED(mp) = USED(from); - ALLOC(mp) = USED(from); - SIGN(mp) = SIGN(from); - - return MP_OKAY; - -} /* end mp_init_copy() */ - -/* }}} */ - -/* {{{ mp_copy(from, to) */ - -/* - mp_copy(from, to) - - Copies the mp_int 'from' to the mp_int 'to'. It is presumed that - 'to' has already been initialized (if not, use mp_init_copy() - instead). If 'from' and 'to' are identical, nothing happens. - */ - -mp_err mp_copy(mp_int *from, mp_int *to) -{ - ARGCHK(from != NULL && to != NULL, MP_BADARG); - - if(from == to) - return MP_OKAY; - - { /* copy */ - mp_digit *tmp; - - /* - If the allocated buffer in 'to' already has enough space to hold - all the used digits of 'from', we'll re-use it to avoid hitting - the memory allocater more than necessary; otherwise, we'd have - to grow anyway, so we just allocate a hunk and make the copy as - usual - */ - if(ALLOC(to) >= USED(from)) { - s_mp_setz(DIGITS(to) + USED(from), ALLOC(to) - USED(from)); - s_mp_copy(DIGITS(from), DIGITS(to), USED(from)); - - } else { - if((tmp = s_mp_alloc(USED(from), sizeof(mp_digit))) == NULL) - return MP_MEM; - - s_mp_copy(DIGITS(from), tmp, USED(from)); - - if(DIGITS(to) != NULL) { -#if MP_CRYPTO - s_mp_setz(DIGITS(to), ALLOC(to)); -#endif - s_mp_free(DIGITS(to)); - } - - DIGITS(to) = tmp; - ALLOC(to) = USED(from); - } - - /* Copy the precision and sign from the original */ - USED(to) = USED(from); - SIGN(to) = SIGN(from); - } /* end copy */ - - return MP_OKAY; - -} /* end mp_copy() */ - -/* }}} */ - -/* {{{ mp_exch(mp1, mp2) */ - -/* - mp_exch(mp1, mp2) - - Exchange mp1 and mp2 without allocating any intermediate memory - (well, unless you count the stack space needed for this call and the - locals it creates...). This cannot fail. - */ - -void mp_exch(mp_int *mp1, mp_int *mp2) -{ -#if MP_ARGCHK == 2 - assert(mp1 != NULL && mp2 != NULL); -#else - if(mp1 == NULL || mp2 == NULL) - return; -#endif - - s_mp_exch(mp1, mp2); - -} /* end mp_exch() */ - -/* }}} */ - -/* {{{ mp_clear(mp) */ - -/* - mp_clear(mp) - - Release the storage used by an mp_int, and void its fields so that - if someone calls mp_clear() again for the same int later, we won't - get tollchocked. - */ - -void mp_clear(mp_int *mp) -{ - if(mp == NULL) - return; - - if(DIGITS(mp) != NULL) { -#if MP_CRYPTO - s_mp_setz(DIGITS(mp), ALLOC(mp)); -#endif - s_mp_free(DIGITS(mp)); - DIGITS(mp) = NULL; - } - - USED(mp) = 0; - ALLOC(mp) = 0; - -} /* end mp_clear() */ - -/* }}} */ - -/* {{{ mp_clear_array(mp[], count) */ - -void mp_clear_array(mp_int mp[], int count) -{ - ARGCHK(mp != NULL && count > 0, MP_BADARG); - - while(--count >= 0) - mp_clear(&mp[count]); - -} /* end mp_clear_array() */ - -/* }}} */ - -/* {{{ mp_zero(mp) */ - -/* - mp_zero(mp) - - Set mp to zero. Does not change the allocated size of the structure, - and therefore cannot fail (except on a bad argument, which we ignore) - */ -void mp_zero(mp_int *mp) -{ - if(mp == NULL) - return; - - s_mp_setz(DIGITS(mp), ALLOC(mp)); - USED(mp) = 1; - SIGN(mp) = MP_ZPOS; - -} /* end mp_zero() */ - -/* }}} */ - -/* {{{ mp_set(mp, d) */ - -void mp_set(mp_int *mp, mp_digit d) -{ - if(mp == NULL) - return; - - mp_zero(mp); - DIGIT(mp, 0) = d; - -} /* end mp_set() */ - -/* }}} */ - -/* {{{ mp_set_int(mp, z) */ - -mp_err mp_set_int(mp_int *mp, long z) -{ - int ix; - unsigned long v = abs(z); - mp_err res; - - ARGCHK(mp != NULL, MP_BADARG); - - mp_zero(mp); - if(z == 0) - return MP_OKAY; /* shortcut for zero */ - - for(ix = sizeof(long) - 1; ix >= 0; ix--) { - - if((res = s_mp_mul_2d(mp, CHAR_BIT)) != MP_OKAY) - return res; - - res = s_mp_add_d(mp, - (mp_digit)((v >> (ix * CHAR_BIT)) & UCHAR_MAX)); - if(res != MP_OKAY) - return res; - - } - - if(z < 0) - SIGN(mp) = MP_NEG; - - return MP_OKAY; - -} /* end mp_set_int() */ - -/* }}} */ - -/*------------------------------------------------------------------------*/ -/* {{{ Digit arithmetic */ - -/* {{{ mp_add_d(a, d, b) */ - -/* - mp_add_d(a, d, b) - - Compute the sum b = a + d, for a single digit d. Respects the sign of - its primary addend (single digits are unsigned anyway). - */ - -mp_err mp_add_d(mp_int *a, mp_digit d, mp_int *b) -{ - mp_err res = MP_OKAY; - - ARGCHK(a != NULL && b != NULL, MP_BADARG); - - if((res = mp_copy(a, b)) != MP_OKAY) - return res; - - if(SIGN(b) == MP_ZPOS) { - res = s_mp_add_d(b, d); - } else if(s_mp_cmp_d(b, d) >= 0) { - res = s_mp_sub_d(b, d); - } else { - SIGN(b) = MP_ZPOS; - - DIGIT(b, 0) = d - DIGIT(b, 0); - } - - return res; - -} /* end mp_add_d() */ - -/* }}} */ - -/* {{{ mp_sub_d(a, d, b) */ - -/* - mp_sub_d(a, d, b) - - Compute the difference b = a - d, for a single digit d. Respects the - sign of its subtrahend (single digits are unsigned anyway). - */ - -mp_err mp_sub_d(mp_int *a, mp_digit d, mp_int *b) -{ - mp_err res; - - ARGCHK(a != NULL && b != NULL, MP_BADARG); - - if((res = mp_copy(a, b)) != MP_OKAY) - return res; - - if(SIGN(b) == MP_NEG) { - if((res = s_mp_add_d(b, d)) != MP_OKAY) - return res; - - } else if(s_mp_cmp_d(b, d) >= 0) { - if((res = s_mp_sub_d(b, d)) != MP_OKAY) - return res; - - } else { - mp_neg(b, b); - - DIGIT(b, 0) = d - DIGIT(b, 0); - SIGN(b) = MP_NEG; - } - - if(s_mp_cmp_d(b, 0) == 0) - SIGN(b) = MP_ZPOS; - - return MP_OKAY; - -} /* end mp_sub_d() */ - -/* }}} */ - -/* {{{ mp_mul_d(a, d, b) */ - -/* - mp_mul_d(a, d, b) - - Compute the product b = a * d, for a single digit d. Respects the sign - of its multiplicand (single digits are unsigned anyway) - */ - -mp_err mp_mul_d(mp_int *a, mp_digit d, mp_int *b) -{ - mp_err res; - - ARGCHK(a != NULL && b != NULL, MP_BADARG); - - if(d == 0) { - mp_zero(b); - return MP_OKAY; - } - - if((res = mp_copy(a, b)) != MP_OKAY) - return res; - - res = s_mp_mul_d(b, d); - - return res; - -} /* end mp_mul_d() */ - -/* }}} */ - -/* {{{ mp_mul_2(a, c) */ - -mp_err mp_mul_2(mp_int *a, mp_int *c) -{ - mp_err res; - - ARGCHK(a != NULL && c != NULL, MP_BADARG); - - if((res = mp_copy(a, c)) != MP_OKAY) - return res; - - return s_mp_mul_2(c); - -} /* end mp_mul_2() */ - -/* }}} */ - -/* {{{ mp_div_d(a, d, q, r) */ - -/* - mp_div_d(a, d, q, r) - - Compute the quotient q = a / d and remainder r = a mod d, for a - single digit d. Respects the sign of its divisor (single digits are - unsigned anyway). - */ - -mp_err mp_div_d(mp_int *a, mp_digit d, mp_int *q, mp_digit *r) -{ - mp_err res; - mp_digit rem; - int pow; - - ARGCHK(a != NULL, MP_BADARG); - - if(d == 0) - return MP_RANGE; - - /* Shortcut for powers of two ... */ - if((pow = s_mp_ispow2d(d)) >= 0) { - mp_digit mask; - - mask = (1 << pow) - 1; - rem = DIGIT(a, 0) & mask; - - if(q) { - mp_copy(a, q); - s_mp_div_2d(q, pow); - } - - if(r) - *r = rem; - - return MP_OKAY; - } - - /* - If the quotient is actually going to be returned, we'll try to - avoid hitting the memory allocator by copying the dividend into it - and doing the division there. This can't be any _worse_ than - always copying, and will sometimes be better (since it won't make - another copy) - - If it's not going to be returned, we need to allocate a temporary - to hold the quotient, which will just be discarded. - */ - if(q) { - if((res = mp_copy(a, q)) != MP_OKAY) - return res; - - res = s_mp_div_d(q, d, &rem); - if(s_mp_cmp_d(q, 0) == MP_EQ) - SIGN(q) = MP_ZPOS; - - } else { - mp_int qp; - - if((res = mp_init_copy(&qp, a)) != MP_OKAY) - return res; - - res = s_mp_div_d(&qp, d, &rem); - if(s_mp_cmp_d(&qp, 0) == 0) - SIGN(&qp) = MP_ZPOS; - - mp_clear(&qp); - } - - if(r) - *r = rem; - - return res; - -} /* end mp_div_d() */ - -/* }}} */ - -/* {{{ mp_div_2(a, c) */ - -/* - mp_div_2(a, c) - - Compute c = a / 2, disregarding the remainder. - */ - -mp_err mp_div_2(mp_int *a, mp_int *c) -{ - mp_err res; - - ARGCHK(a != NULL && c != NULL, MP_BADARG); - - if((res = mp_copy(a, c)) != MP_OKAY) - return res; - - s_mp_div_2(c); - - return MP_OKAY; - -} /* end mp_div_2() */ - -/* }}} */ - -/* {{{ mp_expt_d(a, d, b) */ - -mp_err mp_expt_d(mp_int *a, mp_digit d, mp_int *c) -{ - mp_int s, x; - mp_err res; - - ARGCHK(a != NULL && c != NULL, MP_BADARG); - - if((res = mp_init(&s)) != MP_OKAY) - return res; - if((res = mp_init_copy(&x, a)) != MP_OKAY) - goto X; - - DIGIT(&s, 0) = 1; - - while(d != 0) { - if(d & 1) { - if((res = s_mp_mul(&s, &x)) != MP_OKAY) - goto CLEANUP; - } - - d >>= 1; - - if((res = s_mp_sqr(&x)) != MP_OKAY) - goto CLEANUP; - } - - s_mp_exch(&s, c); - -CLEANUP: - mp_clear(&x); -X: - mp_clear(&s); - - return res; - -} /* end mp_expt_d() */ - -/* }}} */ - -/* }}} */ - -/*------------------------------------------------------------------------*/ -/* {{{ Full arithmetic */ - -/* {{{ mp_abs(a, b) */ - -/* - mp_abs(a, b) - - Compute b = |a|. 'a' and 'b' may be identical. - */ - -mp_err mp_abs(mp_int *a, mp_int *b) -{ - mp_err res; - - ARGCHK(a != NULL && b != NULL, MP_BADARG); - - if((res = mp_copy(a, b)) != MP_OKAY) - return res; - - SIGN(b) = MP_ZPOS; - - return MP_OKAY; - -} /* end mp_abs() */ - -/* }}} */ - -/* {{{ mp_neg(a, b) */ - -/* - mp_neg(a, b) - - Compute b = -a. 'a' and 'b' may be identical. - */ - -mp_err mp_neg(mp_int *a, mp_int *b) -{ - mp_err res; - - ARGCHK(a != NULL && b != NULL, MP_BADARG); - - if((res = mp_copy(a, b)) != MP_OKAY) - return res; - - if(s_mp_cmp_d(b, 0) == MP_EQ) - SIGN(b) = MP_ZPOS; - else - SIGN(b) = (SIGN(b) == MP_NEG) ? MP_ZPOS : MP_NEG; - - return MP_OKAY; - -} /* end mp_neg() */ - -/* }}} */ - -/* {{{ mp_add(a, b, c) */ - -/* - mp_add(a, b, c) - - Compute c = a + b. All parameters may be identical. - */ - -mp_err mp_add(mp_int *a, mp_int *b, mp_int *c) -{ - mp_err res; - int cmp; - - ARGCHK(a != NULL && b != NULL && c != NULL, MP_BADARG); - - if(SIGN(a) == SIGN(b)) { /* same sign: add values, keep sign */ - - /* Commutativity of addition lets us do this in either order, - so we avoid having to use a temporary even if the result - is supposed to replace the output - */ - if(c == b) { - if((res = s_mp_add(c, a)) != MP_OKAY) - return res; - } else { - if(c != a && (res = mp_copy(a, c)) != MP_OKAY) - return res; - - if((res = s_mp_add(c, b)) != MP_OKAY) - return res; - } - - } else if((cmp = s_mp_cmp(a, b)) > 0) { /* different sign: a > b */ - - /* If the output is going to be clobbered, we will use a temporary - variable; otherwise, we'll do it without touching the memory - allocator at all, if possible - */ - if(c == b) { - mp_int tmp; - - if((res = mp_init_copy(&tmp, a)) != MP_OKAY) - return res; - if((res = s_mp_sub(&tmp, b)) != MP_OKAY) { - mp_clear(&tmp); - return res; - } - - s_mp_exch(&tmp, c); - mp_clear(&tmp); - - } else { - - if(c != a && (res = mp_copy(a, c)) != MP_OKAY) - return res; - if((res = s_mp_sub(c, b)) != MP_OKAY) - return res; - - } - - } else if(cmp == 0) { /* different sign, a == b */ - - mp_zero(c); - return MP_OKAY; - - } else { /* different sign: a < b */ - - /* See above... */ - if(c == a) { - mp_int tmp; - - if((res = mp_init_copy(&tmp, b)) != MP_OKAY) - return res; - if((res = s_mp_sub(&tmp, a)) != MP_OKAY) { - mp_clear(&tmp); - return res; - } - - s_mp_exch(&tmp, c); - mp_clear(&tmp); - - } else { - - if(c != b && (res = mp_copy(b, c)) != MP_OKAY) - return res; - if((res = s_mp_sub(c, a)) != MP_OKAY) - return res; - - } - } - - if(USED(c) == 1 && DIGIT(c, 0) == 0) - SIGN(c) = MP_ZPOS; - - return MP_OKAY; - -} /* end mp_add() */ - -/* }}} */ - -/* {{{ mp_sub(a, b, c) */ - -/* - mp_sub(a, b, c) - - Compute c = a - b. All parameters may be identical. - */ - -mp_err mp_sub(mp_int *a, mp_int *b, mp_int *c) -{ - mp_err res; - int cmp; - - ARGCHK(a != NULL && b != NULL && c != NULL, MP_BADARG); - - if(SIGN(a) != SIGN(b)) { - if(c == a) { - if((res = s_mp_add(c, b)) != MP_OKAY) - return res; - } else { - if(c != b && ((res = mp_copy(b, c)) != MP_OKAY)) - return res; - if((res = s_mp_add(c, a)) != MP_OKAY) - return res; - SIGN(c) = SIGN(a); - } - - } else if((cmp = s_mp_cmp(a, b)) > 0) { /* Same sign, a > b */ - if(c == b) { - mp_int tmp; - - if((res = mp_init_copy(&tmp, a)) != MP_OKAY) - return res; - if((res = s_mp_sub(&tmp, b)) != MP_OKAY) { - mp_clear(&tmp); - return res; - } - s_mp_exch(&tmp, c); - mp_clear(&tmp); - - } else { - if(c != a && ((res = mp_copy(a, c)) != MP_OKAY)) - return res; - - if((res = s_mp_sub(c, b)) != MP_OKAY) - return res; - } - - } else if(cmp == 0) { /* Same sign, equal magnitude */ - mp_zero(c); - return MP_OKAY; - - } else { /* Same sign, b > a */ - if(c == a) { - mp_int tmp; - - if((res = mp_init_copy(&tmp, b)) != MP_OKAY) - return res; - - if((res = s_mp_sub(&tmp, a)) != MP_OKAY) { - mp_clear(&tmp); - return res; - } - s_mp_exch(&tmp, c); - mp_clear(&tmp); - - } else { - if(c != b && ((res = mp_copy(b, c)) != MP_OKAY)) - return res; - - if((res = s_mp_sub(c, a)) != MP_OKAY) - return res; - } - - SIGN(c) = !SIGN(b); - } - - if(USED(c) == 1 && DIGIT(c, 0) == 0) - SIGN(c) = MP_ZPOS; - - return MP_OKAY; - -} /* end mp_sub() */ - -/* }}} */ - -/* {{{ mp_mul(a, b, c) */ - -/* - mp_mul(a, b, c) - - Compute c = a * b. All parameters may be identical. - */ - -mp_err mp_mul(mp_int *a, mp_int *b, mp_int *c) -{ - mp_err res; - mp_sign sgn; - - ARGCHK(a != NULL && b != NULL && c != NULL, MP_BADARG); - - sgn = (SIGN(a) == SIGN(b)) ? MP_ZPOS : MP_NEG; - - if(c == b) { - if((res = s_mp_mul(c, a)) != MP_OKAY) - return res; - - } else { - if((res = mp_copy(a, c)) != MP_OKAY) - return res; - - if((res = s_mp_mul(c, b)) != MP_OKAY) - return res; - } - - if(sgn == MP_ZPOS || s_mp_cmp_d(c, 0) == MP_EQ) - SIGN(c) = MP_ZPOS; - else - SIGN(c) = sgn; - - return MP_OKAY; - -} /* end mp_mul() */ - -/* }}} */ - -/* {{{ mp_mul_2d(a, d, c) */ - -/* - mp_mul_2d(a, d, c) - - Compute c = a * 2^d. a may be the same as c. - */ - -mp_err mp_mul_2d(mp_int *a, mp_digit d, mp_int *c) -{ - mp_err res; - - ARGCHK(a != NULL && c != NULL, MP_BADARG); - - if((res = mp_copy(a, c)) != MP_OKAY) - return res; - - if(d == 0) - return MP_OKAY; - - return s_mp_mul_2d(c, d); - -} /* end mp_mul() */ - -/* }}} */ - -/* {{{ mp_sqr(a, b) */ - -#if MP_SQUARE -mp_err mp_sqr(mp_int *a, mp_int *b) -{ - mp_err res; - - ARGCHK(a != NULL && b != NULL, MP_BADARG); - - if((res = mp_copy(a, b)) != MP_OKAY) - return res; - - if((res = s_mp_sqr(b)) != MP_OKAY) - return res; - - SIGN(b) = MP_ZPOS; - - return MP_OKAY; - -} /* end mp_sqr() */ -#endif - -/* }}} */ - -/* {{{ mp_div(a, b, q, r) */ - -/* - mp_div(a, b, q, r) - - Compute q = a / b and r = a mod b. Input parameters may be re-used - as output parameters. If q or r is NULL, that portion of the - computation will be discarded (although it will still be computed) - - Pay no attention to the hacker behind the curtain. - */ - -mp_err mp_div(mp_int *a, mp_int *b, mp_int *q, mp_int *r) -{ - mp_err res; - mp_int qtmp, rtmp; - int cmp; - - ARGCHK(a != NULL && b != NULL, MP_BADARG); - - if(mp_cmp_z(b) == MP_EQ) - return MP_RANGE; - - /* If a <= b, we can compute the solution without division, and - avoid any memory allocation - */ - if((cmp = s_mp_cmp(a, b)) < 0) { - if(r) { - if((res = mp_copy(a, r)) != MP_OKAY) - return res; - } - - if(q) - mp_zero(q); - - return MP_OKAY; - - } else if(cmp == 0) { - - /* Set quotient to 1, with appropriate sign */ - if(q) { - int qneg = (SIGN(a) != SIGN(b)); - - mp_set(q, 1); - if(qneg) - SIGN(q) = MP_NEG; - } - - if(r) - mp_zero(r); - - return MP_OKAY; - } - - /* If we get here, it means we actually have to do some division */ - - /* Set up some temporaries... */ - if((res = mp_init_copy(&qtmp, a)) != MP_OKAY) - return res; - if((res = mp_init_copy(&rtmp, b)) != MP_OKAY) - goto CLEANUP; - - if((res = s_mp_div(&qtmp, &rtmp)) != MP_OKAY) - goto CLEANUP; - - /* Compute the signs for the output */ - SIGN(&rtmp) = SIGN(a); /* Sr = Sa */ - if(SIGN(a) == SIGN(b)) - SIGN(&qtmp) = MP_ZPOS; /* Sq = MP_ZPOS if Sa = Sb */ - else - SIGN(&qtmp) = MP_NEG; /* Sq = MP_NEG if Sa != Sb */ - - if(s_mp_cmp_d(&qtmp, 0) == MP_EQ) - SIGN(&qtmp) = MP_ZPOS; - if(s_mp_cmp_d(&rtmp, 0) == MP_EQ) - SIGN(&rtmp) = MP_ZPOS; - - /* Copy output, if it is needed */ - if(q) - s_mp_exch(&qtmp, q); - - if(r) - s_mp_exch(&rtmp, r); - -CLEANUP: - mp_clear(&rtmp); - mp_clear(&qtmp); - - return res; - -} /* end mp_div() */ - -/* }}} */ - -/* {{{ mp_div_2d(a, d, q, r) */ - -mp_err mp_div_2d(mp_int *a, mp_digit d, mp_int *q, mp_int *r) -{ - mp_err res; - - ARGCHK(a != NULL, MP_BADARG); - - if(q) { - if((res = mp_copy(a, q)) != MP_OKAY) - return res; - - s_mp_div_2d(q, d); - } - - if(r) { - if((res = mp_copy(a, r)) != MP_OKAY) - return res; - - s_mp_mod_2d(r, d); - } - - return MP_OKAY; - -} /* end mp_div_2d() */ - -/* }}} */ - -/* {{{ mp_expt(a, b, c) */ - -/* - mp_expt(a, b, c) - - Compute c = a ** b, that is, raise a to the b power. Uses a - standard iterative square-and-multiply technique. - */ - -mp_err mp_expt(mp_int *a, mp_int *b, mp_int *c) -{ - mp_int s, x; - mp_err res; - mp_digit d; - unsigned int bit, dig; - - ARGCHK(a != NULL && b != NULL && c != NULL, MP_BADARG); - - if(mp_cmp_z(b) < 0) - return MP_RANGE; - - if((res = mp_init(&s)) != MP_OKAY) - return res; - - mp_set(&s, 1); - - if((res = mp_init_copy(&x, a)) != MP_OKAY) - goto X; - - /* Loop over low-order digits in ascending order */ - for(dig = 0; dig < (USED(b) - 1); dig++) { - d = DIGIT(b, dig); - - /* Loop over bits of each non-maximal digit */ - for(bit = 0; bit < DIGIT_BIT; bit++) { - if(d & 1) { - if((res = s_mp_mul(&s, &x)) != MP_OKAY) - goto CLEANUP; - } - - d >>= 1; - - if((res = s_mp_sqr(&x)) != MP_OKAY) - goto CLEANUP; - } - } - - /* Consider now the last digit... */ - d = DIGIT(b, dig); - - while(d) { - if(d & 1) { - if((res = s_mp_mul(&s, &x)) != MP_OKAY) - goto CLEANUP; - } - - d >>= 1; - - if((res = s_mp_sqr(&x)) != MP_OKAY) - goto CLEANUP; - } - - if(mp_iseven(b)) - SIGN(&s) = SIGN(a); - - res = mp_copy(&s, c); - -CLEANUP: - mp_clear(&x); -X: - mp_clear(&s); - - return res; - -} /* end mp_expt() */ - -/* }}} */ - -/* {{{ mp_2expt(a, k) */ - -/* Compute a = 2^k */ - -mp_err mp_2expt(mp_int *a, mp_digit k) -{ - ARGCHK(a != NULL, MP_BADARG); - - return s_mp_2expt(a, k); - -} /* end mp_2expt() */ - -/* }}} */ - -/* {{{ mp_mod(a, m, c) */ - -/* - mp_mod(a, m, c) - - Compute c = a (mod m). Result will always be 0 <= c < m. - */ - -mp_err mp_mod(mp_int *a, mp_int *m, mp_int *c) -{ - mp_err res; - int mag; - - ARGCHK(a != NULL && m != NULL && c != NULL, MP_BADARG); - - if(SIGN(m) == MP_NEG) - return MP_RANGE; - - /* - If |a| > m, we need to divide to get the remainder and take the - absolute value. - - If |a| < m, we don't need to do any division, just copy and adjust - the sign (if a is negative). - - If |a| == m, we can simply set the result to zero. - - This order is intended to minimize the average path length of the - comparison chain on common workloads -- the most frequent cases are - that |a| != m, so we do those first. - */ - if((mag = s_mp_cmp(a, m)) > 0) { - if((res = mp_div(a, m, NULL, c)) != MP_OKAY) - return res; - - if(SIGN(c) == MP_NEG) { - if((res = mp_add(c, m, c)) != MP_OKAY) - return res; - } - - } else if(mag < 0) { - if((res = mp_copy(a, c)) != MP_OKAY) - return res; - - if(mp_cmp_z(a) < 0) { - if((res = mp_add(c, m, c)) != MP_OKAY) - return res; - - } - - } else { - mp_zero(c); - - } - - return MP_OKAY; - -} /* end mp_mod() */ - -/* }}} */ - -/* {{{ mp_mod_d(a, d, c) */ - -/* - mp_mod_d(a, d, c) - - Compute c = a (mod d). Result will always be 0 <= c < d - */ -mp_err mp_mod_d(mp_int *a, mp_digit d, mp_digit *c) -{ - mp_err res; - mp_digit rem; - - ARGCHK(a != NULL && c != NULL, MP_BADARG); - - if(s_mp_cmp_d(a, d) > 0) { - if((res = mp_div_d(a, d, NULL, &rem)) != MP_OKAY) - return res; - - } else { - if(SIGN(a) == MP_NEG) - rem = d - DIGIT(a, 0); - else - rem = DIGIT(a, 0); - } - - if(c) - *c = rem; - - return MP_OKAY; - -} /* end mp_mod_d() */ - -/* }}} */ - -/* {{{ mp_sqrt(a, b) */ - -/* - mp_sqrt(a, b) - - Compute the integer square root of a, and store the result in b. - Uses an integer-arithmetic version of Newton's iterative linear - approximation technique to determine this value; the result has the - following two properties: - - b^2 <= a - (b+1)^2 >= a - - It is a range error to pass a negative value. - */ -mp_err mp_sqrt(mp_int *a, mp_int *b) -{ - mp_int x, t; - mp_err res; - - ARGCHK(a != NULL && b != NULL, MP_BADARG); - - /* Cannot take square root of a negative value */ - if(SIGN(a) == MP_NEG) - return MP_RANGE; - - /* Special cases for zero and one, trivial */ - if(mp_cmp_d(a, 0) == MP_EQ || mp_cmp_d(a, 1) == MP_EQ) - return mp_copy(a, b); - - /* Initialize the temporaries we'll use below */ - if((res = mp_init_size(&t, USED(a))) != MP_OKAY) - return res; - - /* Compute an initial guess for the iteration as a itself */ - if((res = mp_init_copy(&x, a)) != MP_OKAY) - goto X; - -s_mp_rshd(&x, (USED(&x)/2)+1); -mp_add_d(&x, 1, &x); - - for(;;) { - /* t = (x * x) - a */ - mp_copy(&x, &t); /* can't fail, t is big enough for original x */ - if((res = mp_sqr(&t, &t)) != MP_OKAY || - (res = mp_sub(&t, a, &t)) != MP_OKAY) - goto CLEANUP; - - /* t = t / 2x */ - s_mp_mul_2(&x); - if((res = mp_div(&t, &x, &t, NULL)) != MP_OKAY) - goto CLEANUP; - s_mp_div_2(&x); - - /* Terminate the loop, if the quotient is zero */ - if(mp_cmp_z(&t) == MP_EQ) - break; - - /* x = x - t */ - if((res = mp_sub(&x, &t, &x)) != MP_OKAY) - goto CLEANUP; - - } - - /* Copy result to output parameter */ - mp_sub_d(&x, 1, &x); - s_mp_exch(&x, b); - - CLEANUP: - mp_clear(&x); - X: - mp_clear(&t); - - return res; - -} /* end mp_sqrt() */ - -/* }}} */ - -/* }}} */ - -/*------------------------------------------------------------------------*/ -/* {{{ Modular arithmetic */ - -#if MP_MODARITH -/* {{{ mp_addmod(a, b, m, c) */ - -/* - mp_addmod(a, b, m, c) - - Compute c = (a + b) mod m - */ - -mp_err mp_addmod(mp_int *a, mp_int *b, mp_int *m, mp_int *c) -{ - mp_err res; - - ARGCHK(a != NULL && b != NULL && m != NULL && c != NULL, MP_BADARG); - - if((res = mp_add(a, b, c)) != MP_OKAY) - return res; - if((res = mp_mod(c, m, c)) != MP_OKAY) - return res; - - return MP_OKAY; - -} - -/* }}} */ - -/* {{{ mp_submod(a, b, m, c) */ - -/* - mp_submod(a, b, m, c) - - Compute c = (a - b) mod m - */ - -mp_err mp_submod(mp_int *a, mp_int *b, mp_int *m, mp_int *c) -{ - mp_err res; - - ARGCHK(a != NULL && b != NULL && m != NULL && c != NULL, MP_BADARG); - - if((res = mp_sub(a, b, c)) != MP_OKAY) - return res; - if((res = mp_mod(c, m, c)) != MP_OKAY) - return res; - - return MP_OKAY; - -} - -/* }}} */ - -/* {{{ mp_mulmod(a, b, m, c) */ - -/* - mp_mulmod(a, b, m, c) - - Compute c = (a * b) mod m - */ - -mp_err mp_mulmod(mp_int *a, mp_int *b, mp_int *m, mp_int *c) -{ - mp_err res; - - ARGCHK(a != NULL && b != NULL && m != NULL && c != NULL, MP_BADARG); - - if((res = mp_mul(a, b, c)) != MP_OKAY) - return res; - if((res = mp_mod(c, m, c)) != MP_OKAY) - return res; - - return MP_OKAY; - -} - -/* }}} */ - -/* {{{ mp_sqrmod(a, m, c) */ - -#if MP_SQUARE -mp_err mp_sqrmod(mp_int *a, mp_int *m, mp_int *c) -{ - mp_err res; - - ARGCHK(a != NULL && m != NULL && c != NULL, MP_BADARG); - - if((res = mp_sqr(a, c)) != MP_OKAY) - return res; - if((res = mp_mod(c, m, c)) != MP_OKAY) - return res; - - return MP_OKAY; - -} /* end mp_sqrmod() */ -#endif - -/* }}} */ - -/* {{{ mp_exptmod(a, b, m, c) */ - -/* - mp_exptmod(a, b, m, c) - - Compute c = (a ** b) mod m. Uses a standard square-and-multiply - method with modular reductions at each step. (This is basically the - same code as mp_expt(), except for the addition of the reductions) - - The modular reductions are done using Barrett's algorithm (see - s_mp_reduce() below for details) - */ - -mp_err mp_exptmod(mp_int *a, mp_int *b, mp_int *m, mp_int *c) -{ - mp_int s, x, mu; - mp_err res; - mp_digit d, *db = DIGITS(b); - mp_size ub = USED(b); - unsigned int bit, dig; - - ARGCHK(a != NULL && b != NULL && c != NULL, MP_BADARG); - - if(mp_cmp_z(b) < 0 || mp_cmp_z(m) <= 0) - return MP_RANGE; - - if((res = mp_init(&s)) != MP_OKAY) - return res; - if((res = mp_init_copy(&x, a)) != MP_OKAY) - goto X; - if((res = mp_mod(&x, m, &x)) != MP_OKAY || - (res = mp_init(&mu)) != MP_OKAY) - goto MU; - - mp_set(&s, 1); - - /* mu = b^2k / m */ - s_mp_add_d(&mu, 1); - s_mp_lshd(&mu, 2 * USED(m)); - if((res = mp_div(&mu, m, &mu, NULL)) != MP_OKAY) - goto CLEANUP; - - /* Loop over digits of b in ascending order, except highest order */ - for(dig = 0; dig < (ub - 1); dig++) { - d = *db++; - - /* Loop over the bits of the lower-order digits */ - for(bit = 0; bit < DIGIT_BIT; bit++) { - if(d & 1) { - if((res = s_mp_mul(&s, &x)) != MP_OKAY) - goto CLEANUP; - if((res = s_mp_reduce(&s, m, &mu)) != MP_OKAY) - goto CLEANUP; - } - - d >>= 1; - - if((res = s_mp_sqr(&x)) != MP_OKAY) - goto CLEANUP; - if((res = s_mp_reduce(&x, m, &mu)) != MP_OKAY) - goto CLEANUP; - } - } - - /* Now do the last digit... */ - d = *db; - - while(d) { - if(d & 1) { - if((res = s_mp_mul(&s, &x)) != MP_OKAY) - goto CLEANUP; - if((res = s_mp_reduce(&s, m, &mu)) != MP_OKAY) - goto CLEANUP; - } - - d >>= 1; - - if((res = s_mp_sqr(&x)) != MP_OKAY) - goto CLEANUP; - if((res = s_mp_reduce(&x, m, &mu)) != MP_OKAY) - goto CLEANUP; - } - - s_mp_exch(&s, c); - - CLEANUP: - mp_clear(&mu); - MU: - mp_clear(&x); - X: - mp_clear(&s); - - return res; - -} /* end mp_exptmod() */ - -/* }}} */ - -/* {{{ mp_exptmod_d(a, d, m, c) */ - -mp_err mp_exptmod_d(mp_int *a, mp_digit d, mp_int *m, mp_int *c) -{ - mp_int s, x; - mp_err res; - - ARGCHK(a != NULL && c != NULL, MP_BADARG); - - if((res = mp_init(&s)) != MP_OKAY) - return res; - if((res = mp_init_copy(&x, a)) != MP_OKAY) - goto X; - - mp_set(&s, 1); - - while(d != 0) { - if(d & 1) { - if((res = s_mp_mul(&s, &x)) != MP_OKAY || - (res = mp_mod(&s, m, &s)) != MP_OKAY) - goto CLEANUP; - } - - d /= 2; - - if((res = s_mp_sqr(&x)) != MP_OKAY || - (res = mp_mod(&x, m, &x)) != MP_OKAY) - goto CLEANUP; - } - - s_mp_exch(&s, c); - -CLEANUP: - mp_clear(&x); -X: - mp_clear(&s); - - return res; - -} /* end mp_exptmod_d() */ - -/* }}} */ -#endif /* if MP_MODARITH */ - -/* }}} */ - -/*------------------------------------------------------------------------*/ -/* {{{ Comparison functions */ - -/* {{{ mp_cmp_z(a) */ - -/* - mp_cmp_z(a) - - Compare a <=> 0. Returns <0 if a<0, 0 if a=0, >0 if a>0. - */ - -int mp_cmp_z(mp_int *a) -{ - if(SIGN(a) == MP_NEG) - return MP_LT; - else if(USED(a) == 1 && DIGIT(a, 0) == 0) - return MP_EQ; - else - return MP_GT; - -} /* end mp_cmp_z() */ - -/* }}} */ - -/* {{{ mp_cmp_d(a, d) */ - -/* - mp_cmp_d(a, d) - - Compare a <=> d. Returns <0 if a<d, 0 if a=d, >0 if a>d - */ - -int mp_cmp_d(mp_int *a, mp_digit d) -{ - ARGCHK(a != NULL, MP_EQ); - - if(SIGN(a) == MP_NEG) - return MP_LT; - - return s_mp_cmp_d(a, d); - -} /* end mp_cmp_d() */ - -/* }}} */ - -/* {{{ mp_cmp(a, b) */ - -int mp_cmp(mp_int *a, mp_int *b) -{ - ARGCHK(a != NULL && b != NULL, MP_EQ); - - if(SIGN(a) == SIGN(b)) { - int mag; - - if((mag = s_mp_cmp(a, b)) == MP_EQ) - return MP_EQ; - - if(SIGN(a) == MP_ZPOS) - return mag; - else - return -mag; - - } else if(SIGN(a) == MP_ZPOS) { - return MP_GT; - } else { - return MP_LT; - } - -} /* end mp_cmp() */ - -/* }}} */ - -/* {{{ mp_cmp_mag(a, b) */ - -/* - mp_cmp_mag(a, b) - - Compares |a| <=> |b|, and returns an appropriate comparison result - */ - -int mp_cmp_mag(mp_int *a, mp_int *b) -{ - ARGCHK(a != NULL && b != NULL, MP_EQ); - - return s_mp_cmp(a, b); - -} /* end mp_cmp_mag() */ - -/* }}} */ - -/* {{{ mp_cmp_int(a, z) */ - -/* - This just converts z to an mp_int, and uses the existing comparison - routines. This is sort of inefficient, but it's not clear to me how - frequently this wil get used anyway. For small positive constants, - you can always use mp_cmp_d(), and for zero, there is mp_cmp_z(). - */ -int mp_cmp_int(mp_int *a, long z) -{ - mp_int tmp; - int out; - - ARGCHK(a != NULL, MP_EQ); - - mp_init(&tmp); mp_set_int(&tmp, z); - out = mp_cmp(a, &tmp); - mp_clear(&tmp); - - return out; - -} /* end mp_cmp_int() */ - -/* }}} */ - -/* {{{ mp_isodd(a) */ - -/* - mp_isodd(a) - - Returns a true (non-zero) value if a is odd, false (zero) otherwise. - */ -int mp_isodd(mp_int *a) -{ - ARGCHK(a != NULL, 0); - - return (DIGIT(a, 0) & 1); - -} /* end mp_isodd() */ - -/* }}} */ - -/* {{{ mp_iseven(a) */ - -int mp_iseven(mp_int *a) -{ - return !mp_isodd(a); - -} /* end mp_iseven() */ - -/* }}} */ - -/* }}} */ - -/*------------------------------------------------------------------------*/ -/* {{{ Number theoretic functions */ - -#if MP_NUMTH -/* {{{ mp_gcd(a, b, c) */ - -/* - Like the old mp_gcd() function, except computes the GCD using the - binary algorithm due to Josef Stein in 1961 (via Knuth). - */ -mp_err mp_gcd(mp_int *a, mp_int *b, mp_int *c) -{ - mp_err res; - mp_int u, v, t; - mp_size k = 0; - - ARGCHK(a != NULL && b != NULL && c != NULL, MP_BADARG); - - if(mp_cmp_z(a) == MP_EQ && mp_cmp_z(b) == MP_EQ) - return MP_RANGE; - if(mp_cmp_z(a) == MP_EQ) { - return mp_copy(b, c); - } else if(mp_cmp_z(b) == MP_EQ) { - return mp_copy(a, c); - } - - if((res = mp_init(&t)) != MP_OKAY) - return res; - if((res = mp_init_copy(&u, a)) != MP_OKAY) - goto U; - if((res = mp_init_copy(&v, b)) != MP_OKAY) - goto V; - - SIGN(&u) = MP_ZPOS; - SIGN(&v) = MP_ZPOS; - - /* Divide out common factors of 2 until at least 1 of a, b is even */ - while(mp_iseven(&u) && mp_iseven(&v)) { - s_mp_div_2(&u); - s_mp_div_2(&v); - ++k; - } - - /* Initialize t */ - if(mp_isodd(&u)) { - if((res = mp_copy(&v, &t)) != MP_OKAY) - goto CLEANUP; - - /* t = -v */ - if(SIGN(&v) == MP_ZPOS) - SIGN(&t) = MP_NEG; - else - SIGN(&t) = MP_ZPOS; - - } else { - if((res = mp_copy(&u, &t)) != MP_OKAY) - goto CLEANUP; - - } - - for(;;) { - while(mp_iseven(&t)) { - s_mp_div_2(&t); - } - - if(mp_cmp_z(&t) == MP_GT) { - if((res = mp_copy(&t, &u)) != MP_OKAY) - goto CLEANUP; - - } else { - if((res = mp_copy(&t, &v)) != MP_OKAY) - goto CLEANUP; - - /* v = -t */ - if(SIGN(&t) == MP_ZPOS) - SIGN(&v) = MP_NEG; - else - SIGN(&v) = MP_ZPOS; - } - - if((res = mp_sub(&u, &v, &t)) != MP_OKAY) - goto CLEANUP; - - if(s_mp_cmp_d(&t, 0) == MP_EQ) - break; - } - - s_mp_2expt(&v, k); /* v = 2^k */ - res = mp_mul(&u, &v, c); /* c = u * v */ - - CLEANUP: - mp_clear(&v); - V: - mp_clear(&u); - U: - mp_clear(&t); - - return res; - -} /* end mp_bgcd() */ - -/* }}} */ - -/* {{{ mp_lcm(a, b, c) */ - -/* We compute the least common multiple using the rule: - - ab = [a, b](a, b) - - ... by computing the product, and dividing out the gcd. - */ - -mp_err mp_lcm(mp_int *a, mp_int *b, mp_int *c) -{ - mp_int gcd, prod; - mp_err res; - - ARGCHK(a != NULL && b != NULL && c != NULL, MP_BADARG); - - /* Set up temporaries */ - if((res = mp_init(&gcd)) != MP_OKAY) - return res; - if((res = mp_init(&prod)) != MP_OKAY) - goto GCD; - - if((res = mp_mul(a, b, &prod)) != MP_OKAY) - goto CLEANUP; - if((res = mp_gcd(a, b, &gcd)) != MP_OKAY) - goto CLEANUP; - - res = mp_div(&prod, &gcd, c, NULL); - - CLEANUP: - mp_clear(&prod); - GCD: - mp_clear(&gcd); - - return res; - -} /* end mp_lcm() */ - -/* }}} */ - -/* {{{ mp_xgcd(a, b, g, x, y) */ - -/* - mp_xgcd(a, b, g, x, y) - - Compute g = (a, b) and values x and y satisfying Bezout's identity - (that is, ax + by = g). This uses the extended binary GCD algorithm - based on the Stein algorithm used for mp_gcd() - */ - -mp_err mp_xgcd(mp_int *a, mp_int *b, mp_int *g, mp_int *x, mp_int *y) -{ - mp_int gx, xc, yc, u, v, A, B, C, D; - mp_int *clean[9]; - mp_err res; - int last = -1; - - if(mp_cmp_z(b) == 0) - return MP_RANGE; - - /* Initialize all these variables we need */ - if((res = mp_init(&u)) != MP_OKAY) goto CLEANUP; - clean[++last] = &u; - if((res = mp_init(&v)) != MP_OKAY) goto CLEANUP; - clean[++last] = &v; - if((res = mp_init(&gx)) != MP_OKAY) goto CLEANUP; - clean[++last] = &gx; - if((res = mp_init(&A)) != MP_OKAY) goto CLEANUP; - clean[++last] = &A; - if((res = mp_init(&B)) != MP_OKAY) goto CLEANUP; - clean[++last] = &B; - if((res = mp_init(&C)) != MP_OKAY) goto CLEANUP; - clean[++last] = &C; - if((res = mp_init(&D)) != MP_OKAY) goto CLEANUP; - clean[++last] = &D; - if((res = mp_init_copy(&xc, a)) != MP_OKAY) goto CLEANUP; - clean[++last] = &xc; - mp_abs(&xc, &xc); - if((res = mp_init_copy(&yc, b)) != MP_OKAY) goto CLEANUP; - clean[++last] = &yc; - mp_abs(&yc, &yc); - - mp_set(&gx, 1); - - /* Divide by two until at least one of them is even */ - while(mp_iseven(&xc) && mp_iseven(&yc)) { - s_mp_div_2(&xc); - s_mp_div_2(&yc); - if((res = s_mp_mul_2(&gx)) != MP_OKAY) - goto CLEANUP; - } - - mp_copy(&xc, &u); - mp_copy(&yc, &v); - mp_set(&A, 1); mp_set(&D, 1); - - /* Loop through binary GCD algorithm */ - for(;;) { - while(mp_iseven(&u)) { - s_mp_div_2(&u); - - if(mp_iseven(&A) && mp_iseven(&B)) { - s_mp_div_2(&A); s_mp_div_2(&B); - } else { - if((res = mp_add(&A, &yc, &A)) != MP_OKAY) goto CLEANUP; - s_mp_div_2(&A); - if((res = mp_sub(&B, &xc, &B)) != MP_OKAY) goto CLEANUP; - s_mp_div_2(&B); - } - } - - while(mp_iseven(&v)) { - s_mp_div_2(&v); - - if(mp_iseven(&C) && mp_iseven(&D)) { - s_mp_div_2(&C); s_mp_div_2(&D); - } else { - if((res = mp_add(&C, &yc, &C)) != MP_OKAY) goto CLEANUP; - s_mp_div_2(&C); - if((res = mp_sub(&D, &xc, &D)) != MP_OKAY) goto CLEANUP; - s_mp_div_2(&D); - } - } - - if(mp_cmp(&u, &v) >= 0) { - if((res = mp_sub(&u, &v, &u)) != MP_OKAY) goto CLEANUP; - if((res = mp_sub(&A, &C, &A)) != MP_OKAY) goto CLEANUP; - if((res = mp_sub(&B, &D, &B)) != MP_OKAY) goto CLEANUP; - - } else { - if((res = mp_sub(&v, &u, &v)) != MP_OKAY) goto CLEANUP; - if((res = mp_sub(&C, &A, &C)) != MP_OKAY) goto CLEANUP; - if((res = mp_sub(&D, &B, &D)) != MP_OKAY) goto CLEANUP; - - } - - /* If we're done, copy results to output */ - if(mp_cmp_z(&u) == 0) { - if(x) - if((res = mp_copy(&C, x)) != MP_OKAY) goto CLEANUP; - - if(y) - if((res = mp_copy(&D, y)) != MP_OKAY) goto CLEANUP; - - if(g) - if((res = mp_mul(&gx, &v, g)) != MP_OKAY) goto CLEANUP; - - break; - } - } - - CLEANUP: - while(last >= 0) - mp_clear(clean[last--]); - - return res; - -} /* end mp_xgcd() */ - -/* }}} */ - -/* {{{ mp_invmod(a, m, c) */ - -/* - mp_invmod(a, m, c) - - Compute c = a^-1 (mod m), if there is an inverse for a (mod m). - This is equivalent to the question of whether (a, m) = 1. If not, - MP_UNDEF is returned, and there is no inverse. - */ - -mp_err mp_invmod(mp_int *a, mp_int *m, mp_int *c) -{ - mp_int g, x; - mp_err res; - - ARGCHK(a && m && c, MP_BADARG); - - if(mp_cmp_z(a) == 0 || mp_cmp_z(m) == 0) - return MP_RANGE; - - if((res = mp_init(&g)) != MP_OKAY) - return res; - if((res = mp_init(&x)) != MP_OKAY) - goto X; - - if((res = mp_xgcd(a, m, &g, &x, NULL)) != MP_OKAY) - goto CLEANUP; - - if(mp_cmp_d(&g, 1) != MP_EQ) { - res = MP_UNDEF; - goto CLEANUP; - } - - res = mp_mod(&x, m, c); - SIGN(c) = SIGN(a); - -CLEANUP: - mp_clear(&x); -X: - mp_clear(&g); - - return res; - -} /* end mp_invmod() */ - -/* }}} */ -#endif /* if MP_NUMTH */ - -/* }}} */ - -/*------------------------------------------------------------------------*/ -/* {{{ mp_print(mp, ofp) */ - -#if MP_IOFUNC -/* - mp_print(mp, ofp) - - Print a textual representation of the given mp_int on the output - stream 'ofp'. Output is generated using the internal radix. - */ - -void mp_print(mp_int *mp, FILE *ofp) -{ - int ix; - - if(mp == NULL || ofp == NULL) - return; - - fputc((SIGN(mp) == MP_NEG) ? '-' : '+', ofp); - - for(ix = USED(mp) - 1; ix >= 0; ix--) { - fprintf(ofp, DIGIT_FMT, DIGIT(mp, ix)); - } - -} /* end mp_print() */ - -#endif /* if MP_IOFUNC */ - -/* }}} */ - -/*------------------------------------------------------------------------*/ -/* {{{ More I/O Functions */ - -/* {{{ mp_read_signed_bin(mp, str, len) */ - -/* - mp_read_signed_bin(mp, str, len) - - Read in a raw value (base 256) into the given mp_int - */ - -mp_err mp_read_signed_bin(mp_int *mp, unsigned char *str, int len) -{ - mp_err res; - - ARGCHK(mp != NULL && str != NULL && len > 0, MP_BADARG); - - if((res = mp_read_unsigned_bin(mp, str + 1, len - 1)) == MP_OKAY) { - /* Get sign from first byte */ - if(str[0]) - SIGN(mp) = MP_NEG; - else - SIGN(mp) = MP_ZPOS; - } - - return res; - -} /* end mp_read_signed_bin() */ - -/* }}} */ - -/* {{{ mp_signed_bin_size(mp) */ - -int mp_signed_bin_size(mp_int *mp) -{ - ARGCHK(mp != NULL, 0); - - return mp_unsigned_bin_size(mp) + 1; - -} /* end mp_signed_bin_size() */ - -/* }}} */ - -/* {{{ mp_to_signed_bin(mp, str) */ - -mp_err mp_to_signed_bin(mp_int *mp, unsigned char *str) -{ - ARGCHK(mp != NULL && str != NULL, MP_BADARG); - - /* Caller responsible for allocating enough memory (use mp_raw_size(mp)) */ - str[0] = (char)SIGN(mp); - - return mp_to_unsigned_bin(mp, str + 1); - -} /* end mp_to_signed_bin() */ - -/* }}} */ - -/* {{{ mp_read_unsigned_bin(mp, str, len) */ - -/* - mp_read_unsigned_bin(mp, str, len) - - Read in an unsigned value (base 256) into the given mp_int - */ - -mp_err mp_read_unsigned_bin(mp_int *mp, unsigned char *str, int len) -{ - int ix; - mp_err res; - - ARGCHK(mp != NULL && str != NULL && len > 0, MP_BADARG); - - mp_zero(mp); - - for(ix = 0; ix < len; ix++) { - if((res = s_mp_mul_2d(mp, CHAR_BIT)) != MP_OKAY) - return res; - - if((res = mp_add_d(mp, str[ix], mp)) != MP_OKAY) - return res; - } - - return MP_OKAY; - -} /* end mp_read_unsigned_bin() */ - -/* }}} */ - -/* {{{ mp_unsigned_bin_size(mp) */ - -int mp_unsigned_bin_size(mp_int *mp) -{ - mp_digit topdig; - int count; - - ARGCHK(mp != NULL, 0); - - /* Special case for the value zero */ - if(USED(mp) == 1 && DIGIT(mp, 0) == 0) - return 1; - - count = (USED(mp) - 1) * sizeof(mp_digit); - topdig = DIGIT(mp, USED(mp) - 1); - - while(topdig != 0) { - ++count; - topdig >>= CHAR_BIT; - } - - return count; - -} /* end mp_unsigned_bin_size() */ - -/* }}} */ - -/* {{{ mp_to_unsigned_bin(mp, str) */ - -mp_err mp_to_unsigned_bin(mp_int *mp, unsigned char *str) -{ - mp_digit *dp, *end, d; - unsigned char *spos; - - ARGCHK(mp != NULL && str != NULL, MP_BADARG); - - dp = DIGITS(mp); - end = dp + USED(mp) - 1; - spos = str; - - /* Special case for zero, quick test */ - if(dp == end && *dp == 0) { - *str = '\0'; - return MP_OKAY; - } - - /* Generate digits in reverse order */ - while(dp < end) { - unsigned int ix; - - d = *dp; - for(ix = 0; ix < sizeof(mp_digit); ++ix) { - *spos = d & UCHAR_MAX; - d >>= CHAR_BIT; - ++spos; - } - - ++dp; - } - - /* Now handle last digit specially, high order zeroes are not written */ - d = *end; - while(d != 0) { - *spos = d & UCHAR_MAX; - d >>= CHAR_BIT; - ++spos; - } - - /* Reverse everything to get digits in the correct order */ - while(--spos > str) { - unsigned char t = *str; - *str = *spos; - *spos = t; - - ++str; - } - - return MP_OKAY; - -} /* end mp_to_unsigned_bin() */ - -/* }}} */ - -/* {{{ mp_count_bits(mp) */ - -int mp_count_bits(mp_int *mp) -{ - int len; - mp_digit d; - - ARGCHK(mp != NULL, MP_BADARG); - - len = DIGIT_BIT * (USED(mp) - 1); - d = DIGIT(mp, USED(mp) - 1); - - while(d != 0) { - ++len; - d >>= 1; - } - - return len; - -} /* end mp_count_bits() */ - -/* }}} */ - -/* {{{ mp_read_radix(mp, str, radix) */ - -/* - mp_read_radix(mp, str, radix) - - Read an integer from the given string, and set mp to the resulting - value. The input is presumed to be in base 10. Leading non-digit - characters are ignored, and the function reads until a non-digit - character or the end of the string. - */ - -mp_err mp_read_radix(mp_int *mp, unsigned char *str, int radix) -{ - int ix = 0, val = 0; - mp_err res; - mp_sign sig = MP_ZPOS; - - ARGCHK(mp != NULL && str != NULL && radix >= 2 && radix <= MAX_RADIX, - MP_BADARG); - - mp_zero(mp); - - /* Skip leading non-digit characters until a digit or '-' or '+' */ - while(str[ix] && - (s_mp_tovalue(str[ix], radix) < 0) && - str[ix] != '-' && - str[ix] != '+') { - ++ix; - } - - if(str[ix] == '-') { - sig = MP_NEG; - ++ix; - } else if(str[ix] == '+') { - sig = MP_ZPOS; /* this is the default anyway... */ - ++ix; - } - - while((val = s_mp_tovalue(str[ix], radix)) >= 0) { - if((res = s_mp_mul_d(mp, radix)) != MP_OKAY) - return res; - if((res = s_mp_add_d(mp, val)) != MP_OKAY) - return res; - ++ix; - } - - if(s_mp_cmp_d(mp, 0) == MP_EQ) - SIGN(mp) = MP_ZPOS; - else - SIGN(mp) = sig; - - return MP_OKAY; - -} /* end mp_read_radix() */ - -/* }}} */ - -/* {{{ mp_radix_size(mp, radix) */ - -int mp_radix_size(mp_int *mp, int radix) -{ - int len; - ARGCHK(mp != NULL, 0); - - len = s_mp_outlen(mp_count_bits(mp), radix) + 1; /* for NUL terminator */ - - if(mp_cmp_z(mp) < 0) - ++len; /* for sign */ - - return len; - -} /* end mp_radix_size() */ - -/* }}} */ - -/* {{{ mp_value_radix_size(num, qty, radix) */ - -/* num = number of digits - qty = number of bits per digit - radix = target base - - Return the number of digits in the specified radix that would be - needed to express 'num' digits of 'qty' bits each. - */ -int mp_value_radix_size(int num, int qty, int radix) -{ - ARGCHK(num >= 0 && qty > 0 && radix >= 2 && radix <= MAX_RADIX, 0); - - return s_mp_outlen(num * qty, radix); - -} /* end mp_value_radix_size() */ - -/* }}} */ - -/* {{{ mp_toradix(mp, str, radix) */ - -mp_err mp_toradix(mp_int *mp, char *str, int radix) -{ - int ix, pos = 0; - - ARGCHK(mp != NULL && str != NULL, MP_BADARG); - ARGCHK(radix > 1 && radix <= MAX_RADIX, MP_RANGE); - - if(mp_cmp_z(mp) == MP_EQ) { - str[0] = '0'; - str[1] = '\0'; - } else { - mp_err res; - mp_int tmp; - mp_sign sgn; - mp_digit rem, rdx = (mp_digit)radix; - char ch; - - if((res = mp_init_copy(&tmp, mp)) != MP_OKAY) - return res; - - /* Save sign for later, and take absolute value */ - sgn = SIGN(&tmp); SIGN(&tmp) = MP_ZPOS; - - /* Generate output digits in reverse order */ - while(mp_cmp_z(&tmp) != 0) { - if((res = s_mp_div_d(&tmp, rdx, &rem)) != MP_OKAY) { - mp_clear(&tmp); - return res; - } - - /* Generate digits, use capital letters */ - ch = s_mp_todigit(rem, radix, 0); - - str[pos++] = ch; - } - - /* Add - sign if original value was negative */ - if(sgn == MP_NEG) - str[pos++] = '-'; - - /* Add trailing NUL to end the string */ - str[pos--] = '\0'; - - /* Reverse the digits and sign indicator */ - ix = 0; - while(ix < pos) { - char _tmp = str[ix]; - - str[ix] = str[pos]; - str[pos] = _tmp; - ++ix; - --pos; - } - - mp_clear(&tmp); - } - - return MP_OKAY; - -} /* end mp_toradix() */ - -/* }}} */ - -/* {{{ mp_char2value(ch, r) */ - -int mp_char2value(char ch, int r) -{ - return s_mp_tovalue(ch, r); - -} /* end mp_tovalue() */ - -/* }}} */ - -/* }}} */ - -/* {{{ mp_strerror(ec) */ - -/* - mp_strerror(ec) - - Return a string describing the meaning of error code 'ec'. The - string returned is allocated in static memory, so the caller should - not attempt to modify or free the memory associated with this - string. - */ -const char *mp_strerror(mp_err ec) -{ - int aec = (ec < 0) ? -ec : ec; - - /* Code values are negative, so the senses of these comparisons - are accurate */ - if(ec < MP_LAST_CODE || ec > MP_OKAY) { - return mp_err_string[0]; /* unknown error code */ - } else { - return mp_err_string[aec + 1]; - } - -} /* end mp_strerror() */ - -/* }}} */ - -/*========================================================================*/ -/*------------------------------------------------------------------------*/ -/* Static function definitions (internal use only) */ - -/* {{{ Memory management */ - -/* {{{ s_mp_grow(mp, min) */ - -/* Make sure there are at least 'min' digits allocated to mp */ -mp_err s_mp_grow(mp_int *mp, mp_size min) -{ - if(min > ALLOC(mp)) { - mp_digit *tmp; - - /* Set min to next nearest default precision block size */ - min = ((min + (s_mp_defprec - 1)) / s_mp_defprec) * s_mp_defprec; - - if((tmp = s_mp_alloc(min, sizeof(mp_digit))) == NULL) - return MP_MEM; - - s_mp_copy(DIGITS(mp), tmp, USED(mp)); - -#if MP_CRYPTO - s_mp_setz(DIGITS(mp), ALLOC(mp)); -#endif - s_mp_free(DIGITS(mp)); - DIGITS(mp) = tmp; - ALLOC(mp) = min; - } - - return MP_OKAY; - -} /* end s_mp_grow() */ - -/* }}} */ - -/* {{{ s_mp_pad(mp, min) */ - -/* Make sure the used size of mp is at least 'min', growing if needed */ -mp_err s_mp_pad(mp_int *mp, mp_size min) -{ - if(min > USED(mp)) { - mp_err res; - - /* Make sure there is room to increase precision */ - if(min > ALLOC(mp) && (res = s_mp_grow(mp, min)) != MP_OKAY) - return res; - - /* Increase precision; should already be 0-filled */ - USED(mp) = min; - } - - return MP_OKAY; - -} /* end s_mp_pad() */ - -/* }}} */ - -/* {{{ s_mp_setz(dp, count) */ - -#if MP_MACRO == 0 -/* Set 'count' digits pointed to by dp to be zeroes */ -void s_mp_setz(mp_digit *dp, mp_size count) -{ -#if MP_MEMSET == 0 - int ix; - - for(ix = 0; ix < count; ix++) - dp[ix] = 0; -#else - memset(dp, 0, count * sizeof(mp_digit)); -#endif - -} /* end s_mp_setz() */ -#endif - -/* }}} */ - -/* {{{ s_mp_copy(sp, dp, count) */ - -#if MP_MACRO == 0 -/* Copy 'count' digits from sp to dp */ -void s_mp_copy(mp_digit *sp, mp_digit *dp, mp_size count) -{ -#if MP_MEMCPY == 0 - int ix; - - for(ix = 0; ix < count; ix++) - dp[ix] = sp[ix]; -#else - memcpy(dp, sp, count * sizeof(mp_digit)); -#endif - -} /* end s_mp_copy() */ -#endif - -/* }}} */ - -/* {{{ s_mp_alloc(nb, ni) */ - -#if MP_MACRO == 0 -/* Allocate ni records of nb bytes each, and return a pointer to that */ -void *s_mp_alloc(size_t nb, size_t ni) -{ - return calloc(nb, ni); - -} /* end s_mp_alloc() */ -#endif - -/* }}} */ - -/* {{{ s_mp_free(ptr) */ - -#if MP_MACRO == 0 -/* Free the memory pointed to by ptr */ -void s_mp_free(void *ptr) -{ - if(ptr) - free(ptr); - -} /* end s_mp_free() */ -#endif - -/* }}} */ - -/* {{{ s_mp_clamp(mp) */ - -/* Remove leading zeroes from the given value */ -void s_mp_clamp(mp_int *mp) -{ - mp_size du = USED(mp); - mp_digit *zp = DIGITS(mp) + du - 1; - - while(du > 1 && !*zp--) - --du; - - USED(mp) = du; - -} /* end s_mp_clamp() */ - - -/* }}} */ - -/* {{{ s_mp_exch(a, b) */ - -/* Exchange the data for a and b; (b, a) = (a, b) */ -void s_mp_exch(mp_int *a, mp_int *b) -{ - mp_int tmp; - - tmp = *a; - *a = *b; - *b = tmp; - -} /* end s_mp_exch() */ - -/* }}} */ - -/* }}} */ - -/* {{{ Arithmetic helpers */ - -/* {{{ s_mp_lshd(mp, p) */ - -/* - Shift mp leftward by p digits, growing if needed, and zero-filling - the in-shifted digits at the right end. This is a convenient - alternative to multiplication by powers of the radix - */ - -mp_err s_mp_lshd(mp_int *mp, mp_size p) -{ - mp_err res; - mp_size pos; - mp_digit *dp; - int ix; - - if(p == 0) - return MP_OKAY; - - if((res = s_mp_pad(mp, USED(mp) + p)) != MP_OKAY) - return res; - - pos = USED(mp) - 1; - dp = DIGITS(mp); - - /* Shift all the significant figures over as needed */ - for(ix = pos - p; ix >= 0; ix--) - dp[ix + p] = dp[ix]; - - /* Fill the bottom digits with zeroes */ - for(ix = 0; (unsigned)ix < p; ix++) - dp[ix] = 0; - - return MP_OKAY; - -} /* end s_mp_lshd() */ - -/* }}} */ - -/* {{{ s_mp_rshd(mp, p) */ - -/* - Shift mp rightward by p digits. Maintains the invariant that - digits above the precision are all zero. Digits shifted off the - end are lost. Cannot fail. - */ - -void s_mp_rshd(mp_int *mp, mp_size p) -{ - mp_size ix; - mp_digit *dp; - - if(p == 0) - return; - - /* Shortcut when all digits are to be shifted off */ - if(p >= USED(mp)) { - s_mp_setz(DIGITS(mp), ALLOC(mp)); - USED(mp) = 1; - SIGN(mp) = MP_ZPOS; - return; - } - - /* Shift all the significant figures over as needed */ - dp = DIGITS(mp); - for(ix = p; ix < USED(mp); ix++) - dp[ix - p] = dp[ix]; - - /* Fill the top digits with zeroes */ - ix -= p; - while(ix < USED(mp)) - dp[ix++] = 0; - - /* Strip off any leading zeroes */ - s_mp_clamp(mp); - -} /* end s_mp_rshd() */ - -/* }}} */ - -/* {{{ s_mp_div_2(mp) */ - -/* Divide by two -- take advantage of radix properties to do it fast */ -void s_mp_div_2(mp_int *mp) -{ - s_mp_div_2d(mp, 1); - -} /* end s_mp_div_2() */ - -/* }}} */ - -/* {{{ s_mp_mul_2(mp) */ - -mp_err s_mp_mul_2(mp_int *mp) -{ - unsigned int ix; - mp_digit kin = 0, kout, *dp = DIGITS(mp); - mp_err res; - - /* Shift digits leftward by 1 bit */ - for(ix = 0; ix < USED(mp); ix++) { - kout = (dp[ix] >> (DIGIT_BIT - 1)) & 1; - dp[ix] = (dp[ix] << 1) | kin; - - kin = kout; - } - - /* Deal with rollover from last digit */ - if(kin) { - if(ix >= ALLOC(mp)) { - if((res = s_mp_grow(mp, ALLOC(mp) + 1)) != MP_OKAY) - return res; - dp = DIGITS(mp); - } - - dp[ix] = kin; - USED(mp) += 1; - } - - return MP_OKAY; - -} /* end s_mp_mul_2() */ - -/* }}} */ - -/* {{{ s_mp_mod_2d(mp, d) */ - -/* - Remainder the integer by 2^d, where d is a number of bits. This - amounts to a bitwise AND of the value, and does not require the full - division code - */ -void s_mp_mod_2d(mp_int *mp, mp_digit d) -{ - unsigned int ndig = (d / DIGIT_BIT), nbit = (d % DIGIT_BIT); - unsigned int ix; - mp_digit dmask, *dp = DIGITS(mp); - - if(ndig >= USED(mp)) - return; - - /* Flush all the bits above 2^d in its digit */ - dmask = (1 << nbit) - 1; - dp[ndig] &= dmask; - - /* Flush all digits above the one with 2^d in it */ - for(ix = ndig + 1; ix < USED(mp); ix++) - dp[ix] = 0; - - s_mp_clamp(mp); - -} /* end s_mp_mod_2d() */ - -/* }}} */ - -/* {{{ s_mp_mul_2d(mp, d) */ - -/* - Multiply by the integer 2^d, where d is a number of bits. This - amounts to a bitwise shift of the value, and does not require the - full multiplication code. - */ -mp_err s_mp_mul_2d(mp_int *mp, mp_digit d) -{ - mp_err res; - mp_digit save, next, mask, *dp; - mp_size used; - unsigned int ix; - - if((res = s_mp_lshd(mp, d / DIGIT_BIT)) != MP_OKAY) - return res; - - dp = DIGITS(mp); used = USED(mp); - d %= DIGIT_BIT; - - mask = (1 << d) - 1; - - /* If the shift requires another digit, make sure we've got one to - work with */ - if((dp[used - 1] >> (DIGIT_BIT - d)) & mask) { - if((res = s_mp_grow(mp, used + 1)) != MP_OKAY) - return res; - dp = DIGITS(mp); - } - - /* Do the shifting... */ - save = 0; - for(ix = 0; ix < used; ix++) { - next = (dp[ix] >> (DIGIT_BIT - d)) & mask; - dp[ix] = (dp[ix] << d) | save; - save = next; - } - - /* If, at this point, we have a nonzero carryout into the next - digit, we'll increase the size by one digit, and store it... - */ - if(save) { - dp[used] = save; - USED(mp) += 1; - } - - s_mp_clamp(mp); - return MP_OKAY; - -} /* end s_mp_mul_2d() */ - -/* }}} */ - -/* {{{ s_mp_div_2d(mp, d) */ - -/* - Divide the integer by 2^d, where d is a number of bits. This - amounts to a bitwise shift of the value, and does not require the - full division code (used in Barrett reduction, see below) - */ -void s_mp_div_2d(mp_int *mp, mp_digit d) -{ - int ix; - mp_digit save, next, mask, *dp = DIGITS(mp); - - s_mp_rshd(mp, d / DIGIT_BIT); - d %= DIGIT_BIT; - - mask = (1 << d) - 1; - - save = 0; - for(ix = USED(mp) - 1; ix >= 0; ix--) { - next = dp[ix] & mask; - dp[ix] = (dp[ix] >> d) | (save << (DIGIT_BIT - d)); - save = next; - } - - s_mp_clamp(mp); - -} /* end s_mp_div_2d() */ - -/* }}} */ - -/* {{{ s_mp_norm(a, b) */ - -/* - s_mp_norm(a, b) - - Normalize a and b for division, where b is the divisor. In order - that we might make good guesses for quotient digits, we want the - leading digit of b to be at least half the radix, which we - accomplish by multiplying a and b by a constant. This constant is - returned (so that it can be divided back out of the remainder at the - end of the division process). - - We multiply by the smallest power of 2 that gives us a leading digit - at least half the radix. By choosing a power of 2, we simplify the - multiplication and division steps to simple shifts. - */ -mp_digit s_mp_norm(mp_int *a, mp_int *b) -{ - mp_digit t, d = 0; - - t = DIGIT(b, USED(b) - 1); - while(t < (RADIX / 2)) { - t <<= 1; - ++d; - } - - if(d != 0) { - s_mp_mul_2d(a, d); - s_mp_mul_2d(b, d); - } - - return d; - -} /* end s_mp_norm() */ - -/* }}} */ - -/* }}} */ - -/* {{{ Primitive digit arithmetic */ - -/* {{{ s_mp_add_d(mp, d) */ - -/* Add d to |mp| in place */ -mp_err s_mp_add_d(mp_int *mp, mp_digit d) /* unsigned digit addition */ -{ - mp_word w, k = 0; - mp_size ix = 1, used = USED(mp); - mp_digit *dp = DIGITS(mp); - - w = dp[0] + d; - dp[0] = ACCUM(w); - k = CARRYOUT(w); - - while(ix < used && k) { - w = dp[ix] + k; - dp[ix] = ACCUM(w); - k = CARRYOUT(w); - ++ix; - } - - if(k != 0) { - mp_err res; - - if((res = s_mp_pad(mp, USED(mp) + 1)) != MP_OKAY) - return res; - - DIGIT(mp, ix) = k; - } - - return MP_OKAY; - -} /* end s_mp_add_d() */ - -/* }}} */ - -/* {{{ s_mp_sub_d(mp, d) */ - -/* Subtract d from |mp| in place, assumes |mp| > d */ -mp_err s_mp_sub_d(mp_int *mp, mp_digit d) /* unsigned digit subtract */ -{ - mp_word w, b = 0; - mp_size ix = 1, used = USED(mp); - mp_digit *dp = DIGITS(mp); - - /* Compute initial subtraction */ - w = (RADIX + dp[0]) - d; - b = CARRYOUT(w) ? 0 : 1; - dp[0] = ACCUM(w); - - /* Propagate borrows leftward */ - while(b && ix < used) { - w = (RADIX + dp[ix]) - b; - b = CARRYOUT(w) ? 0 : 1; - dp[ix] = ACCUM(w); - ++ix; - } - - /* Remove leading zeroes */ - s_mp_clamp(mp); - - /* If we have a borrow out, it's a violation of the input invariant */ - if(b) - return MP_RANGE; - else - return MP_OKAY; - -} /* end s_mp_sub_d() */ - -/* }}} */ - -/* {{{ s_mp_mul_d(a, d) */ - -/* Compute a = a * d, single digit multiplication */ -mp_err s_mp_mul_d(mp_int *a, mp_digit d) -{ - mp_word w, k = 0; - mp_size ix, max; - mp_err res; - mp_digit *dp = DIGITS(a); - - /* - Single-digit multiplication will increase the precision of the - output by at most one digit. However, we can detect when this - will happen -- if the high-order digit of a, times d, gives a - two-digit result, then the precision of the result will increase; - otherwise it won't. We use this fact to avoid calling s_mp_pad() - unless absolutely necessary. - */ - max = USED(a); - w = dp[max - 1] * d; - if(CARRYOUT(w) != 0) { - if((res = s_mp_pad(a, max + 1)) != MP_OKAY) - return res; - dp = DIGITS(a); - } - - for(ix = 0; ix < max; ix++) { - w = (dp[ix] * d) + k; - dp[ix] = ACCUM(w); - k = CARRYOUT(w); - } - - /* If there is a precision increase, take care of it here; the above - test guarantees we have enough storage to do this safely. - */ - if(k) { - dp[max] = k; - USED(a) = max + 1; - } - - s_mp_clamp(a); - - return MP_OKAY; - -} /* end s_mp_mul_d() */ - -/* }}} */ - -/* {{{ s_mp_div_d(mp, d, r) */ - -/* - s_mp_div_d(mp, d, r) - - Compute the quotient mp = mp / d and remainder r = mp mod d, for a - single digit d. If r is null, the remainder will be discarded. - */ - -mp_err s_mp_div_d(mp_int *mp, mp_digit d, mp_digit *r) -{ - mp_word w = 0, t; - mp_int quot; - mp_err res; - mp_digit *dp = DIGITS(mp), *qp; - int ix; - - if(d == 0) - return MP_RANGE; - - /* Make room for the quotient */ - if((res = mp_init_size(", USED(mp))) != MP_OKAY) - return res; - - USED(") = USED(mp); /* so clamping will work below */ - qp = DIGITS("); - - /* Divide without subtraction */ - for(ix = USED(mp) - 1; ix >= 0; ix--) { - w = (w << DIGIT_BIT) | dp[ix]; - - if(w >= d) { - t = w / d; - w = w % d; - } else { - t = 0; - } - - qp[ix] = t; - } - - /* Deliver the remainder, if desired */ - if(r) - *r = w; - - s_mp_clamp("); - mp_exch(", mp); - mp_clear("); - - return MP_OKAY; - -} /* end s_mp_div_d() */ - -/* }}} */ - -/* }}} */ - -/* {{{ Primitive full arithmetic */ - -/* {{{ s_mp_add(a, b) */ - -/* Compute a = |a| + |b| */ -mp_err s_mp_add(mp_int *a, mp_int *b) /* magnitude addition */ -{ - mp_word w = 0; - mp_digit *pa, *pb; - mp_size ix, used = USED(b); - mp_err res; - - /* Make sure a has enough precision for the output value */ - if((used > USED(a)) && (res = s_mp_pad(a, used)) != MP_OKAY) - return res; - - /* - Add up all digits up to the precision of b. If b had initially - the same precision as a, or greater, we took care of it by the - padding step above, so there is no problem. If b had initially - less precision, we'll have to make sure the carry out is duly - propagated upward among the higher-order digits of the sum. - */ - pa = DIGITS(a); - pb = DIGITS(b); - for(ix = 0; ix < used; ++ix) { - w += *pa + *pb++; - *pa++ = ACCUM(w); - w = CARRYOUT(w); - } - - /* If we run out of 'b' digits before we're actually done, make - sure the carries get propagated upward... - */ - used = USED(a); - while(w && ix < used) { - w += *pa; - *pa++ = ACCUM(w); - w = CARRYOUT(w); - ++ix; - } - - /* If there's an overall carry out, increase precision and include - it. We could have done this initially, but why touch the memory - allocator unless we're sure we have to? - */ - if(w) { - if((res = s_mp_pad(a, used + 1)) != MP_OKAY) - return res; - - DIGIT(a, ix) = w; /* pa may not be valid after s_mp_pad() call */ - } - - return MP_OKAY; - -} /* end s_mp_add() */ - -/* }}} */ - -/* {{{ s_mp_sub(a, b) */ - -/* Compute a = |a| - |b|, assumes |a| >= |b| */ -mp_err s_mp_sub(mp_int *a, mp_int *b) /* magnitude subtract */ -{ - mp_word w = 0; - mp_digit *pa, *pb; - mp_size ix, used = USED(b); - - /* - Subtract and propagate borrow. Up to the precision of b, this - accounts for the digits of b; after that, we just make sure the - carries get to the right place. This saves having to pad b out to - the precision of a just to make the loops work right... - */ - pa = DIGITS(a); - pb = DIGITS(b); - - for(ix = 0; ix < used; ++ix) { - w = (RADIX + *pa) - w - *pb++; - *pa++ = ACCUM(w); - w = CARRYOUT(w) ? 0 : 1; - } - - used = USED(a); - while(ix < used) { - w = RADIX + *pa - w; - *pa++ = ACCUM(w); - w = CARRYOUT(w) ? 0 : 1; - ++ix; - } - - /* Clobber any leading zeroes we created */ - s_mp_clamp(a); - - /* - If there was a borrow out, then |b| > |a| in violation - of our input invariant. We've already done the work, - but we'll at least complain about it... - */ - if(w) - return MP_RANGE; - else - return MP_OKAY; - -} /* end s_mp_sub() */ - -/* }}} */ - -mp_err s_mp_reduce(mp_int *x, mp_int *m, mp_int *mu) -{ - mp_int q; - mp_err res; - mp_size um = USED(m); - - if((res = mp_init_copy(&q, x)) != MP_OKAY) - return res; - - s_mp_rshd(&q, um - 1); /* q1 = x / b^(k-1) */ - s_mp_mul(&q, mu); /* q2 = q1 * mu */ - s_mp_rshd(&q, um + 1); /* q3 = q2 / b^(k+1) */ - - /* x = x mod b^(k+1), quick (no division) */ - s_mp_mod_2d(x, (mp_digit)(DIGIT_BIT * (um + 1))); - - /* q = q * m mod b^(k+1), quick (no division), uses the short multiplier */ -#ifndef SHRT_MUL - s_mp_mul(&q, m); - s_mp_mod_2d(&q, (mp_digit)(DIGIT_BIT * (um + 1))); -#else - s_mp_mul_dig(&q, m, um + 1); -#endif - - /* x = x - q */ - if((res = mp_sub(x, &q, x)) != MP_OKAY) - goto CLEANUP; - - /* If x < 0, add b^(k+1) to it */ - if(mp_cmp_z(x) < 0) { - mp_set(&q, 1); - if((res = s_mp_lshd(&q, um + 1)) != MP_OKAY) - goto CLEANUP; - if((res = mp_add(x, &q, x)) != MP_OKAY) - goto CLEANUP; - } - - /* Back off if it's too big */ - while(mp_cmp(x, m) >= 0) { - if((res = s_mp_sub(x, m)) != MP_OKAY) - break; - } - - CLEANUP: - mp_clear(&q); - - return res; - -} /* end s_mp_reduce() */ - - - -/* {{{ s_mp_mul(a, b) */ - -/* Compute a = |a| * |b| */ -mp_err s_mp_mul(mp_int *a, mp_int *b) -{ - mp_word w, k = 0; - mp_int tmp; - mp_err res; - mp_size ix, jx, ua = USED(a), ub = USED(b); - mp_digit *pa, *pb, *pt, *pbt; - - if((res = mp_init_size(&tmp, ua + ub)) != MP_OKAY) - return res; - - /* This has the effect of left-padding with zeroes... */ - USED(&tmp) = ua + ub; - - /* We're going to need the base value each iteration */ - pbt = DIGITS(&tmp); - - /* Outer loop: Digits of b */ - - pb = DIGITS(b); - for(ix = 0; ix < ub; ++ix, ++pb) { - if(*pb == 0) - continue; - - /* Inner product: Digits of a */ - pa = DIGITS(a); - for(jx = 0; jx < ua; ++jx, ++pa) { - pt = pbt + ix + jx; - w = *pb * *pa + k + *pt; - *pt = ACCUM(w); - k = CARRYOUT(w); - } - - pbt[ix + jx] = k; - k = 0; - } - - s_mp_clamp(&tmp); - s_mp_exch(&tmp, a); - - mp_clear(&tmp); - - return MP_OKAY; - -} /* end s_mp_mul() */ - -/* }}} */ - -/* {{{ s_mp_kmul(a, b, out, len) */ - -#if 0 -void s_mp_kmul(mp_digit *a, mp_digit *b, mp_digit *out, mp_size len) -{ - mp_word w, k = 0; - mp_size ix, jx; - mp_digit *pa, *pt; - - for(ix = 0; ix < len; ++ix, ++b) { - if(*b == 0) - continue; - - pa = a; - for(jx = 0; jx < len; ++jx, ++pa) { - pt = out + ix + jx; - w = *b * *pa + k + *pt; - *pt = ACCUM(w); - k = CARRYOUT(w); - } - - out[ix + jx] = k; - k = 0; - } - -} /* end s_mp_kmul() */ -#endif - -/* }}} */ - -/* {{{ s_mp_sqr(a) */ - -/* - Computes the square of a, in place. This can be done more - efficiently than a general multiplication, because many of the - computation steps are redundant when squaring. The inner product - step is a bit more complicated, but we save a fair number of - iterations of the multiplication loop. - */ -#if MP_SQUARE -mp_err s_mp_sqr(mp_int *a) -{ - mp_word w, k = 0; - mp_int tmp; - mp_err res; - mp_size ix, jx, kx, used = USED(a); - mp_digit *pa1, *pa2, *pt, *pbt; - - if((res = mp_init_size(&tmp, 2 * used)) != MP_OKAY) - return res; - - /* Left-pad with zeroes */ - USED(&tmp) = 2 * used; - - /* We need the base value each time through the loop */ - pbt = DIGITS(&tmp); - - pa1 = DIGITS(a); - for(ix = 0; ix < used; ++ix, ++pa1) { - if(*pa1 == 0) - continue; - - w = DIGIT(&tmp, ix + ix) + (*pa1 * *pa1); - - pbt[ix + ix] = ACCUM(w); - k = CARRYOUT(w); - - /* - The inner product is computed as: - - (C, S) = t[i,j] + 2 a[i] a[j] + C - - This can overflow what can be represented in an mp_word, and - since C arithmetic does not provide any way to check for - overflow, we have to check explicitly for overflow conditions - before they happen. - */ - for(jx = ix + 1, pa2 = DIGITS(a) + jx; jx < used; ++jx, ++pa2) { - mp_word u = 0, v; - - /* Store this in a temporary to avoid indirections later */ - pt = pbt + ix + jx; - - /* Compute the multiplicative step */ - w = *pa1 * *pa2; - - /* If w is more than half MP_WORD_MAX, the doubling will - overflow, and we need to record a carry out into the next - word */ - u = (w >> (MP_WORD_BIT - 1)) & 1; - - /* Double what we've got, overflow will be ignored as defined - for C arithmetic (we've already noted if it is to occur) - */ - w *= 2; - - /* Compute the additive step */ - v = *pt + k; - - /* If we do not already have an overflow carry, check to see - if the addition will cause one, and set the carry out if so - */ - u |= ((MP_WORD_MAX - v) < w); - - /* Add in the rest, again ignoring overflow */ - w += v; - - /* Set the i,j digit of the output */ - *pt = ACCUM(w); - - /* Save carry information for the next iteration of the loop. - This is why k must be an mp_word, instead of an mp_digit */ - k = CARRYOUT(w) | (u << DIGIT_BIT); - - } /* for(jx ...) */ - - /* Set the last digit in the cycle and reset the carry */ - k = DIGIT(&tmp, ix + jx) + k; - pbt[ix + jx] = ACCUM(k); - k = CARRYOUT(k); - - /* If we are carrying out, propagate the carry to the next digit - in the output. This may cascade, so we have to be somewhat - circumspect -- but we will have enough precision in the output - that we won't overflow - */ - kx = 1; - while(k) { - k = pbt[ix + jx + kx] + 1; - pbt[ix + jx + kx] = ACCUM(k); - k = CARRYOUT(k); - ++kx; - } - } /* for(ix ...) */ - - s_mp_clamp(&tmp); - s_mp_exch(&tmp, a); - - mp_clear(&tmp); - - return MP_OKAY; - -} /* end s_mp_sqr() */ -#endif - -/* }}} */ - -/* {{{ s_mp_div(a, b) */ - -/* - s_mp_div(a, b) - - Compute a = a / b and b = a mod b. Assumes b > a. - */ - -mp_err s_mp_div(mp_int *a, mp_int *b) -{ - mp_int quot, rem, t; - mp_word q; - mp_err res; - mp_digit d; - int ix; - - if(mp_cmp_z(b) == 0) - return MP_RANGE; - - /* Shortcut if b is power of two */ - if((ix = s_mp_ispow2(b)) >= 0) { - mp_copy(a, b); /* need this for remainder */ - s_mp_div_2d(a, (mp_digit)ix); - s_mp_mod_2d(b, (mp_digit)ix); - - return MP_OKAY; - } - - /* Allocate space to store the quotient */ - if((res = mp_init_size(", USED(a))) != MP_OKAY) - return res; - - /* A working temporary for division */ - if((res = mp_init_size(&t, USED(a))) != MP_OKAY) - goto T; - - /* Allocate space for the remainder */ - if((res = mp_init_size(&rem, USED(a))) != MP_OKAY) - goto REM; - - /* Normalize to optimize guessing */ - d = s_mp_norm(a, b); - - /* Perform the division itself...woo! */ - ix = USED(a) - 1; - - while(ix >= 0) { - /* Find a partial substring of a which is at least b */ - while(s_mp_cmp(&rem, b) < 0 && ix >= 0) { - if((res = s_mp_lshd(&rem, 1)) != MP_OKAY) - goto CLEANUP; - - if((res = s_mp_lshd(", 1)) != MP_OKAY) - goto CLEANUP; - - DIGIT(&rem, 0) = DIGIT(a, ix); - s_mp_clamp(&rem); - --ix; - } - - /* If we didn't find one, we're finished dividing */ - if(s_mp_cmp(&rem, b) < 0) - break; - - /* Compute a guess for the next quotient digit */ - q = DIGIT(&rem, USED(&rem) - 1); - if(q <= DIGIT(b, USED(b) - 1) && USED(&rem) > 1) - q = (q << DIGIT_BIT) | DIGIT(&rem, USED(&rem) - 2); - - q /= DIGIT(b, USED(b) - 1); - - /* The guess can be as much as RADIX + 1 */ - if(q >= RADIX) - q = RADIX - 1; - - /* See what that multiplies out to */ - mp_copy(b, &t); - if((res = s_mp_mul_d(&t, q)) != MP_OKAY) - goto CLEANUP; - - /* - If it's too big, back it off. We should not have to do this - more than once, or, in rare cases, twice. Knuth describes a - method by which this could be reduced to a maximum of once, but - I didn't implement that here. - */ - while(s_mp_cmp(&t, &rem) > 0) { - --q; - s_mp_sub(&t, b); - } - - /* At this point, q should be the right next digit */ - if((res = s_mp_sub(&rem, &t)) != MP_OKAY) - goto CLEANUP; - - /* - Include the digit in the quotient. We allocated enough memory - for any quotient we could ever possibly get, so we should not - have to check for failures here - */ - DIGIT(", 0) = q; - } - - /* Denormalize remainder */ - if(d != 0) - s_mp_div_2d(&rem, d); - - s_mp_clamp("); - s_mp_clamp(&rem); - - /* Copy quotient back to output */ - s_mp_exch(", a); - - /* Copy remainder back to output */ - s_mp_exch(&rem, b); - -CLEANUP: - mp_clear(&rem); -REM: - mp_clear(&t); -T: - mp_clear("); - - return res; - -} /* end s_mp_div() */ - -/* }}} */ - -/* {{{ s_mp_2expt(a, k) */ - -mp_err s_mp_2expt(mp_int *a, mp_digit k) -{ - mp_err res; - mp_size dig, bit; - - dig = k / DIGIT_BIT; - bit = k % DIGIT_BIT; - - mp_zero(a); - if((res = s_mp_pad(a, dig + 1)) != MP_OKAY) - return res; - - DIGIT(a, dig) |= (1 << bit); - - return MP_OKAY; - -} /* end s_mp_2expt() */ - -/* }}} */ - - -/* }}} */ - -/* }}} */ - -/* {{{ Primitive comparisons */ - -/* {{{ s_mp_cmp(a, b) */ - -/* Compare |a| <=> |b|, return 0 if equal, <0 if a<b, >0 if a>b */ -int s_mp_cmp(mp_int *a, mp_int *b) -{ - mp_size ua = USED(a), ub = USED(b); - - if(ua > ub) - return MP_GT; - else if(ua < ub) - return MP_LT; - else { - int ix = ua - 1; - mp_digit *ap = DIGITS(a) + ix, *bp = DIGITS(b) + ix; - - while(ix >= 0) { - if(*ap > *bp) - return MP_GT; - else if(*ap < *bp) - return MP_LT; - - --ap; --bp; --ix; - } - - return MP_EQ; - } - -} /* end s_mp_cmp() */ - -/* }}} */ - -/* {{{ s_mp_cmp_d(a, d) */ - -/* Compare |a| <=> d, return 0 if equal, <0 if a<d, >0 if a>d */ -int s_mp_cmp_d(mp_int *a, mp_digit d) -{ - mp_size ua = USED(a); - mp_digit *ap = DIGITS(a); - - if(ua > 1) - return MP_GT; - - if(*ap < d) - return MP_LT; - else if(*ap > d) - return MP_GT; - else - return MP_EQ; - -} /* end s_mp_cmp_d() */ - -/* }}} */ - -/* {{{ s_mp_ispow2(v) */ - -/* - Returns -1 if the value is not a power of two; otherwise, it returns - k such that v = 2^k, i.e. lg(v). - */ -int s_mp_ispow2(mp_int *v) -{ - mp_digit d, *dp; - mp_size uv = USED(v); - int extra = 0, ix; - - d = DIGIT(v, uv - 1); /* most significant digit of v */ - - while(d && ((d & 1) == 0)) { - d >>= 1; - ++extra; - } - - if(d == 1) { - ix = uv - 2; - dp = DIGITS(v) + ix; - - while(ix >= 0) { - if(*dp) - return -1; /* not a power of two */ - - --dp; --ix; - } - - return ((uv - 1) * DIGIT_BIT) + extra; - } - - return -1; - -} /* end s_mp_ispow2() */ - -/* }}} */ - -/* {{{ s_mp_ispow2d(d) */ - -int s_mp_ispow2d(mp_digit d) -{ - int pow = 0; - - while((d & 1) == 0) { - ++pow; d >>= 1; - } - - if(d == 1) - return pow; - - return -1; - -} /* end s_mp_ispow2d() */ - -/* }}} */ - -/* }}} */ - -/* {{{ Primitive I/O helpers */ - -/* {{{ s_mp_tovalue(ch, r) */ - -/* - Convert the given character to its digit value, in the given radix. - If the given character is not understood in the given radix, -1 is - returned. Otherwise the digit's numeric value is returned. - - The results will be odd if you use a radix < 2 or > 62, you are - expected to know what you're up to. - */ -int s_mp_tovalue(char ch, int r) -{ - int val, xch; - - if(r > 36) - xch = ch; - else - xch = toupper(ch); - - if(isdigit(xch)) - val = xch - '0'; - else if(isupper(xch)) - val = xch - 'A' + 10; - else if(islower(xch)) - val = xch - 'a' + 36; - else if(xch == '+') - val = 62; - else if(xch == '/') - val = 63; - else - return -1; - - if(val < 0 || val >= r) - return -1; - - return val; - -} /* end s_mp_tovalue() */ - -/* }}} */ - -/* {{{ s_mp_todigit(val, r, low) */ - -/* - Convert val to a radix-r digit, if possible. If val is out of range - for r, returns zero. Otherwise, returns an ASCII character denoting - the value in the given radix. - - The results may be odd if you use a radix < 2 or > 64, you are - expected to know what you're doing. - */ - -char s_mp_todigit(int val, int r, int low) -{ - char ch; - - if(val < 0 || val >= r) - return 0; - - ch = s_dmap_1[val]; - - if(r <= 36 && low) - ch = tolower(ch); - - return ch; - -} /* end s_mp_todigit() */ - -/* }}} */ - -/* {{{ s_mp_outlen(bits, radix) */ - -/* - Return an estimate for how long a string is needed to hold a radix - r representation of a number with 'bits' significant bits. - - Does not include space for a sign or a NUL terminator. - */ -int s_mp_outlen(int bits, int r) -{ - return (int)((double)bits * LOG_V_2(r)); - -} /* end s_mp_outlen() */ - -/* }}} */ - -/* }}} */ - -/*------------------------------------------------------------------------*/ -/* HERE THERE BE DRAGONS */ -/* crc==4242132123, version==2, Sat Feb 02 06:43:52 2002 */ - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ diff --git a/libtommath/mtest/mpi.h b/libtommath/mtest/mpi.h deleted file mode 100644 index 5accb52..0000000 --- a/libtommath/mtest/mpi.h +++ /dev/null @@ -1,231 +0,0 @@ -/* - mpi.h - - by Michael J. Fromberger <sting@linguist.dartmouth.edu> - Copyright (C) 1998 Michael J. Fromberger, All Rights Reserved - - Arbitrary precision integer arithmetic library - - $Id$ - */ - -#ifndef _H_MPI_ -#define _H_MPI_ - -#include "mpi-config.h" - -#define MP_LT -1 -#define MP_EQ 0 -#define MP_GT 1 - -#if MP_DEBUG -#undef MP_IOFUNC -#define MP_IOFUNC 1 -#endif - -#if MP_IOFUNC -#include <stdio.h> -#include <ctype.h> -#endif - -#include <limits.h> - -#define MP_NEG 1 -#define MP_ZPOS 0 - -/* Included for compatibility... */ -#define NEG MP_NEG -#define ZPOS MP_ZPOS - -#define MP_OKAY 0 /* no error, all is well */ -#define MP_YES 0 /* yes (boolean result) */ -#define MP_NO -1 /* no (boolean result) */ -#define MP_MEM -2 /* out of memory */ -#define MP_RANGE -3 /* argument out of range */ -#define MP_BADARG -4 /* invalid parameter */ -#define MP_UNDEF -5 /* answer is undefined */ -#define MP_LAST_CODE MP_UNDEF - -#include "mpi-types.h" - -/* Included for compatibility... */ -#define DIGIT_BIT MP_DIGIT_BIT -#define DIGIT_MAX MP_DIGIT_MAX - -/* Macros for accessing the mp_int internals */ -#define SIGN(MP) ((MP)->sign) -#define USED(MP) ((MP)->used) -#define ALLOC(MP) ((MP)->alloc) -#define DIGITS(MP) ((MP)->dp) -#define DIGIT(MP,N) (MP)->dp[(N)] - -#if MP_ARGCHK == 1 -#define ARGCHK(X,Y) {if(!(X)){return (Y);}} -#elif MP_ARGCHK == 2 -#include <assert.h> -#define ARGCHK(X,Y) assert(X) -#else -#define ARGCHK(X,Y) /* */ -#endif - -/* This defines the maximum I/O base (minimum is 2) */ -#define MAX_RADIX 64 - -typedef struct { - mp_sign sign; /* sign of this quantity */ - mp_size alloc; /* how many digits allocated */ - mp_size used; /* how many digits used */ - mp_digit *dp; /* the digits themselves */ -} mp_int; - -/*------------------------------------------------------------------------*/ -/* Default precision */ - -unsigned int mp_get_prec(void); -void mp_set_prec(unsigned int prec); - -/*------------------------------------------------------------------------*/ -/* Memory management */ - -mp_err mp_init(mp_int *mp); -mp_err mp_init_array(mp_int mp[], int count); -mp_err mp_init_size(mp_int *mp, mp_size prec); -mp_err mp_init_copy(mp_int *mp, mp_int *from); -mp_err mp_copy(mp_int *from, mp_int *to); -void mp_exch(mp_int *mp1, mp_int *mp2); -void mp_clear(mp_int *mp); -void mp_clear_array(mp_int mp[], int count); -void mp_zero(mp_int *mp); -void mp_set(mp_int *mp, mp_digit d); -mp_err mp_set_int(mp_int *mp, long z); -mp_err mp_shrink(mp_int *a); - - -/*------------------------------------------------------------------------*/ -/* Single digit arithmetic */ - -mp_err mp_add_d(mp_int *a, mp_digit d, mp_int *b); -mp_err mp_sub_d(mp_int *a, mp_digit d, mp_int *b); -mp_err mp_mul_d(mp_int *a, mp_digit d, mp_int *b); -mp_err mp_mul_2(mp_int *a, mp_int *c); -mp_err mp_div_d(mp_int *a, mp_digit d, mp_int *q, mp_digit *r); -mp_err mp_div_2(mp_int *a, mp_int *c); -mp_err mp_expt_d(mp_int *a, mp_digit d, mp_int *c); - -/*------------------------------------------------------------------------*/ -/* Sign manipulations */ - -mp_err mp_abs(mp_int *a, mp_int *b); -mp_err mp_neg(mp_int *a, mp_int *b); - -/*------------------------------------------------------------------------*/ -/* Full arithmetic */ - -mp_err mp_add(mp_int *a, mp_int *b, mp_int *c); -mp_err mp_sub(mp_int *a, mp_int *b, mp_int *c); -mp_err mp_mul(mp_int *a, mp_int *b, mp_int *c); -mp_err mp_mul_2d(mp_int *a, mp_digit d, mp_int *c); -#if MP_SQUARE -mp_err mp_sqr(mp_int *a, mp_int *b); -#else -#define mp_sqr(a, b) mp_mul(a, a, b) -#endif -mp_err mp_div(mp_int *a, mp_int *b, mp_int *q, mp_int *r); -mp_err mp_div_2d(mp_int *a, mp_digit d, mp_int *q, mp_int *r); -mp_err mp_expt(mp_int *a, mp_int *b, mp_int *c); -mp_err mp_2expt(mp_int *a, mp_digit k); -mp_err mp_sqrt(mp_int *a, mp_int *b); - -/*------------------------------------------------------------------------*/ -/* Modular arithmetic */ - -#if MP_MODARITH -mp_err mp_mod(mp_int *a, mp_int *m, mp_int *c); -mp_err mp_mod_d(mp_int *a, mp_digit d, mp_digit *c); -mp_err mp_addmod(mp_int *a, mp_int *b, mp_int *m, mp_int *c); -mp_err mp_submod(mp_int *a, mp_int *b, mp_int *m, mp_int *c); -mp_err mp_mulmod(mp_int *a, mp_int *b, mp_int *m, mp_int *c); -#if MP_SQUARE -mp_err mp_sqrmod(mp_int *a, mp_int *m, mp_int *c); -#else -#define mp_sqrmod(a, m, c) mp_mulmod(a, a, m, c) -#endif -mp_err mp_exptmod(mp_int *a, mp_int *b, mp_int *m, mp_int *c); -mp_err mp_exptmod_d(mp_int *a, mp_digit d, mp_int *m, mp_int *c); -#endif /* MP_MODARITH */ - -/*------------------------------------------------------------------------*/ -/* Comparisons */ - -int mp_cmp_z(mp_int *a); -int mp_cmp_d(mp_int *a, mp_digit d); -int mp_cmp(mp_int *a, mp_int *b); -int mp_cmp_mag(mp_int *a, mp_int *b); -int mp_cmp_int(mp_int *a, long z); -int mp_isodd(mp_int *a); -int mp_iseven(mp_int *a); - -/*------------------------------------------------------------------------*/ -/* Number theoretic */ - -#if MP_NUMTH -mp_err mp_gcd(mp_int *a, mp_int *b, mp_int *c); -mp_err mp_lcm(mp_int *a, mp_int *b, mp_int *c); -mp_err mp_xgcd(mp_int *a, mp_int *b, mp_int *g, mp_int *x, mp_int *y); -mp_err mp_invmod(mp_int *a, mp_int *m, mp_int *c); -#endif /* end MP_NUMTH */ - -/*------------------------------------------------------------------------*/ -/* Input and output */ - -#if MP_IOFUNC -void mp_print(mp_int *mp, FILE *ofp); -#endif /* end MP_IOFUNC */ - -/*------------------------------------------------------------------------*/ -/* Base conversion */ - -#define BITS 1 -#define BYTES CHAR_BIT - -mp_err mp_read_signed_bin(mp_int *mp, unsigned char *str, int len); -int mp_signed_bin_size(mp_int *mp); -mp_err mp_to_signed_bin(mp_int *mp, unsigned char *str); - -mp_err mp_read_unsigned_bin(mp_int *mp, unsigned char *str, int len); -int mp_unsigned_bin_size(mp_int *mp); -mp_err mp_to_unsigned_bin(mp_int *mp, unsigned char *str); - -int mp_count_bits(mp_int *mp); - -#if MP_COMPAT_MACROS -#define mp_read_raw(mp, str, len) mp_read_signed_bin((mp), (str), (len)) -#define mp_raw_size(mp) mp_signed_bin_size(mp) -#define mp_toraw(mp, str) mp_to_signed_bin((mp), (str)) -#define mp_read_mag(mp, str, len) mp_read_unsigned_bin((mp), (str), (len)) -#define mp_mag_size(mp) mp_unsigned_bin_size(mp) -#define mp_tomag(mp, str) mp_to_unsigned_bin((mp), (str)) -#endif - -mp_err mp_read_radix(mp_int *mp, unsigned char *str, int radix); -int mp_radix_size(mp_int *mp, int radix); -int mp_value_radix_size(int num, int qty, int radix); -mp_err mp_toradix(mp_int *mp, char *str, int radix); - -int mp_char2value(char ch, int r); - -#define mp_tobinary(M, S) mp_toradix((M), (S), 2) -#define mp_tooctal(M, S) mp_toradix((M), (S), 8) -#define mp_todecimal(M, S) mp_toradix((M), (S), 10) -#define mp_tohex(M, S) mp_toradix((M), (S), 16) - -/*------------------------------------------------------------------------*/ -/* Error strings */ - -const char *mp_strerror(mp_err ec); - -#endif /* end _H_MPI_ */ - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ diff --git a/libtommath/mtest/mtest.c b/libtommath/mtest/mtest.c deleted file mode 100644 index 56b5a90..0000000 --- a/libtommath/mtest/mtest.c +++ /dev/null @@ -1,374 +0,0 @@ -/* makes a bignum test harness with NUM tests per operation - * - * the output is made in the following format [one parameter per line] - -operation -operand1 -operand2 -[... operandN] -result1 -result2 -[... resultN] - -So for example "a * b mod n" would be - -mulmod -a -b -n -a*b mod n - -e.g. if a=3, b=4 n=11 then - -mulmod -3 -4 -11 -1 - - */ - -#ifdef MP_8BIT -#define THE_MASK 127 -#else -#define THE_MASK 32767 -#endif - -#include <stdio.h> -#include <stdlib.h> -#include <time.h> -#include "mpi.c" - -#ifdef LTM_MTEST_REAL_RAND -#define getRandChar() fgetc(rng) -FILE *rng; -#else -#define getRandChar() (rand()&0xFF) -#endif - -void rand_num(mp_int *a) -{ - int size; - unsigned char buf[2048]; - size_t sz; - - size = 1 + ((getRandChar()<<8) + getRandChar()) % 101; - buf[0] = (getRandChar()&1)?1:0; -#ifdef LTM_MTEST_REAL_RAND - sz = fread(buf+1, 1, size, rng); -#else - sz = 1; - while (sz < (unsigned)size) { - buf[sz] = getRandChar(); - ++sz; - } -#endif - if (sz != (unsigned)size) { - fprintf(stderr, "\nWarning: fread failed\n\n"); - } - while (buf[1] == 0) buf[1] = getRandChar(); - mp_read_raw(a, buf, 1+size); -} - -void rand_num2(mp_int *a) -{ - int size; - unsigned char buf[2048]; - size_t sz; - - size = 10 + ((getRandChar()<<8) + getRandChar()) % 101; - buf[0] = (getRandChar()&1)?1:0; -#ifdef LTM_MTEST_REAL_RAND - sz = fread(buf+1, 1, size, rng); -#else - sz = 1; - while (sz < (unsigned)size) { - buf[sz] = getRandChar(); - ++sz; - } -#endif - if (sz != (unsigned)size) { - fprintf(stderr, "\nWarning: fread failed\n\n"); - } - while (buf[1] == 0) buf[1] = getRandChar(); - mp_read_raw(a, buf, 1+size); -} - -#define mp_to64(a, b) mp_toradix(a, b, 64) - -int main(int argc, char *argv[]) -{ - int n, tmp; - long long max; - mp_int a, b, c, d, e; -#ifdef MTEST_NO_FULLSPEED - clock_t t1; -#endif - char buf[4096]; - - mp_init(&a); - mp_init(&b); - mp_init(&c); - mp_init(&d); - mp_init(&e); - - if (argc > 1) { - max = strtol(argv[1], NULL, 0); - if (max < 0) { - if (max > -64) { - max = (1 << -(max)) + 1; - } else { - max = 1; - } - } else if (max == 0) { - max = 1; - } - } - else { - max = 0; - } - - - /* initial (2^n - 1)^2 testing, makes sure the comba multiplier works [it has the new carry code] */ -/* - mp_set(&a, 1); - for (n = 1; n < 8192; n++) { - mp_mul(&a, &a, &c); - printf("mul\n"); - mp_to64(&a, buf); - printf("%s\n%s\n", buf, buf); - mp_to64(&c, buf); - printf("%s\n", buf); - - mp_add_d(&a, 1, &a); - mp_mul_2(&a, &a); - mp_sub_d(&a, 1, &a); - } -*/ - -#ifdef LTM_MTEST_REAL_RAND - rng = fopen("/dev/urandom", "rb"); - if (rng == NULL) { - rng = fopen("/dev/random", "rb"); - if (rng == NULL) { - fprintf(stderr, "\nWarning: stdin used as random source\n\n"); - rng = stdin; - } - } -#else - srand(23); -#endif - -#ifdef MTEST_NO_FULLSPEED - t1 = clock(); -#endif - for (;;) { -#ifdef MTEST_NO_FULLSPEED - if (clock() - t1 > CLOCKS_PER_SEC) { - sleep(2); - t1 = clock(); - } -#endif - n = getRandChar() % 15; - - if (max != 0) { - --max; - if (max == 0) - n = 255; - } - - if (n == 0) { - /* add tests */ - rand_num(&a); - rand_num(&b); - mp_add(&a, &b, &c); - printf("add\n"); - mp_to64(&a, buf); - printf("%s\n", buf); - mp_to64(&b, buf); - printf("%s\n", buf); - mp_to64(&c, buf); - printf("%s\n", buf); - } else if (n == 1) { - /* sub tests */ - rand_num(&a); - rand_num(&b); - mp_sub(&a, &b, &c); - printf("sub\n"); - mp_to64(&a, buf); - printf("%s\n", buf); - mp_to64(&b, buf); - printf("%s\n", buf); - mp_to64(&c, buf); - printf("%s\n", buf); - } else if (n == 2) { - /* mul tests */ - rand_num(&a); - rand_num(&b); - mp_mul(&a, &b, &c); - printf("mul\n"); - mp_to64(&a, buf); - printf("%s\n", buf); - mp_to64(&b, buf); - printf("%s\n", buf); - mp_to64(&c, buf); - printf("%s\n", buf); - } else if (n == 3) { - /* div tests */ - rand_num(&a); - rand_num(&b); - mp_div(&a, &b, &c, &d); - printf("div\n"); - mp_to64(&a, buf); - printf("%s\n", buf); - mp_to64(&b, buf); - printf("%s\n", buf); - mp_to64(&c, buf); - printf("%s\n", buf); - mp_to64(&d, buf); - printf("%s\n", buf); - } else if (n == 4) { - /* sqr tests */ - rand_num(&a); - mp_sqr(&a, &b); - printf("sqr\n"); - mp_to64(&a, buf); - printf("%s\n", buf); - mp_to64(&b, buf); - printf("%s\n", buf); - } else if (n == 5) { - /* mul_2d test */ - rand_num(&a); - mp_copy(&a, &b); - n = getRandChar() & 63; - mp_mul_2d(&b, n, &b); - mp_to64(&a, buf); - printf("mul2d\n"); - printf("%s\n", buf); - printf("%d\n", n); - mp_to64(&b, buf); - printf("%s\n", buf); - } else if (n == 6) { - /* div_2d test */ - rand_num(&a); - mp_copy(&a, &b); - n = getRandChar() & 63; - mp_div_2d(&b, n, &b, NULL); - mp_to64(&a, buf); - printf("div2d\n"); - printf("%s\n", buf); - printf("%d\n", n); - mp_to64(&b, buf); - printf("%s\n", buf); - } else if (n == 7) { - /* gcd test */ - rand_num(&a); - rand_num(&b); - a.sign = MP_ZPOS; - b.sign = MP_ZPOS; - mp_gcd(&a, &b, &c); - printf("gcd\n"); - mp_to64(&a, buf); - printf("%s\n", buf); - mp_to64(&b, buf); - printf("%s\n", buf); - mp_to64(&c, buf); - printf("%s\n", buf); - } else if (n == 8) { - /* lcm test */ - rand_num(&a); - rand_num(&b); - a.sign = MP_ZPOS; - b.sign = MP_ZPOS; - mp_lcm(&a, &b, &c); - printf("lcm\n"); - mp_to64(&a, buf); - printf("%s\n", buf); - mp_to64(&b, buf); - printf("%s\n", buf); - mp_to64(&c, buf); - printf("%s\n", buf); - } else if (n == 9) { - /* exptmod test */ - rand_num2(&a); - rand_num2(&b); - rand_num2(&c); -// if (c.dp[0]&1) mp_add_d(&c, 1, &c); - a.sign = b.sign = c.sign = 0; - mp_exptmod(&a, &b, &c, &d); - printf("expt\n"); - mp_to64(&a, buf); - printf("%s\n", buf); - mp_to64(&b, buf); - printf("%s\n", buf); - mp_to64(&c, buf); - printf("%s\n", buf); - mp_to64(&d, buf); - printf("%s\n", buf); - } else if (n == 10) { - /* invmod test */ - rand_num2(&a); - rand_num2(&b); - b.sign = MP_ZPOS; - a.sign = MP_ZPOS; - mp_gcd(&a, &b, &c); - if (mp_cmp_d(&c, 1) != 0) continue; - if (mp_cmp_d(&b, 1) == 0) continue; - mp_invmod(&a, &b, &c); - printf("invmod\n"); - mp_to64(&a, buf); - printf("%s\n", buf); - mp_to64(&b, buf); - printf("%s\n", buf); - mp_to64(&c, buf); - printf("%s\n", buf); - } else if (n == 11) { - rand_num(&a); - mp_mul_2(&a, &a); - mp_div_2(&a, &b); - printf("div2\n"); - mp_to64(&a, buf); - printf("%s\n", buf); - mp_to64(&b, buf); - printf("%s\n", buf); - } else if (n == 12) { - rand_num2(&a); - mp_mul_2(&a, &b); - printf("mul2\n"); - mp_to64(&a, buf); - printf("%s\n", buf); - mp_to64(&b, buf); - printf("%s\n", buf); - } else if (n == 13) { - rand_num2(&a); - tmp = abs(rand()) & THE_MASK; - mp_add_d(&a, tmp, &b); - printf("add_d\n"); - mp_to64(&a, buf); - printf("%s\n%d\n", buf, tmp); - mp_to64(&b, buf); - printf("%s\n", buf); - } else if (n == 14) { - rand_num2(&a); - tmp = abs(rand()) & THE_MASK; - mp_sub_d(&a, tmp, &b); - printf("sub_d\n"); - mp_to64(&a, buf); - printf("%s\n%d\n", buf, tmp); - mp_to64(&b, buf); - printf("%s\n", buf); - } else if (n == 255) { - printf("exit\n"); - break; - } - - } -#ifdef LTM_MTEST_REAL_RAND - fclose(rng); -#endif - return 0; -} - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ diff --git a/libtommath/parsenames.pl b/libtommath/parsenames.pl deleted file mode 100755 index cc57673..0000000 --- a/libtommath/parsenames.pl +++ /dev/null @@ -1,25 +0,0 @@ -#!/usr/bin/perl -# -# Splits the list of files and outputs for makefile type files -# wrapped at 80 chars -# -# Tom St Denis -@a = split(" ", $ARGV[1]); -$b = "$ARGV[0]="; -$len = length($b); -print $b; -foreach my $obj (@a) { - $len = $len + length($obj); - $obj =~ s/\*/\$/; - if ($len > 100) { - printf "\\\n"; - $len = length($obj); - } - print "$obj "; -} - -print "\n\n"; - -# $Source$ -# $Revision$ -# $Date$ diff --git a/libtommath/pics/design_process.sxd b/libtommath/pics/design_process.sxd Binary files differdeleted file mode 100644 index 7414dbb..0000000 --- a/libtommath/pics/design_process.sxd +++ /dev/null diff --git a/libtommath/pics/design_process.tif b/libtommath/pics/design_process.tif Binary files differdeleted file mode 100644 index 4a0c012..0000000 --- a/libtommath/pics/design_process.tif +++ /dev/null diff --git a/libtommath/pics/expt_state.sxd b/libtommath/pics/expt_state.sxd Binary files differdeleted file mode 100644 index 6518404..0000000 --- a/libtommath/pics/expt_state.sxd +++ /dev/null diff --git a/libtommath/pics/expt_state.tif b/libtommath/pics/expt_state.tif Binary files differdeleted file mode 100644 index cb06e8e..0000000 --- a/libtommath/pics/expt_state.tif +++ /dev/null diff --git a/libtommath/pics/makefile b/libtommath/pics/makefile deleted file mode 100644 index 3ecb02f..0000000 --- a/libtommath/pics/makefile +++ /dev/null @@ -1,35 +0,0 @@ -# makes the images... yeah - -default: pses - -design_process.ps: design_process.tif - tiff2ps -s -e design_process.tif > design_process.ps - -sliding_window.ps: sliding_window.tif - tiff2ps -s -e sliding_window.tif > sliding_window.ps - -expt_state.ps: expt_state.tif - tiff2ps -s -e expt_state.tif > expt_state.ps - -primality.ps: primality.tif - tiff2ps -s -e primality.tif > primality.ps - -design_process.pdf: design_process.ps - epstopdf design_process.ps - -sliding_window.pdf: sliding_window.ps - epstopdf sliding_window.ps - -expt_state.pdf: expt_state.ps - epstopdf expt_state.ps - -primality.pdf: primality.ps - epstopdf primality.ps - - -pses: sliding_window.ps expt_state.ps primality.ps design_process.ps -pdfes: sliding_window.pdf expt_state.pdf primality.pdf design_process.pdf - -clean: - rm -rf *.ps *.pdf .xvpics -
\ No newline at end of file diff --git a/libtommath/pics/primality.tif b/libtommath/pics/primality.tif Binary files differdeleted file mode 100644 index 76d6be3..0000000 --- a/libtommath/pics/primality.tif +++ /dev/null diff --git a/libtommath/pics/radix.sxd b/libtommath/pics/radix.sxd Binary files differdeleted file mode 100644 index b9eb9a0..0000000 --- a/libtommath/pics/radix.sxd +++ /dev/null diff --git a/libtommath/pics/sliding_window.sxd b/libtommath/pics/sliding_window.sxd Binary files differdeleted file mode 100644 index 91e7c0d..0000000 --- a/libtommath/pics/sliding_window.sxd +++ /dev/null diff --git a/libtommath/pics/sliding_window.tif b/libtommath/pics/sliding_window.tif Binary files differdeleted file mode 100644 index bb4cb96..0000000 --- a/libtommath/pics/sliding_window.tif +++ /dev/null diff --git a/libtommath/poster.out b/libtommath/poster.out deleted file mode 100644 index e69de29..0000000 --- a/libtommath/poster.out +++ /dev/null diff --git a/libtommath/poster.pdf b/libtommath/poster.pdf Binary files differdeleted file mode 100644 index f212c3e..0000000 --- a/libtommath/poster.pdf +++ /dev/null diff --git a/libtommath/poster.tex b/libtommath/poster.tex deleted file mode 100644 index e7388f4..0000000 --- a/libtommath/poster.tex +++ /dev/null @@ -1,35 +0,0 @@ -\documentclass[landscape,11pt]{article} -\usepackage{amsmath, amssymb} -\usepackage{hyperref} -\begin{document} -\hspace*{-3in} -\begin{tabular}{llllll} -$c = a + b$ & {\tt mp\_add(\&a, \&b, \&c)} & $b = 2a$ & {\tt mp\_mul\_2(\&a, \&b)} & \\ -$c = a - b$ & {\tt mp\_sub(\&a, \&b, \&c)} & $b = a/2$ & {\tt mp\_div\_2(\&a, \&b)} & \\ -$c = ab $ & {\tt mp\_mul(\&a, \&b, \&c)} & $c = 2^ba$ & {\tt mp\_mul\_2d(\&a, b, \&c)} \\ -$b = a^2 $ & {\tt mp\_sqr(\&a, \&b)} & $c = a/2^b, d = a \mod 2^b$ & {\tt mp\_div\_2d(\&a, b, \&c, \&d)} \\ -$c = \lfloor a/b \rfloor, d = a \mod b$ & {\tt mp\_div(\&a, \&b, \&c, \&d)} & $c = a \mod 2^b $ & {\tt mp\_mod\_2d(\&a, b, \&c)} \\ - && \\ -$a = b $ & {\tt mp\_set\_int(\&a, b)} & $c = a \vee b$ & {\tt mp\_or(\&a, \&b, \&c)} \\ -$b = a $ & {\tt mp\_copy(\&a, \&b)} & $c = a \wedge b$ & {\tt mp\_and(\&a, \&b, \&c)} \\ - && $c = a \oplus b$ & {\tt mp\_xor(\&a, \&b, \&c)} \\ - & \\ -$b = -a $ & {\tt mp\_neg(\&a, \&b)} & $d = a + b \mod c$ & {\tt mp\_addmod(\&a, \&b, \&c, \&d)} \\ -$b = |a| $ & {\tt mp\_abs(\&a, \&b)} & $d = a - b \mod c$ & {\tt mp\_submod(\&a, \&b, \&c, \&d)} \\ - && $d = ab \mod c$ & {\tt mp\_mulmod(\&a, \&b, \&c, \&d)} \\ -Compare $a$ and $b$ & {\tt mp\_cmp(\&a, \&b)} & $c = a^2 \mod b$ & {\tt mp\_sqrmod(\&a, \&b, \&c)} \\ -Is Zero? & {\tt mp\_iszero(\&a)} & $c = a^{-1} \mod b$ & {\tt mp\_invmod(\&a, \&b, \&c)} \\ -Is Even? & {\tt mp\_iseven(\&a)} & $d = a^b \mod c$ & {\tt mp\_exptmod(\&a, \&b, \&c, \&d)} \\ -Is Odd ? & {\tt mp\_isodd(\&a)} \\ -&\\ -$\vert \vert a \vert \vert$ & {\tt mp\_unsigned\_bin\_size(\&a)} & $res$ = 1 if $a$ prime to $t$ rounds? & {\tt mp\_prime\_is\_prime(\&a, t, \&res)} \\ -$buf \leftarrow a$ & {\tt mp\_to\_unsigned\_bin(\&a, buf)} & Next prime after $a$ to $t$ rounds. & {\tt mp\_prime\_next\_prime(\&a, t, bbs\_style)} \\ -$a \leftarrow buf[0..len-1]$ & {\tt mp\_read\_unsigned\_bin(\&a, buf, len)} \\ -&\\ -$b = \sqrt{a}$ & {\tt mp\_sqrt(\&a, \&b)} & $c = \mbox{gcd}(a, b)$ & {\tt mp\_gcd(\&a, \&b, \&c)} \\ -$c = a^{1/b}$ & {\tt mp\_n\_root(\&a, b, \&c)} & $c = \mbox{lcm}(a, b)$ & {\tt mp\_lcm(\&a, \&b, \&c)} \\ -&\\ -Greater Than & MP\_GT & Equal To & MP\_EQ \\ -Less Than & MP\_LT & Bits per digit & DIGIT\_BIT \\ -\end{tabular} -\end{document} diff --git a/libtommath/pre_gen/mpi.c b/libtommath/pre_gen/mpi.c deleted file mode 100644 index 0d55d73..0000000 --- a/libtommath/pre_gen/mpi.c +++ /dev/null @@ -1,9524 +0,0 @@ -/* Start: bn_error.c */ -#include <tommath.h> -#ifdef BN_ERROR_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -static const struct { - int code; - char *msg; -} msgs[] = { - { MP_OKAY, "Successful" }, - { MP_MEM, "Out of heap" }, - { MP_VAL, "Value out of range" } -}; - -/* return a char * string for a given code */ -char *mp_error_to_string(int code) -{ - int x; - - /* scan the lookup table for the given message */ - for (x = 0; x < (int)(sizeof(msgs) / sizeof(msgs[0])); x++) { - if (msgs[x].code == code) { - return msgs[x].msg; - } - } - - /* generic reply for invalid code */ - return "Invalid error code"; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_error.c */ - -/* Start: bn_fast_mp_invmod.c */ -#include <tommath.h> -#ifdef BN_FAST_MP_INVMOD_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* computes the modular inverse via binary extended euclidean algorithm, - * that is c = 1/a mod b - * - * Based on slow invmod except this is optimized for the case where b is - * odd as per HAC Note 14.64 on pp. 610 - */ -int fast_mp_invmod (mp_int * a, mp_int * b, mp_int * c) -{ - mp_int x, y, u, v, B, D; - int res, neg; - - /* 2. [modified] b must be odd */ - if (mp_iseven (b) == 1) { - return MP_VAL; - } - - /* init all our temps */ - if ((res = mp_init_multi(&x, &y, &u, &v, &B, &D, NULL)) != MP_OKAY) { - return res; - } - - /* x == modulus, y == value to invert */ - if ((res = mp_copy (b, &x)) != MP_OKAY) { - goto LBL_ERR; - } - - /* we need y = |a| */ - if ((res = mp_mod (a, b, &y)) != MP_OKAY) { - goto LBL_ERR; - } - - /* 3. u=x, v=y, A=1, B=0, C=0,D=1 */ - if ((res = mp_copy (&x, &u)) != MP_OKAY) { - goto LBL_ERR; - } - if ((res = mp_copy (&y, &v)) != MP_OKAY) { - goto LBL_ERR; - } - mp_set (&D, 1); - -top: - /* 4. while u is even do */ - while (mp_iseven (&u) == 1) { - /* 4.1 u = u/2 */ - if ((res = mp_div_2 (&u, &u)) != MP_OKAY) { - goto LBL_ERR; - } - /* 4.2 if B is odd then */ - if (mp_isodd (&B) == 1) { - if ((res = mp_sub (&B, &x, &B)) != MP_OKAY) { - goto LBL_ERR; - } - } - /* B = B/2 */ - if ((res = mp_div_2 (&B, &B)) != MP_OKAY) { - goto LBL_ERR; - } - } - - /* 5. while v is even do */ - while (mp_iseven (&v) == 1) { - /* 5.1 v = v/2 */ - if ((res = mp_div_2 (&v, &v)) != MP_OKAY) { - goto LBL_ERR; - } - /* 5.2 if D is odd then */ - if (mp_isodd (&D) == 1) { - /* D = (D-x)/2 */ - if ((res = mp_sub (&D, &x, &D)) != MP_OKAY) { - goto LBL_ERR; - } - } - /* D = D/2 */ - if ((res = mp_div_2 (&D, &D)) != MP_OKAY) { - goto LBL_ERR; - } - } - - /* 6. if u >= v then */ - if (mp_cmp (&u, &v) != MP_LT) { - /* u = u - v, B = B - D */ - if ((res = mp_sub (&u, &v, &u)) != MP_OKAY) { - goto LBL_ERR; - } - - if ((res = mp_sub (&B, &D, &B)) != MP_OKAY) { - goto LBL_ERR; - } - } else { - /* v - v - u, D = D - B */ - if ((res = mp_sub (&v, &u, &v)) != MP_OKAY) { - goto LBL_ERR; - } - - if ((res = mp_sub (&D, &B, &D)) != MP_OKAY) { - goto LBL_ERR; - } - } - - /* if not zero goto step 4 */ - if (mp_iszero (&u) == 0) { - goto top; - } - - /* now a = C, b = D, gcd == g*v */ - - /* if v != 1 then there is no inverse */ - if (mp_cmp_d (&v, 1) != MP_EQ) { - res = MP_VAL; - goto LBL_ERR; - } - - /* b is now the inverse */ - neg = a->sign; - while (D.sign == MP_NEG) { - if ((res = mp_add (&D, b, &D)) != MP_OKAY) { - goto LBL_ERR; - } - } - mp_exch (&D, c); - c->sign = neg; - res = MP_OKAY; - -LBL_ERR:mp_clear_multi (&x, &y, &u, &v, &B, &D, NULL); - return res; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_fast_mp_invmod.c */ - -/* Start: bn_fast_mp_montgomery_reduce.c */ -#include <tommath.h> -#ifdef BN_FAST_MP_MONTGOMERY_REDUCE_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* computes xR**-1 == x (mod N) via Montgomery Reduction - * - * This is an optimized implementation of montgomery_reduce - * which uses the comba method to quickly calculate the columns of the - * reduction. - * - * Based on Algorithm 14.32 on pp.601 of HAC. -*/ -int fast_mp_montgomery_reduce (mp_int * x, mp_int * n, mp_digit rho) -{ - int ix, res, olduse; - mp_word W[MP_WARRAY]; - - /* get old used count */ - olduse = x->used; - - /* grow a as required */ - if (x->alloc < n->used + 1) { - if ((res = mp_grow (x, n->used + 1)) != MP_OKAY) { - return res; - } - } - - /* first we have to get the digits of the input into - * an array of double precision words W[...] - */ - { - register mp_word *_W; - register mp_digit *tmpx; - - /* alias for the W[] array */ - _W = W; - - /* alias for the digits of x*/ - tmpx = x->dp; - - /* copy the digits of a into W[0..a->used-1] */ - for (ix = 0; ix < x->used; ix++) { - *_W++ = *tmpx++; - } - - /* zero the high words of W[a->used..m->used*2] */ - for (; ix < n->used * 2 + 1; ix++) { - *_W++ = 0; - } - } - - /* now we proceed to zero successive digits - * from the least significant upwards - */ - for (ix = 0; ix < n->used; ix++) { - /* mu = ai * m' mod b - * - * We avoid a double precision multiplication (which isn't required) - * by casting the value down to a mp_digit. Note this requires - * that W[ix-1] have the carry cleared (see after the inner loop) - */ - register mp_digit mu; - mu = (mp_digit) (((W[ix] & MP_MASK) * rho) & MP_MASK); - - /* a = a + mu * m * b**i - * - * This is computed in place and on the fly. The multiplication - * by b**i is handled by offseting which columns the results - * are added to. - * - * Note the comba method normally doesn't handle carries in the - * inner loop In this case we fix the carry from the previous - * column since the Montgomery reduction requires digits of the - * result (so far) [see above] to work. This is - * handled by fixing up one carry after the inner loop. The - * carry fixups are done in order so after these loops the - * first m->used words of W[] have the carries fixed - */ - { - register int iy; - register mp_digit *tmpn; - register mp_word *_W; - - /* alias for the digits of the modulus */ - tmpn = n->dp; - - /* Alias for the columns set by an offset of ix */ - _W = W + ix; - - /* inner loop */ - for (iy = 0; iy < n->used; iy++) { - *_W++ += ((mp_word)mu) * ((mp_word)*tmpn++); - } - } - - /* now fix carry for next digit, W[ix+1] */ - W[ix + 1] += W[ix] >> ((mp_word) DIGIT_BIT); - } - - /* now we have to propagate the carries and - * shift the words downward [all those least - * significant digits we zeroed]. - */ - { - register mp_digit *tmpx; - register mp_word *_W, *_W1; - - /* nox fix rest of carries */ - - /* alias for current word */ - _W1 = W + ix; - - /* alias for next word, where the carry goes */ - _W = W + ++ix; - - for (; ix <= n->used * 2 + 1; ix++) { - *_W++ += *_W1++ >> ((mp_word) DIGIT_BIT); - } - - /* copy out, A = A/b**n - * - * The result is A/b**n but instead of converting from an - * array of mp_word to mp_digit than calling mp_rshd - * we just copy them in the right order - */ - - /* alias for destination word */ - tmpx = x->dp; - - /* alias for shifted double precision result */ - _W = W + n->used; - - for (ix = 0; ix < n->used + 1; ix++) { - *tmpx++ = (mp_digit)(*_W++ & ((mp_word) MP_MASK)); - } - - /* zero oldused digits, if the input a was larger than - * m->used+1 we'll have to clear the digits - */ - for (; ix < olduse; ix++) { - *tmpx++ = 0; - } - } - - /* set the max used and clamp */ - x->used = n->used + 1; - mp_clamp (x); - - /* if A >= m then A = A - m */ - if (mp_cmp_mag (x, n) != MP_LT) { - return s_mp_sub (x, n, x); - } - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_fast_mp_montgomery_reduce.c */ - -/* Start: bn_fast_s_mp_mul_digs.c */ -#include <tommath.h> -#ifdef BN_FAST_S_MP_MUL_DIGS_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* Fast (comba) multiplier - * - * This is the fast column-array [comba] multiplier. It is - * designed to compute the columns of the product first - * then handle the carries afterwards. This has the effect - * of making the nested loops that compute the columns very - * simple and schedulable on super-scalar processors. - * - * This has been modified to produce a variable number of - * digits of output so if say only a half-product is required - * you don't have to compute the upper half (a feature - * required for fast Barrett reduction). - * - * Based on Algorithm 14.12 on pp.595 of HAC. - * - */ -int fast_s_mp_mul_digs (mp_int * a, mp_int * b, mp_int * c, int digs) -{ - int olduse, res, pa, ix, iz; - mp_digit W[MP_WARRAY]; - register mp_word _W; - - /* grow the destination as required */ - if (c->alloc < digs) { - if ((res = mp_grow (c, digs)) != MP_OKAY) { - return res; - } - } - - /* number of output digits to produce */ - pa = MIN(digs, a->used + b->used); - - /* clear the carry */ - _W = 0; - for (ix = 0; ix < pa; ix++) { - int tx, ty; - int iy; - mp_digit *tmpx, *tmpy; - - /* get offsets into the two bignums */ - ty = MIN(b->used-1, ix); - tx = ix - ty; - - /* setup temp aliases */ - tmpx = a->dp + tx; - tmpy = b->dp + ty; - - /* this is the number of times the loop will iterrate, essentially - while (tx++ < a->used && ty-- >= 0) { ... } - */ - iy = MIN(a->used-tx, ty+1); - - /* execute loop */ - for (iz = 0; iz < iy; ++iz) { - _W += ((mp_word)*tmpx++)*((mp_word)*tmpy--); - - } - - /* store term */ - W[ix] = ((mp_digit)_W) & MP_MASK; - - /* make next carry */ - _W = _W >> ((mp_word)DIGIT_BIT); - } - - /* setup dest */ - olduse = c->used; - c->used = pa; - - { - register mp_digit *tmpc; - tmpc = c->dp; - for (ix = 0; ix < pa+1; ix++) { - /* now extract the previous digit [below the carry] */ - *tmpc++ = W[ix]; - } - - /* clear unused digits [that existed in the old copy of c] */ - for (; ix < olduse; ix++) { - *tmpc++ = 0; - } - } - mp_clamp (c); - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_fast_s_mp_mul_digs.c */ - -/* Start: bn_fast_s_mp_mul_high_digs.c */ -#include <tommath.h> -#ifdef BN_FAST_S_MP_MUL_HIGH_DIGS_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* this is a modified version of fast_s_mul_digs that only produces - * output digits *above* digs. See the comments for fast_s_mul_digs - * to see how it works. - * - * This is used in the Barrett reduction since for one of the multiplications - * only the higher digits were needed. This essentially halves the work. - * - * Based on Algorithm 14.12 on pp.595 of HAC. - */ -int fast_s_mp_mul_high_digs (mp_int * a, mp_int * b, mp_int * c, int digs) -{ - int olduse, res, pa, ix, iz; - mp_digit W[MP_WARRAY]; - mp_word _W; - - /* grow the destination as required */ - pa = a->used + b->used; - if (c->alloc < pa) { - if ((res = mp_grow (c, pa)) != MP_OKAY) { - return res; - } - } - - /* number of output digits to produce */ - pa = a->used + b->used; - _W = 0; - for (ix = digs; ix < pa; ix++) { - int tx, ty, iy; - mp_digit *tmpx, *tmpy; - - /* get offsets into the two bignums */ - ty = MIN(b->used-1, ix); - tx = ix - ty; - - /* setup temp aliases */ - tmpx = a->dp + tx; - tmpy = b->dp + ty; - - /* this is the number of times the loop will iterrate, essentially its - while (tx++ < a->used && ty-- >= 0) { ... } - */ - iy = MIN(a->used-tx, ty+1); - - /* execute loop */ - for (iz = 0; iz < iy; iz++) { - _W += ((mp_word)*tmpx++)*((mp_word)*tmpy--); - } - - /* store term */ - W[ix] = ((mp_digit)_W) & MP_MASK; - - /* make next carry */ - _W = _W >> ((mp_word)DIGIT_BIT); - } - - /* setup dest */ - olduse = c->used; - c->used = pa; - - { - register mp_digit *tmpc; - - tmpc = c->dp + digs; - for (ix = digs; ix < pa; ix++) { - /* now extract the previous digit [below the carry] */ - *tmpc++ = W[ix]; - } - - /* clear unused digits [that existed in the old copy of c] */ - for (; ix < olduse; ix++) { - *tmpc++ = 0; - } - } - mp_clamp (c); - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_fast_s_mp_mul_high_digs.c */ - -/* Start: bn_fast_s_mp_sqr.c */ -#include <tommath.h> -#ifdef BN_FAST_S_MP_SQR_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* the jist of squaring... - * you do like mult except the offset of the tmpx [one that - * starts closer to zero] can't equal the offset of tmpy. - * So basically you set up iy like before then you min it with - * (ty-tx) so that it never happens. You double all those - * you add in the inner loop - -After that loop you do the squares and add them in. -*/ - -int fast_s_mp_sqr (mp_int * a, mp_int * b) -{ - int olduse, res, pa, ix, iz; - mp_digit W[MP_WARRAY], *tmpx; - mp_word W1; - - /* grow the destination as required */ - pa = a->used + a->used; - if (b->alloc < pa) { - if ((res = mp_grow (b, pa)) != MP_OKAY) { - return res; - } - } - - /* number of output digits to produce */ - W1 = 0; - for (ix = 0; ix < pa; ix++) { - int tx, ty, iy; - mp_word _W; - mp_digit *tmpy; - - /* clear counter */ - _W = 0; - - /* get offsets into the two bignums */ - ty = MIN(a->used-1, ix); - tx = ix - ty; - - /* setup temp aliases */ - tmpx = a->dp + tx; - tmpy = a->dp + ty; - - /* this is the number of times the loop will iterrate, essentially - while (tx++ < a->used && ty-- >= 0) { ... } - */ - iy = MIN(a->used-tx, ty+1); - - /* now for squaring tx can never equal ty - * we halve the distance since they approach at a rate of 2x - * and we have to round because odd cases need to be executed - */ - iy = MIN(iy, (ty-tx+1)>>1); - - /* execute loop */ - for (iz = 0; iz < iy; iz++) { - _W += ((mp_word)*tmpx++)*((mp_word)*tmpy--); - } - - /* double the inner product and add carry */ - _W = _W + _W + W1; - - /* even columns have the square term in them */ - if ((ix&1) == 0) { - _W += ((mp_word)a->dp[ix>>1])*((mp_word)a->dp[ix>>1]); - } - - /* store it */ - W[ix] = (mp_digit)(_W & MP_MASK); - - /* make next carry */ - W1 = _W >> ((mp_word)DIGIT_BIT); - } - - /* setup dest */ - olduse = b->used; - b->used = a->used+a->used; - - { - mp_digit *tmpb; - tmpb = b->dp; - for (ix = 0; ix < pa; ix++) { - *tmpb++ = W[ix] & MP_MASK; - } - - /* clear unused digits [that existed in the old copy of c] */ - for (; ix < olduse; ix++) { - *tmpb++ = 0; - } - } - mp_clamp (b); - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_fast_s_mp_sqr.c */ - -/* Start: bn_mp_2expt.c */ -#include <tommath.h> -#ifdef BN_MP_2EXPT_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* computes a = 2**b - * - * Simple algorithm which zeroes the int, grows it then just sets one bit - * as required. - */ -int -mp_2expt (mp_int * a, int b) -{ - int res; - - /* zero a as per default */ - mp_zero (a); - - /* grow a to accomodate the single bit */ - if ((res = mp_grow (a, b / DIGIT_BIT + 1)) != MP_OKAY) { - return res; - } - - /* set the used count of where the bit will go */ - a->used = b / DIGIT_BIT + 1; - - /* put the single bit in its place */ - a->dp[b / DIGIT_BIT] = ((mp_digit)1) << (b % DIGIT_BIT); - - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_2expt.c */ - -/* Start: bn_mp_abs.c */ -#include <tommath.h> -#ifdef BN_MP_ABS_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* b = |a| - * - * Simple function copies the input and fixes the sign to positive - */ -int -mp_abs (mp_int * a, mp_int * b) -{ - int res; - - /* copy a to b */ - if (a != b) { - if ((res = mp_copy (a, b)) != MP_OKAY) { - return res; - } - } - - /* force the sign of b to positive */ - b->sign = MP_ZPOS; - - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_abs.c */ - -/* Start: bn_mp_add.c */ -#include <tommath.h> -#ifdef BN_MP_ADD_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* high level addition (handles signs) */ -int mp_add (mp_int * a, mp_int * b, mp_int * c) -{ - int sa, sb, res; - - /* get sign of both inputs */ - sa = a->sign; - sb = b->sign; - - /* handle two cases, not four */ - if (sa == sb) { - /* both positive or both negative */ - /* add their magnitudes, copy the sign */ - c->sign = sa; - res = s_mp_add (a, b, c); - } else { - /* one positive, the other negative */ - /* subtract the one with the greater magnitude from */ - /* the one of the lesser magnitude. The result gets */ - /* the sign of the one with the greater magnitude. */ - if (mp_cmp_mag (a, b) == MP_LT) { - c->sign = sb; - res = s_mp_sub (b, a, c); - } else { - c->sign = sa; - res = s_mp_sub (a, b, c); - } - } - return res; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_add.c */ - -/* Start: bn_mp_add_d.c */ -#include <tommath.h> -#ifdef BN_MP_ADD_D_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* single digit addition */ -int -mp_add_d (mp_int * a, mp_digit b, mp_int * c) -{ - int res, ix, oldused; - mp_digit *tmpa, *tmpc, mu; - - /* grow c as required */ - if (c->alloc < a->used + 1) { - if ((res = mp_grow(c, a->used + 1)) != MP_OKAY) { - return res; - } - } - - /* if a is negative and |a| >= b, call c = |a| - b */ - if (a->sign == MP_NEG && (a->used > 1 || a->dp[0] >= b)) { - /* temporarily fix sign of a */ - a->sign = MP_ZPOS; - - /* c = |a| - b */ - res = mp_sub_d(a, b, c); - - /* fix sign */ - a->sign = c->sign = MP_NEG; - - /* clamp */ - mp_clamp(c); - - return res; - } - - /* old number of used digits in c */ - oldused = c->used; - - /* sign always positive */ - c->sign = MP_ZPOS; - - /* source alias */ - tmpa = a->dp; - - /* destination alias */ - tmpc = c->dp; - - /* if a is positive */ - if (a->sign == MP_ZPOS) { - /* add digit, after this we're propagating - * the carry. - */ - *tmpc = *tmpa++ + b; - mu = *tmpc >> DIGIT_BIT; - *tmpc++ &= MP_MASK; - - /* now handle rest of the digits */ - for (ix = 1; ix < a->used; ix++) { - *tmpc = *tmpa++ + mu; - mu = *tmpc >> DIGIT_BIT; - *tmpc++ &= MP_MASK; - } - /* set final carry */ - ix++; - *tmpc++ = mu; - - /* setup size */ - c->used = a->used + 1; - } else { - /* a was negative and |a| < b */ - c->used = 1; - - /* the result is a single digit */ - if (a->used == 1) { - *tmpc++ = b - a->dp[0]; - } else { - *tmpc++ = b; - } - - /* setup count so the clearing of oldused - * can fall through correctly - */ - ix = 1; - } - - /* now zero to oldused */ - while (ix++ < oldused) { - *tmpc++ = 0; - } - mp_clamp(c); - - return MP_OKAY; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_add_d.c */ - -/* Start: bn_mp_addmod.c */ -#include <tommath.h> -#ifdef BN_MP_ADDMOD_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* d = a + b (mod c) */ -int -mp_addmod (mp_int * a, mp_int * b, mp_int * c, mp_int * d) -{ - int res; - mp_int t; - - if ((res = mp_init (&t)) != MP_OKAY) { - return res; - } - - if ((res = mp_add (a, b, &t)) != MP_OKAY) { - mp_clear (&t); - return res; - } - res = mp_mod (&t, c, d); - mp_clear (&t); - return res; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_addmod.c */ - -/* Start: bn_mp_and.c */ -#include <tommath.h> -#ifdef BN_MP_AND_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* AND two ints together */ -int -mp_and (mp_int * a, mp_int * b, mp_int * c) -{ - int res, ix, px; - mp_int t, *x; - - if (a->used > b->used) { - if ((res = mp_init_copy (&t, a)) != MP_OKAY) { - return res; - } - px = b->used; - x = b; - } else { - if ((res = mp_init_copy (&t, b)) != MP_OKAY) { - return res; - } - px = a->used; - x = a; - } - - for (ix = 0; ix < px; ix++) { - t.dp[ix] &= x->dp[ix]; - } - - /* zero digits above the last from the smallest mp_int */ - for (; ix < t.used; ix++) { - t.dp[ix] = 0; - } - - mp_clamp (&t); - mp_exch (c, &t); - mp_clear (&t); - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_and.c */ - -/* Start: bn_mp_clamp.c */ -#include <tommath.h> -#ifdef BN_MP_CLAMP_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* trim unused digits - * - * This is used to ensure that leading zero digits are - * trimed and the leading "used" digit will be non-zero - * Typically very fast. Also fixes the sign if there - * are no more leading digits - */ -void -mp_clamp (mp_int * a) -{ - /* decrease used while the most significant digit is - * zero. - */ - while (a->used > 0 && a->dp[a->used - 1] == 0) { - --(a->used); - } - - /* reset the sign flag if used == 0 */ - if (a->used == 0) { - a->sign = MP_ZPOS; - } -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_clamp.c */ - -/* Start: bn_mp_clear.c */ -#include <tommath.h> -#ifdef BN_MP_CLEAR_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* clear one (frees) */ -void -mp_clear (mp_int * a) -{ - int i; - - /* only do anything if a hasn't been freed previously */ - if (a->dp != NULL) { - /* first zero the digits */ - for (i = 0; i < a->used; i++) { - a->dp[i] = 0; - } - - /* free ram */ - XFREE(a->dp); - - /* reset members to make debugging easier */ - a->dp = NULL; - a->alloc = a->used = 0; - a->sign = MP_ZPOS; - } -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_clear.c */ - -/* Start: bn_mp_clear_multi.c */ -#include <tommath.h> -#ifdef BN_MP_CLEAR_MULTI_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ -#include <stdarg.h> - -void mp_clear_multi(mp_int *mp, ...) -{ - mp_int* next_mp = mp; - va_list args; - va_start(args, mp); - while (next_mp != NULL) { - mp_clear(next_mp); - next_mp = va_arg(args, mp_int*); - } - va_end(args); -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_clear_multi.c */ - -/* Start: bn_mp_cmp.c */ -#include <tommath.h> -#ifdef BN_MP_CMP_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* compare two ints (signed)*/ -int -mp_cmp (mp_int * a, mp_int * b) -{ - /* compare based on sign */ - if (a->sign != b->sign) { - if (a->sign == MP_NEG) { - return MP_LT; - } else { - return MP_GT; - } - } - - /* compare digits */ - if (a->sign == MP_NEG) { - /* if negative compare opposite direction */ - return mp_cmp_mag(b, a); - } else { - return mp_cmp_mag(a, b); - } -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_cmp.c */ - -/* Start: bn_mp_cmp_d.c */ -#include <tommath.h> -#ifdef BN_MP_CMP_D_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* compare a digit */ -int mp_cmp_d(mp_int * a, mp_digit b) -{ - /* compare based on sign */ - if (a->sign == MP_NEG) { - return MP_LT; - } - - /* compare based on magnitude */ - if (a->used > 1) { - return MP_GT; - } - - /* compare the only digit of a to b */ - if (a->dp[0] > b) { - return MP_GT; - } else if (a->dp[0] < b) { - return MP_LT; - } else { - return MP_EQ; - } -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_cmp_d.c */ - -/* Start: bn_mp_cmp_mag.c */ -#include <tommath.h> -#ifdef BN_MP_CMP_MAG_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* compare maginitude of two ints (unsigned) */ -int mp_cmp_mag (mp_int * a, mp_int * b) -{ - int n; - mp_digit *tmpa, *tmpb; - - /* compare based on # of non-zero digits */ - if (a->used > b->used) { - return MP_GT; - } - - if (a->used < b->used) { - return MP_LT; - } - - /* alias for a */ - tmpa = a->dp + (a->used - 1); - - /* alias for b */ - tmpb = b->dp + (a->used - 1); - - /* compare based on digits */ - for (n = 0; n < a->used; ++n, --tmpa, --tmpb) { - if (*tmpa > *tmpb) { - return MP_GT; - } - - if (*tmpa < *tmpb) { - return MP_LT; - } - } - return MP_EQ; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_cmp_mag.c */ - -/* Start: bn_mp_cnt_lsb.c */ -#include <tommath.h> -#ifdef BN_MP_CNT_LSB_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -static const int lnz[16] = { - 4, 0, 1, 0, 2, 0, 1, 0, 3, 0, 1, 0, 2, 0, 1, 0 -}; - -/* Counts the number of lsbs which are zero before the first zero bit */ -int mp_cnt_lsb(mp_int *a) -{ - int x; - mp_digit q, qq; - - /* easy out */ - if (mp_iszero(a) == 1) { - return 0; - } - - /* scan lower digits until non-zero */ - for (x = 0; x < a->used && a->dp[x] == 0; x++); - q = a->dp[x]; - x *= DIGIT_BIT; - - /* now scan this digit until a 1 is found */ - if ((q & 1) == 0) { - do { - qq = q & 15; - x += lnz[qq]; - q >>= 4; - } while (qq == 0); - } - return x; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_cnt_lsb.c */ - -/* Start: bn_mp_copy.c */ -#include <tommath.h> -#ifdef BN_MP_COPY_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* copy, b = a */ -int -mp_copy (mp_int * a, mp_int * b) -{ - int res, n; - - /* if dst == src do nothing */ - if (a == b) { - return MP_OKAY; - } - - /* grow dest */ - if (b->alloc < a->used) { - if ((res = mp_grow (b, a->used)) != MP_OKAY) { - return res; - } - } - - /* zero b and copy the parameters over */ - { - register mp_digit *tmpa, *tmpb; - - /* pointer aliases */ - - /* source */ - tmpa = a->dp; - - /* destination */ - tmpb = b->dp; - - /* copy all the digits */ - for (n = 0; n < a->used; n++) { - *tmpb++ = *tmpa++; - } - - /* clear high digits */ - for (; n < b->used; n++) { - *tmpb++ = 0; - } - } - - /* copy used count and sign */ - b->used = a->used; - b->sign = a->sign; - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_copy.c */ - -/* Start: bn_mp_count_bits.c */ -#include <tommath.h> -#ifdef BN_MP_COUNT_BITS_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* returns the number of bits in an int */ -int -mp_count_bits (mp_int * a) -{ - int r; - mp_digit q; - - /* shortcut */ - if (a->used == 0) { - return 0; - } - - /* get number of digits and add that */ - r = (a->used - 1) * DIGIT_BIT; - - /* take the last digit and count the bits in it */ - q = a->dp[a->used - 1]; - while (q > ((mp_digit) 0)) { - ++r; - q >>= ((mp_digit) 1); - } - return r; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_count_bits.c */ - -/* Start: bn_mp_div.c */ -#include <tommath.h> -#ifdef BN_MP_DIV_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -#ifdef BN_MP_DIV_SMALL - -/* slower bit-bang division... also smaller */ -int mp_div(mp_int * a, mp_int * b, mp_int * c, mp_int * d) -{ - mp_int ta, tb, tq, q; - int res, n, n2; - - /* is divisor zero ? */ - if (mp_iszero (b) == 1) { - return MP_VAL; - } - - /* if a < b then q=0, r = a */ - if (mp_cmp_mag (a, b) == MP_LT) { - if (d != NULL) { - res = mp_copy (a, d); - } else { - res = MP_OKAY; - } - if (c != NULL) { - mp_zero (c); - } - return res; - } - - /* init our temps */ - if ((res = mp_init_multi(&ta, &tb, &tq, &q, NULL) != MP_OKAY)) { - return res; - } - - - mp_set(&tq, 1); - n = mp_count_bits(a) - mp_count_bits(b); - if (((res = mp_abs(a, &ta)) != MP_OKAY) || - ((res = mp_abs(b, &tb)) != MP_OKAY) || - ((res = mp_mul_2d(&tb, n, &tb)) != MP_OKAY) || - ((res = mp_mul_2d(&tq, n, &tq)) != MP_OKAY)) { - goto LBL_ERR; - } - - while (n-- >= 0) { - if (mp_cmp(&tb, &ta) != MP_GT) { - if (((res = mp_sub(&ta, &tb, &ta)) != MP_OKAY) || - ((res = mp_add(&q, &tq, &q)) != MP_OKAY)) { - goto LBL_ERR; - } - } - if (((res = mp_div_2d(&tb, 1, &tb, NULL)) != MP_OKAY) || - ((res = mp_div_2d(&tq, 1, &tq, NULL)) != MP_OKAY)) { - goto LBL_ERR; - } - } - - /* now q == quotient and ta == remainder */ - n = a->sign; - n2 = (a->sign == b->sign ? MP_ZPOS : MP_NEG); - if (c != NULL) { - mp_exch(c, &q); - c->sign = (mp_iszero(c) == MP_YES) ? MP_ZPOS : n2; - } - if (d != NULL) { - mp_exch(d, &ta); - d->sign = (mp_iszero(d) == MP_YES) ? MP_ZPOS : n; - } -LBL_ERR: - mp_clear_multi(&ta, &tb, &tq, &q, NULL); - return res; -} - -#else - -/* integer signed division. - * c*b + d == a [e.g. a/b, c=quotient, d=remainder] - * HAC pp.598 Algorithm 14.20 - * - * Note that the description in HAC is horribly - * incomplete. For example, it doesn't consider - * the case where digits are removed from 'x' in - * the inner loop. It also doesn't consider the - * case that y has fewer than three digits, etc.. - * - * The overall algorithm is as described as - * 14.20 from HAC but fixed to treat these cases. -*/ -int mp_div (mp_int * a, mp_int * b, mp_int * c, mp_int * d) -{ - mp_int q, x, y, t1, t2; - int res, n, t, i, norm, neg; - - /* is divisor zero ? */ - if (mp_iszero (b) == 1) { - return MP_VAL; - } - - /* if a < b then q=0, r = a */ - if (mp_cmp_mag (a, b) == MP_LT) { - if (d != NULL) { - res = mp_copy (a, d); - } else { - res = MP_OKAY; - } - if (c != NULL) { - mp_zero (c); - } - return res; - } - - if ((res = mp_init_size (&q, a->used + 2)) != MP_OKAY) { - return res; - } - q.used = a->used + 2; - - if ((res = mp_init (&t1)) != MP_OKAY) { - goto LBL_Q; - } - - if ((res = mp_init (&t2)) != MP_OKAY) { - goto LBL_T1; - } - - if ((res = mp_init_copy (&x, a)) != MP_OKAY) { - goto LBL_T2; - } - - if ((res = mp_init_copy (&y, b)) != MP_OKAY) { - goto LBL_X; - } - - /* fix the sign */ - neg = (a->sign == b->sign) ? MP_ZPOS : MP_NEG; - x.sign = y.sign = MP_ZPOS; - - /* normalize both x and y, ensure that y >= b/2, [b == 2**DIGIT_BIT] */ - norm = mp_count_bits(&y) % DIGIT_BIT; - if (norm < (int)(DIGIT_BIT-1)) { - norm = (DIGIT_BIT-1) - norm; - if ((res = mp_mul_2d (&x, norm, &x)) != MP_OKAY) { - goto LBL_Y; - } - if ((res = mp_mul_2d (&y, norm, &y)) != MP_OKAY) { - goto LBL_Y; - } - } else { - norm = 0; - } - - /* note hac does 0 based, so if used==5 then its 0,1,2,3,4, e.g. use 4 */ - n = x.used - 1; - t = y.used - 1; - - /* while (x >= y*b**n-t) do { q[n-t] += 1; x -= y*b**{n-t} } */ - if ((res = mp_lshd (&y, n - t)) != MP_OKAY) { /* y = y*b**{n-t} */ - goto LBL_Y; - } - - while (mp_cmp (&x, &y) != MP_LT) { - ++(q.dp[n - t]); - if ((res = mp_sub (&x, &y, &x)) != MP_OKAY) { - goto LBL_Y; - } - } - - /* reset y by shifting it back down */ - mp_rshd (&y, n - t); - - /* step 3. for i from n down to (t + 1) */ - for (i = n; i >= (t + 1); i--) { - if (i > x.used) { - continue; - } - - /* step 3.1 if xi == yt then set q{i-t-1} to b-1, - * otherwise set q{i-t-1} to (xi*b + x{i-1})/yt */ - if (x.dp[i] == y.dp[t]) { - q.dp[i - t - 1] = ((((mp_digit)1) << DIGIT_BIT) - 1); - } else { - mp_word tmp; - tmp = ((mp_word) x.dp[i]) << ((mp_word) DIGIT_BIT); - tmp |= ((mp_word) x.dp[i - 1]); - tmp /= ((mp_word) y.dp[t]); - if (tmp > (mp_word) MP_MASK) - tmp = MP_MASK; - q.dp[i - t - 1] = (mp_digit) (tmp & (mp_word) (MP_MASK)); - } - - /* while (q{i-t-1} * (yt * b + y{t-1})) > - xi * b**2 + xi-1 * b + xi-2 - - do q{i-t-1} -= 1; - */ - q.dp[i - t - 1] = (q.dp[i - t - 1] + 1) & MP_MASK; - do { - q.dp[i - t - 1] = (q.dp[i - t - 1] - 1) & MP_MASK; - - /* find left hand */ - mp_zero (&t1); - t1.dp[0] = (t - 1 < 0) ? 0 : y.dp[t - 1]; - t1.dp[1] = y.dp[t]; - t1.used = 2; - if ((res = mp_mul_d (&t1, q.dp[i - t - 1], &t1)) != MP_OKAY) { - goto LBL_Y; - } - - /* find right hand */ - t2.dp[0] = (i - 2 < 0) ? 0 : x.dp[i - 2]; - t2.dp[1] = (i - 1 < 0) ? 0 : x.dp[i - 1]; - t2.dp[2] = x.dp[i]; - t2.used = 3; - } while (mp_cmp_mag(&t1, &t2) == MP_GT); - - /* step 3.3 x = x - q{i-t-1} * y * b**{i-t-1} */ - if ((res = mp_mul_d (&y, q.dp[i - t - 1], &t1)) != MP_OKAY) { - goto LBL_Y; - } - - if ((res = mp_lshd (&t1, i - t - 1)) != MP_OKAY) { - goto LBL_Y; - } - - if ((res = mp_sub (&x, &t1, &x)) != MP_OKAY) { - goto LBL_Y; - } - - /* if x < 0 then { x = x + y*b**{i-t-1}; q{i-t-1} -= 1; } */ - if (x.sign == MP_NEG) { - if ((res = mp_copy (&y, &t1)) != MP_OKAY) { - goto LBL_Y; - } - if ((res = mp_lshd (&t1, i - t - 1)) != MP_OKAY) { - goto LBL_Y; - } - if ((res = mp_add (&x, &t1, &x)) != MP_OKAY) { - goto LBL_Y; - } - - q.dp[i - t - 1] = (q.dp[i - t - 1] - 1UL) & MP_MASK; - } - } - - /* now q is the quotient and x is the remainder - * [which we have to normalize] - */ - - /* get sign before writing to c */ - x.sign = x.used == 0 ? MP_ZPOS : a->sign; - - if (c != NULL) { - mp_clamp (&q); - mp_exch (&q, c); - c->sign = neg; - } - - if (d != NULL) { - mp_div_2d (&x, norm, &x, NULL); - mp_exch (&x, d); - } - - res = MP_OKAY; - -LBL_Y:mp_clear (&y); -LBL_X:mp_clear (&x); -LBL_T2:mp_clear (&t2); -LBL_T1:mp_clear (&t1); -LBL_Q:mp_clear (&q); - return res; -} - -#endif - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_div.c */ - -/* Start: bn_mp_div_2.c */ -#include <tommath.h> -#ifdef BN_MP_DIV_2_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* b = a/2 */ -int mp_div_2(mp_int * a, mp_int * b) -{ - int x, res, oldused; - - /* copy */ - if (b->alloc < a->used) { - if ((res = mp_grow (b, a->used)) != MP_OKAY) { - return res; - } - } - - oldused = b->used; - b->used = a->used; - { - register mp_digit r, rr, *tmpa, *tmpb; - - /* source alias */ - tmpa = a->dp + b->used - 1; - - /* dest alias */ - tmpb = b->dp + b->used - 1; - - /* carry */ - r = 0; - for (x = b->used - 1; x >= 0; x--) { - /* get the carry for the next iteration */ - rr = *tmpa & 1; - - /* shift the current digit, add in carry and store */ - *tmpb-- = (*tmpa-- >> 1) | (r << (DIGIT_BIT - 1)); - - /* forward carry to next iteration */ - r = rr; - } - - /* zero excess digits */ - tmpb = b->dp + b->used; - for (x = b->used; x < oldused; x++) { - *tmpb++ = 0; - } - } - b->sign = a->sign; - mp_clamp (b); - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_div_2.c */ - -/* Start: bn_mp_div_2d.c */ -#include <tommath.h> -#ifdef BN_MP_DIV_2D_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* shift right by a certain bit count (store quotient in c, optional remainder in d) */ -int mp_div_2d (mp_int * a, int b, mp_int * c, mp_int * d) -{ - mp_digit D, r, rr; - int x, res; - mp_int t; - - - /* if the shift count is <= 0 then we do no work */ - if (b <= 0) { - res = mp_copy (a, c); - if (d != NULL) { - mp_zero (d); - } - return res; - } - - if ((res = mp_init (&t)) != MP_OKAY) { - return res; - } - - /* get the remainder */ - if (d != NULL) { - if ((res = mp_mod_2d (a, b, &t)) != MP_OKAY) { - mp_clear (&t); - return res; - } - } - - /* copy */ - if ((res = mp_copy (a, c)) != MP_OKAY) { - mp_clear (&t); - return res; - } - - /* shift by as many digits in the bit count */ - if (b >= (int)DIGIT_BIT) { - mp_rshd (c, b / DIGIT_BIT); - } - - /* shift any bit count < DIGIT_BIT */ - D = (mp_digit) (b % DIGIT_BIT); - if (D != 0) { - register mp_digit *tmpc, mask, shift; - - /* mask */ - mask = (((mp_digit)1) << D) - 1; - - /* shift for lsb */ - shift = DIGIT_BIT - D; - - /* alias */ - tmpc = c->dp + (c->used - 1); - - /* carry */ - r = 0; - for (x = c->used - 1; x >= 0; x--) { - /* get the lower bits of this word in a temp */ - rr = *tmpc & mask; - - /* shift the current word and mix in the carry bits from the previous word */ - *tmpc = (*tmpc >> D) | (r << shift); - --tmpc; - - /* set the carry to the carry bits of the current word found above */ - r = rr; - } - } - mp_clamp (c); - if (d != NULL) { - mp_exch (&t, d); - } - mp_clear (&t); - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_div_2d.c */ - -/* Start: bn_mp_div_3.c */ -#include <tommath.h> -#ifdef BN_MP_DIV_3_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* divide by three (based on routine from MPI and the GMP manual) */ -int -mp_div_3 (mp_int * a, mp_int *c, mp_digit * d) -{ - mp_int q; - mp_word w, t; - mp_digit b; - int res, ix; - - /* b = 2**DIGIT_BIT / 3 */ - b = (((mp_word)1) << ((mp_word)DIGIT_BIT)) / ((mp_word)3); - - if ((res = mp_init_size(&q, a->used)) != MP_OKAY) { - return res; - } - - q.used = a->used; - q.sign = a->sign; - w = 0; - for (ix = a->used - 1; ix >= 0; ix--) { - w = (w << ((mp_word)DIGIT_BIT)) | ((mp_word)a->dp[ix]); - - if (w >= 3) { - /* multiply w by [1/3] */ - t = (w * ((mp_word)b)) >> ((mp_word)DIGIT_BIT); - - /* now subtract 3 * [w/3] from w, to get the remainder */ - w -= t+t+t; - - /* fixup the remainder as required since - * the optimization is not exact. - */ - while (w >= 3) { - t += 1; - w -= 3; - } - } else { - t = 0; - } - q.dp[ix] = (mp_digit)t; - } - - /* [optional] store the remainder */ - if (d != NULL) { - *d = (mp_digit)w; - } - - /* [optional] store the quotient */ - if (c != NULL) { - mp_clamp(&q); - mp_exch(&q, c); - } - mp_clear(&q); - - return res; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_div_3.c */ - -/* Start: bn_mp_div_d.c */ -#include <tommath.h> -#ifdef BN_MP_DIV_D_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -static int s_is_power_of_two(mp_digit b, int *p) -{ - int x; - - /* fast return if no power of two */ - if ((b==0) || (b & (b-1))) { - return 0; - } - - for (x = 0; x < DIGIT_BIT; x++) { - if (b == (((mp_digit)1)<<x)) { - *p = x; - return 1; - } - } - return 0; -} - -/* single digit division (based on routine from MPI) */ -int mp_div_d (mp_int * a, mp_digit b, mp_int * c, mp_digit * d) -{ - mp_int q; - mp_word w; - mp_digit t; - int res, ix; - - /* cannot divide by zero */ - if (b == 0) { - return MP_VAL; - } - - /* quick outs */ - if (b == 1 || mp_iszero(a) == 1) { - if (d != NULL) { - *d = 0; - } - if (c != NULL) { - return mp_copy(a, c); - } - return MP_OKAY; - } - - /* power of two ? */ - if (s_is_power_of_two(b, &ix) == 1) { - if (d != NULL) { - *d = a->dp[0] & ((((mp_digit)1)<<ix) - 1); - } - if (c != NULL) { - return mp_div_2d(a, ix, c, NULL); - } - return MP_OKAY; - } - -#ifdef BN_MP_DIV_3_C - /* three? */ - if (b == 3) { - return mp_div_3(a, c, d); - } -#endif - - /* no easy answer [c'est la vie]. Just division */ - if ((res = mp_init_size(&q, a->used)) != MP_OKAY) { - return res; - } - - q.used = a->used; - q.sign = a->sign; - w = 0; - for (ix = a->used - 1; ix >= 0; ix--) { - w = (w << ((mp_word)DIGIT_BIT)) | ((mp_word)a->dp[ix]); - - if (w >= b) { - t = (mp_digit)(w / b); - w -= ((mp_word)t) * ((mp_word)b); - } else { - t = 0; - } - q.dp[ix] = (mp_digit)t; - } - - if (d != NULL) { - *d = (mp_digit)w; - } - - if (c != NULL) { - mp_clamp(&q); - mp_exch(&q, c); - } - mp_clear(&q); - - return res; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_div_d.c */ - -/* Start: bn_mp_dr_is_modulus.c */ -#include <tommath.h> -#ifdef BN_MP_DR_IS_MODULUS_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* determines if a number is a valid DR modulus */ -int mp_dr_is_modulus(mp_int *a) -{ - int ix; - - /* must be at least two digits */ - if (a->used < 2) { - return 0; - } - - /* must be of the form b**k - a [a <= b] so all - * but the first digit must be equal to -1 (mod b). - */ - for (ix = 1; ix < a->used; ix++) { - if (a->dp[ix] != MP_MASK) { - return 0; - } - } - return 1; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_dr_is_modulus.c */ - -/* Start: bn_mp_dr_reduce.c */ -#include <tommath.h> -#ifdef BN_MP_DR_REDUCE_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* reduce "x" in place modulo "n" using the Diminished Radix algorithm. - * - * Based on algorithm from the paper - * - * "Generating Efficient Primes for Discrete Log Cryptosystems" - * Chae Hoon Lim, Pil Joong Lee, - * POSTECH Information Research Laboratories - * - * The modulus must be of a special format [see manual] - * - * Has been modified to use algorithm 7.10 from the LTM book instead - * - * Input x must be in the range 0 <= x <= (n-1)**2 - */ -int -mp_dr_reduce (mp_int * x, mp_int * n, mp_digit k) -{ - int err, i, m; - mp_word r; - mp_digit mu, *tmpx1, *tmpx2; - - /* m = digits in modulus */ - m = n->used; - - /* ensure that "x" has at least 2m digits */ - if (x->alloc < m + m) { - if ((err = mp_grow (x, m + m)) != MP_OKAY) { - return err; - } - } - -/* top of loop, this is where the code resumes if - * another reduction pass is required. - */ -top: - /* aliases for digits */ - /* alias for lower half of x */ - tmpx1 = x->dp; - - /* alias for upper half of x, or x/B**m */ - tmpx2 = x->dp + m; - - /* set carry to zero */ - mu = 0; - - /* compute (x mod B**m) + k * [x/B**m] inline and inplace */ - for (i = 0; i < m; i++) { - r = ((mp_word)*tmpx2++) * ((mp_word)k) + *tmpx1 + mu; - *tmpx1++ = (mp_digit)(r & MP_MASK); - mu = (mp_digit)(r >> ((mp_word)DIGIT_BIT)); - } - - /* set final carry */ - *tmpx1++ = mu; - - /* zero words above m */ - for (i = m + 1; i < x->used; i++) { - *tmpx1++ = 0; - } - - /* clamp, sub and return */ - mp_clamp (x); - - /* if x >= n then subtract and reduce again - * Each successive "recursion" makes the input smaller and smaller. - */ - if (mp_cmp_mag (x, n) != MP_LT) { - s_mp_sub(x, n, x); - goto top; - } - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_dr_reduce.c */ - -/* Start: bn_mp_dr_setup.c */ -#include <tommath.h> -#ifdef BN_MP_DR_SETUP_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* determines the setup value */ -void mp_dr_setup(mp_int *a, mp_digit *d) -{ - /* the casts are required if DIGIT_BIT is one less than - * the number of bits in a mp_digit [e.g. DIGIT_BIT==31] - */ - *d = (mp_digit)((((mp_word)1) << ((mp_word)DIGIT_BIT)) - - ((mp_word)a->dp[0])); -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_dr_setup.c */ - -/* Start: bn_mp_exch.c */ -#include <tommath.h> -#ifdef BN_MP_EXCH_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* swap the elements of two integers, for cases where you can't simply swap the - * mp_int pointers around - */ -void -mp_exch (mp_int * a, mp_int * b) -{ - mp_int t; - - t = *a; - *a = *b; - *b = t; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_exch.c */ - -/* Start: bn_mp_expt_d.c */ -#include <tommath.h> -#ifdef BN_MP_EXPT_D_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* calculate c = a**b using a square-multiply algorithm */ -int mp_expt_d (mp_int * a, mp_digit b, mp_int * c) -{ - int res, x; - mp_int g; - - if ((res = mp_init_copy (&g, a)) != MP_OKAY) { - return res; - } - - /* set initial result */ - mp_set (c, 1); - - for (x = 0; x < (int) DIGIT_BIT; x++) { - /* square */ - if ((res = mp_sqr (c, c)) != MP_OKAY) { - mp_clear (&g); - return res; - } - - /* if the bit is set multiply */ - if ((b & (mp_digit) (((mp_digit)1) << (DIGIT_BIT - 1))) != 0) { - if ((res = mp_mul (c, &g, c)) != MP_OKAY) { - mp_clear (&g); - return res; - } - } - - /* shift to next bit */ - b <<= 1; - } - - mp_clear (&g); - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_expt_d.c */ - -/* Start: bn_mp_exptmod.c */ -#include <tommath.h> -#ifdef BN_MP_EXPTMOD_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - - -/* this is a shell function that calls either the normal or Montgomery - * exptmod functions. Originally the call to the montgomery code was - * embedded in the normal function but that wasted alot of stack space - * for nothing (since 99% of the time the Montgomery code would be called) - */ -int mp_exptmod (mp_int * G, mp_int * X, mp_int * P, mp_int * Y) -{ - int dr; - - /* modulus P must be positive */ - if (P->sign == MP_NEG) { - return MP_VAL; - } - - /* if exponent X is negative we have to recurse */ - if (X->sign == MP_NEG) { -#ifdef BN_MP_INVMOD_C - mp_int tmpG, tmpX; - int err; - - /* first compute 1/G mod P */ - if ((err = mp_init(&tmpG)) != MP_OKAY) { - return err; - } - if ((err = mp_invmod(G, P, &tmpG)) != MP_OKAY) { - mp_clear(&tmpG); - return err; - } - - /* now get |X| */ - if ((err = mp_init(&tmpX)) != MP_OKAY) { - mp_clear(&tmpG); - return err; - } - if ((err = mp_abs(X, &tmpX)) != MP_OKAY) { - mp_clear_multi(&tmpG, &tmpX, NULL); - return err; - } - - /* and now compute (1/G)**|X| instead of G**X [X < 0] */ - err = mp_exptmod(&tmpG, &tmpX, P, Y); - mp_clear_multi(&tmpG, &tmpX, NULL); - return err; -#else - /* no invmod */ - return MP_VAL; -#endif - } - -/* modified diminished radix reduction */ -#if defined(BN_MP_REDUCE_IS_2K_L_C) && defined(BN_MP_REDUCE_2K_L_C) && defined(BN_S_MP_EXPTMOD_C) - if (mp_reduce_is_2k_l(P) == MP_YES) { - return s_mp_exptmod(G, X, P, Y, 1); - } -#endif - -#ifdef BN_MP_DR_IS_MODULUS_C - /* is it a DR modulus? */ - dr = mp_dr_is_modulus(P); -#else - /* default to no */ - dr = 0; -#endif - -#ifdef BN_MP_REDUCE_IS_2K_C - /* if not, is it a unrestricted DR modulus? */ - if (dr == 0) { - dr = mp_reduce_is_2k(P) << 1; - } -#endif - - /* if the modulus is odd or dr != 0 use the montgomery method */ -#ifdef BN_MP_EXPTMOD_FAST_C - if (mp_isodd (P) == 1 || dr != 0) { - return mp_exptmod_fast (G, X, P, Y, dr); - } else { -#endif -#ifdef BN_S_MP_EXPTMOD_C - /* otherwise use the generic Barrett reduction technique */ - return s_mp_exptmod (G, X, P, Y, 0); -#else - /* no exptmod for evens */ - return MP_VAL; -#endif -#ifdef BN_MP_EXPTMOD_FAST_C - } -#endif -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_exptmod.c */ - -/* Start: bn_mp_exptmod_fast.c */ -#include <tommath.h> -#ifdef BN_MP_EXPTMOD_FAST_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* computes Y == G**X mod P, HAC pp.616, Algorithm 14.85 - * - * Uses a left-to-right k-ary sliding window to compute the modular exponentiation. - * The value of k changes based on the size of the exponent. - * - * Uses Montgomery or Diminished Radix reduction [whichever appropriate] - */ - -#ifdef MP_LOW_MEM - #define TAB_SIZE 32 -#else - #define TAB_SIZE 256 -#endif - -int mp_exptmod_fast (mp_int * G, mp_int * X, mp_int * P, mp_int * Y, int redmode) -{ - mp_int M[TAB_SIZE], res; - mp_digit buf, mp; - int err, bitbuf, bitcpy, bitcnt, mode, digidx, x, y, winsize; - - /* use a pointer to the reduction algorithm. This allows us to use - * one of many reduction algorithms without modding the guts of - * the code with if statements everywhere. - */ - int (*redux)(mp_int*,mp_int*,mp_digit); - - /* find window size */ - x = mp_count_bits (X); - if (x <= 7) { - winsize = 2; - } else if (x <= 36) { - winsize = 3; - } else if (x <= 140) { - winsize = 4; - } else if (x <= 450) { - winsize = 5; - } else if (x <= 1303) { - winsize = 6; - } else if (x <= 3529) { - winsize = 7; - } else { - winsize = 8; - } - -#ifdef MP_LOW_MEM - if (winsize > 5) { - winsize = 5; - } -#endif - - /* init M array */ - /* init first cell */ - if ((err = mp_init(&M[1])) != MP_OKAY) { - return err; - } - - /* now init the second half of the array */ - for (x = 1<<(winsize-1); x < (1 << winsize); x++) { - if ((err = mp_init(&M[x])) != MP_OKAY) { - for (y = 1<<(winsize-1); y < x; y++) { - mp_clear (&M[y]); - } - mp_clear(&M[1]); - return err; - } - } - - /* determine and setup reduction code */ - if (redmode == 0) { -#ifdef BN_MP_MONTGOMERY_SETUP_C - /* now setup montgomery */ - if ((err = mp_montgomery_setup (P, &mp)) != MP_OKAY) { - goto LBL_M; - } -#else - err = MP_VAL; - goto LBL_M; -#endif - - /* automatically pick the comba one if available (saves quite a few calls/ifs) */ -#ifdef BN_FAST_MP_MONTGOMERY_REDUCE_C - if (((P->used * 2 + 1) < MP_WARRAY) && - P->used < (1 << ((CHAR_BIT * sizeof (mp_word)) - (2 * DIGIT_BIT)))) { - redux = fast_mp_montgomery_reduce; - } else -#endif - { -#ifdef BN_MP_MONTGOMERY_REDUCE_C - /* use slower baseline Montgomery method */ - redux = mp_montgomery_reduce; -#else - err = MP_VAL; - goto LBL_M; -#endif - } - } else if (redmode == 1) { -#if defined(BN_MP_DR_SETUP_C) && defined(BN_MP_DR_REDUCE_C) - /* setup DR reduction for moduli of the form B**k - b */ - mp_dr_setup(P, &mp); - redux = mp_dr_reduce; -#else - err = MP_VAL; - goto LBL_M; -#endif - } else { -#if defined(BN_MP_REDUCE_2K_SETUP_C) && defined(BN_MP_REDUCE_2K_C) - /* setup DR reduction for moduli of the form 2**k - b */ - if ((err = mp_reduce_2k_setup(P, &mp)) != MP_OKAY) { - goto LBL_M; - } - redux = mp_reduce_2k; -#else - err = MP_VAL; - goto LBL_M; -#endif - } - - /* setup result */ - if ((err = mp_init (&res)) != MP_OKAY) { - goto LBL_M; - } - - /* create M table - * - - * - * The first half of the table is not computed though accept for M[0] and M[1] - */ - - if (redmode == 0) { -#ifdef BN_MP_MONTGOMERY_CALC_NORMALIZATION_C - /* now we need R mod m */ - if ((err = mp_montgomery_calc_normalization (&res, P)) != MP_OKAY) { - goto LBL_RES; - } -#else - err = MP_VAL; - goto LBL_RES; -#endif - - /* now set M[1] to G * R mod m */ - if ((err = mp_mulmod (G, &res, P, &M[1])) != MP_OKAY) { - goto LBL_RES; - } - } else { - mp_set(&res, 1); - if ((err = mp_mod(G, P, &M[1])) != MP_OKAY) { - goto LBL_RES; - } - } - - /* compute the value at M[1<<(winsize-1)] by squaring M[1] (winsize-1) times */ - if ((err = mp_copy (&M[1], &M[1 << (winsize - 1)])) != MP_OKAY) { - goto LBL_RES; - } - - for (x = 0; x < (winsize - 1); x++) { - if ((err = mp_sqr (&M[1 << (winsize - 1)], &M[1 << (winsize - 1)])) != MP_OKAY) { - goto LBL_RES; - } - if ((err = redux (&M[1 << (winsize - 1)], P, mp)) != MP_OKAY) { - goto LBL_RES; - } - } - - /* create upper table */ - for (x = (1 << (winsize - 1)) + 1; x < (1 << winsize); x++) { - if ((err = mp_mul (&M[x - 1], &M[1], &M[x])) != MP_OKAY) { - goto LBL_RES; - } - if ((err = redux (&M[x], P, mp)) != MP_OKAY) { - goto LBL_RES; - } - } - - /* set initial mode and bit cnt */ - mode = 0; - bitcnt = 1; - buf = 0; - digidx = X->used - 1; - bitcpy = 0; - bitbuf = 0; - - for (;;) { - /* grab next digit as required */ - if (--bitcnt == 0) { - /* if digidx == -1 we are out of digits so break */ - if (digidx == -1) { - break; - } - /* read next digit and reset bitcnt */ - buf = X->dp[digidx--]; - bitcnt = (int)DIGIT_BIT; - } - - /* grab the next msb from the exponent */ - y = (mp_digit)(buf >> (DIGIT_BIT - 1)) & 1; - buf <<= (mp_digit)1; - - /* if the bit is zero and mode == 0 then we ignore it - * These represent the leading zero bits before the first 1 bit - * in the exponent. Technically this opt is not required but it - * does lower the # of trivial squaring/reductions used - */ - if (mode == 0 && y == 0) { - continue; - } - - /* if the bit is zero and mode == 1 then we square */ - if (mode == 1 && y == 0) { - if ((err = mp_sqr (&res, &res)) != MP_OKAY) { - goto LBL_RES; - } - if ((err = redux (&res, P, mp)) != MP_OKAY) { - goto LBL_RES; - } - continue; - } - - /* else we add it to the window */ - bitbuf |= (y << (winsize - ++bitcpy)); - mode = 2; - - if (bitcpy == winsize) { - /* ok window is filled so square as required and multiply */ - /* square first */ - for (x = 0; x < winsize; x++) { - if ((err = mp_sqr (&res, &res)) != MP_OKAY) { - goto LBL_RES; - } - if ((err = redux (&res, P, mp)) != MP_OKAY) { - goto LBL_RES; - } - } - - /* then multiply */ - if ((err = mp_mul (&res, &M[bitbuf], &res)) != MP_OKAY) { - goto LBL_RES; - } - if ((err = redux (&res, P, mp)) != MP_OKAY) { - goto LBL_RES; - } - - /* empty window and reset */ - bitcpy = 0; - bitbuf = 0; - mode = 1; - } - } - - /* if bits remain then square/multiply */ - if (mode == 2 && bitcpy > 0) { - /* square then multiply if the bit is set */ - for (x = 0; x < bitcpy; x++) { - if ((err = mp_sqr (&res, &res)) != MP_OKAY) { - goto LBL_RES; - } - if ((err = redux (&res, P, mp)) != MP_OKAY) { - goto LBL_RES; - } - - /* get next bit of the window */ - bitbuf <<= 1; - if ((bitbuf & (1 << winsize)) != 0) { - /* then multiply */ - if ((err = mp_mul (&res, &M[1], &res)) != MP_OKAY) { - goto LBL_RES; - } - if ((err = redux (&res, P, mp)) != MP_OKAY) { - goto LBL_RES; - } - } - } - } - - if (redmode == 0) { - /* fixup result if Montgomery reduction is used - * recall that any value in a Montgomery system is - * actually multiplied by R mod n. So we have - * to reduce one more time to cancel out the factor - * of R. - */ - if ((err = redux(&res, P, mp)) != MP_OKAY) { - goto LBL_RES; - } - } - - /* swap res with Y */ - mp_exch (&res, Y); - err = MP_OKAY; -LBL_RES:mp_clear (&res); -LBL_M: - mp_clear(&M[1]); - for (x = 1<<(winsize-1); x < (1 << winsize); x++) { - mp_clear (&M[x]); - } - return err; -} -#endif - - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_exptmod_fast.c */ - -/* Start: bn_mp_exteuclid.c */ -#include <tommath.h> -#ifdef BN_MP_EXTEUCLID_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* Extended euclidean algorithm of (a, b) produces - a*u1 + b*u2 = u3 - */ -int mp_exteuclid(mp_int *a, mp_int *b, mp_int *U1, mp_int *U2, mp_int *U3) -{ - mp_int u1,u2,u3,v1,v2,v3,t1,t2,t3,q,tmp; - int err; - - if ((err = mp_init_multi(&u1, &u2, &u3, &v1, &v2, &v3, &t1, &t2, &t3, &q, &tmp, NULL)) != MP_OKAY) { - return err; - } - - /* initialize, (u1,u2,u3) = (1,0,a) */ - mp_set(&u1, 1); - if ((err = mp_copy(a, &u3)) != MP_OKAY) { goto _ERR; } - - /* initialize, (v1,v2,v3) = (0,1,b) */ - mp_set(&v2, 1); - if ((err = mp_copy(b, &v3)) != MP_OKAY) { goto _ERR; } - - /* loop while v3 != 0 */ - while (mp_iszero(&v3) == MP_NO) { - /* q = u3/v3 */ - if ((err = mp_div(&u3, &v3, &q, NULL)) != MP_OKAY) { goto _ERR; } - - /* (t1,t2,t3) = (u1,u2,u3) - (v1,v2,v3)q */ - if ((err = mp_mul(&v1, &q, &tmp)) != MP_OKAY) { goto _ERR; } - if ((err = mp_sub(&u1, &tmp, &t1)) != MP_OKAY) { goto _ERR; } - if ((err = mp_mul(&v2, &q, &tmp)) != MP_OKAY) { goto _ERR; } - if ((err = mp_sub(&u2, &tmp, &t2)) != MP_OKAY) { goto _ERR; } - if ((err = mp_mul(&v3, &q, &tmp)) != MP_OKAY) { goto _ERR; } - if ((err = mp_sub(&u3, &tmp, &t3)) != MP_OKAY) { goto _ERR; } - - /* (u1,u2,u3) = (v1,v2,v3) */ - if ((err = mp_copy(&v1, &u1)) != MP_OKAY) { goto _ERR; } - if ((err = mp_copy(&v2, &u2)) != MP_OKAY) { goto _ERR; } - if ((err = mp_copy(&v3, &u3)) != MP_OKAY) { goto _ERR; } - - /* (v1,v2,v3) = (t1,t2,t3) */ - if ((err = mp_copy(&t1, &v1)) != MP_OKAY) { goto _ERR; } - if ((err = mp_copy(&t2, &v2)) != MP_OKAY) { goto _ERR; } - if ((err = mp_copy(&t3, &v3)) != MP_OKAY) { goto _ERR; } - } - - /* make sure U3 >= 0 */ - if (u3.sign == MP_NEG) { - mp_neg(&u1, &u1); - mp_neg(&u2, &u2); - mp_neg(&u3, &u3); - } - - /* copy result out */ - if (U1 != NULL) { mp_exch(U1, &u1); } - if (U2 != NULL) { mp_exch(U2, &u2); } - if (U3 != NULL) { mp_exch(U3, &u3); } - - err = MP_OKAY; -_ERR: mp_clear_multi(&u1, &u2, &u3, &v1, &v2, &v3, &t1, &t2, &t3, &q, &tmp, NULL); - return err; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_exteuclid.c */ - -/* Start: bn_mp_fread.c */ -#include <tommath.h> -#ifdef BN_MP_FREAD_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* read a bigint from a file stream in ASCII */ -int mp_fread(mp_int *a, int radix, FILE *stream) -{ - int err, ch, neg, y; - - /* clear a */ - mp_zero(a); - - /* if first digit is - then set negative */ - ch = fgetc(stream); - if (ch == '-') { - neg = MP_NEG; - ch = fgetc(stream); - } else { - neg = MP_ZPOS; - } - - for (;;) { - /* find y in the radix map */ - for (y = 0; y < radix; y++) { - if (mp_s_rmap[y] == ch) { - break; - } - } - if (y == radix) { - break; - } - - /* shift up and add */ - if ((err = mp_mul_d(a, radix, a)) != MP_OKAY) { - return err; - } - if ((err = mp_add_d(a, y, a)) != MP_OKAY) { - return err; - } - - ch = fgetc(stream); - } - if (mp_cmp_d(a, 0) != MP_EQ) { - a->sign = neg; - } - - return MP_OKAY; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_fread.c */ - -/* Start: bn_mp_fwrite.c */ -#include <tommath.h> -#ifdef BN_MP_FWRITE_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -int mp_fwrite(mp_int *a, int radix, FILE *stream) -{ - char *buf; - int err, len, x; - - if ((err = mp_radix_size(a, radix, &len)) != MP_OKAY) { - return err; - } - - buf = OPT_CAST(char) XMALLOC (len); - if (buf == NULL) { - return MP_MEM; - } - - if ((err = mp_toradix(a, buf, radix)) != MP_OKAY) { - XFREE (buf); - return err; - } - - for (x = 0; x < len; x++) { - if (fputc(buf[x], stream) == EOF) { - XFREE (buf); - return MP_VAL; - } - } - - XFREE (buf); - return MP_OKAY; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_fwrite.c */ - -/* Start: bn_mp_gcd.c */ -#include <tommath.h> -#ifdef BN_MP_GCD_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* Greatest Common Divisor using the binary method */ -int mp_gcd (mp_int * a, mp_int * b, mp_int * c) -{ - mp_int u, v; - int k, u_lsb, v_lsb, res; - - /* either zero than gcd is the largest */ - if (mp_iszero (a) == MP_YES) { - return mp_abs (b, c); - } - if (mp_iszero (b) == MP_YES) { - return mp_abs (a, c); - } - - /* get copies of a and b we can modify */ - if ((res = mp_init_copy (&u, a)) != MP_OKAY) { - return res; - } - - if ((res = mp_init_copy (&v, b)) != MP_OKAY) { - goto LBL_U; - } - - /* must be positive for the remainder of the algorithm */ - u.sign = v.sign = MP_ZPOS; - - /* B1. Find the common power of two for u and v */ - u_lsb = mp_cnt_lsb(&u); - v_lsb = mp_cnt_lsb(&v); - k = MIN(u_lsb, v_lsb); - - if (k > 0) { - /* divide the power of two out */ - if ((res = mp_div_2d(&u, k, &u, NULL)) != MP_OKAY) { - goto LBL_V; - } - - if ((res = mp_div_2d(&v, k, &v, NULL)) != MP_OKAY) { - goto LBL_V; - } - } - - /* divide any remaining factors of two out */ - if (u_lsb != k) { - if ((res = mp_div_2d(&u, u_lsb - k, &u, NULL)) != MP_OKAY) { - goto LBL_V; - } - } - - if (v_lsb != k) { - if ((res = mp_div_2d(&v, v_lsb - k, &v, NULL)) != MP_OKAY) { - goto LBL_V; - } - } - - while (mp_iszero(&v) == 0) { - /* make sure v is the largest */ - if (mp_cmp_mag(&u, &v) == MP_GT) { - /* swap u and v to make sure v is >= u */ - mp_exch(&u, &v); - } - - /* subtract smallest from largest */ - if ((res = s_mp_sub(&v, &u, &v)) != MP_OKAY) { - goto LBL_V; - } - - /* Divide out all factors of two */ - if ((res = mp_div_2d(&v, mp_cnt_lsb(&v), &v, NULL)) != MP_OKAY) { - goto LBL_V; - } - } - - /* multiply by 2**k which we divided out at the beginning */ - if ((res = mp_mul_2d (&u, k, c)) != MP_OKAY) { - goto LBL_V; - } - c->sign = MP_ZPOS; - res = MP_OKAY; -LBL_V:mp_clear (&u); -LBL_U:mp_clear (&v); - return res; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_gcd.c */ - -/* Start: bn_mp_get_int.c */ -#include <tommath.h> -#ifdef BN_MP_GET_INT_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* get the lower 32-bits of an mp_int */ -unsigned long mp_get_int(mp_int * a) -{ - int i; - unsigned long res; - - if (a->used == 0) { - return 0; - } - - /* get number of digits of the lsb we have to read */ - i = MIN(a->used,(int)((sizeof(unsigned long)*CHAR_BIT+DIGIT_BIT-1)/DIGIT_BIT))-1; - - /* get most significant digit of result */ - res = DIGIT(a,i); - - while (--i >= 0) { - res = (res << DIGIT_BIT) | DIGIT(a,i); - } - - /* force result to 32-bits always so it is consistent on non 32-bit platforms */ - return res & 0xFFFFFFFFUL; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_get_int.c */ - -/* Start: bn_mp_grow.c */ -#include <tommath.h> -#ifdef BN_MP_GROW_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* grow as required */ -int mp_grow (mp_int * a, int size) -{ - int i; - mp_digit *tmp; - - /* if the alloc size is smaller alloc more ram */ - if (a->alloc < size) { - /* ensure there are always at least MP_PREC digits extra on top */ - size += (MP_PREC * 2) - (size % MP_PREC); - - /* reallocate the array a->dp - * - * We store the return in a temporary variable - * in case the operation failed we don't want - * to overwrite the dp member of a. - */ - tmp = OPT_CAST(mp_digit) XREALLOC (a->dp, sizeof (mp_digit) * size); - if (tmp == NULL) { - /* reallocation failed but "a" is still valid [can be freed] */ - return MP_MEM; - } - - /* reallocation succeeded so set a->dp */ - a->dp = tmp; - - /* zero excess digits */ - i = a->alloc; - a->alloc = size; - for (; i < a->alloc; i++) { - a->dp[i] = 0; - } - } - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_grow.c */ - -/* Start: bn_mp_init.c */ -#include <tommath.h> -#ifdef BN_MP_INIT_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* init a new mp_int */ -int mp_init (mp_int * a) -{ - int i; - - /* allocate memory required and clear it */ - a->dp = OPT_CAST(mp_digit) XMALLOC (sizeof (mp_digit) * MP_PREC); - if (a->dp == NULL) { - return MP_MEM; - } - - /* set the digits to zero */ - for (i = 0; i < MP_PREC; i++) { - a->dp[i] = 0; - } - - /* set the used to zero, allocated digits to the default precision - * and sign to positive */ - a->used = 0; - a->alloc = MP_PREC; - a->sign = MP_ZPOS; - - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_init.c */ - -/* Start: bn_mp_init_copy.c */ -#include <tommath.h> -#ifdef BN_MP_INIT_COPY_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* creates "a" then copies b into it */ -int mp_init_copy (mp_int * a, mp_int * b) -{ - int res; - - if ((res = mp_init (a)) != MP_OKAY) { - return res; - } - return mp_copy (b, a); -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_init_copy.c */ - -/* Start: bn_mp_init_multi.c */ -#include <tommath.h> -#ifdef BN_MP_INIT_MULTI_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ -#include <stdarg.h> - -int mp_init_multi(mp_int *mp, ...) -{ - mp_err res = MP_OKAY; /* Assume ok until proven otherwise */ - int n = 0; /* Number of ok inits */ - mp_int* cur_arg = mp; - va_list args; - - va_start(args, mp); /* init args to next argument from caller */ - while (cur_arg != NULL) { - if (mp_init(cur_arg) != MP_OKAY) { - /* Oops - error! Back-track and mp_clear what we already - succeeded in init-ing, then return error. - */ - va_list clean_args; - - /* end the current list */ - va_end(args); - - /* now start cleaning up */ - cur_arg = mp; - va_start(clean_args, mp); - while (n--) { - mp_clear(cur_arg); - cur_arg = va_arg(clean_args, mp_int*); - } - va_end(clean_args); - res = MP_MEM; - break; - } - n++; - cur_arg = va_arg(args, mp_int*); - } - va_end(args); - return res; /* Assumed ok, if error flagged above. */ -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_init_multi.c */ - -/* Start: bn_mp_init_set.c */ -#include <tommath.h> -#ifdef BN_MP_INIT_SET_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* initialize and set a digit */ -int mp_init_set (mp_int * a, mp_digit b) -{ - int err; - if ((err = mp_init(a)) != MP_OKAY) { - return err; - } - mp_set(a, b); - return err; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_init_set.c */ - -/* Start: bn_mp_init_set_int.c */ -#include <tommath.h> -#ifdef BN_MP_INIT_SET_INT_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* initialize and set a digit */ -int mp_init_set_int (mp_int * a, unsigned long b) -{ - int err; - if ((err = mp_init(a)) != MP_OKAY) { - return err; - } - return mp_set_int(a, b); -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_init_set_int.c */ - -/* Start: bn_mp_init_size.c */ -#include <tommath.h> -#ifdef BN_MP_INIT_SIZE_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* init an mp_init for a given size */ -int mp_init_size (mp_int * a, int size) -{ - int x; - - /* pad size so there are always extra digits */ - size += (MP_PREC * 2) - (size % MP_PREC); - - /* alloc mem */ - a->dp = OPT_CAST(mp_digit) XMALLOC (sizeof (mp_digit) * size); - if (a->dp == NULL) { - return MP_MEM; - } - - /* set the members */ - a->used = 0; - a->alloc = size; - a->sign = MP_ZPOS; - - /* zero the digits */ - for (x = 0; x < size; x++) { - a->dp[x] = 0; - } - - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_init_size.c */ - -/* Start: bn_mp_invmod.c */ -#include <tommath.h> -#ifdef BN_MP_INVMOD_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* hac 14.61, pp608 */ -int mp_invmod (mp_int * a, mp_int * b, mp_int * c) -{ - /* b cannot be negative */ - if (b->sign == MP_NEG || mp_iszero(b) == 1) { - return MP_VAL; - } - -#ifdef BN_FAST_MP_INVMOD_C - /* if the modulus is odd we can use a faster routine instead */ - if (mp_isodd (b) == 1) { - return fast_mp_invmod (a, b, c); - } -#endif - -#ifdef BN_MP_INVMOD_SLOW_C - return mp_invmod_slow(a, b, c); -#endif - - return MP_VAL; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_invmod.c */ - -/* Start: bn_mp_invmod_slow.c */ -#include <tommath.h> -#ifdef BN_MP_INVMOD_SLOW_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* hac 14.61, pp608 */ -int mp_invmod_slow (mp_int * a, mp_int * b, mp_int * c) -{ - mp_int x, y, u, v, A, B, C, D; - int res; - - /* b cannot be negative */ - if (b->sign == MP_NEG || mp_iszero(b) == 1) { - return MP_VAL; - } - - /* init temps */ - if ((res = mp_init_multi(&x, &y, &u, &v, - &A, &B, &C, &D, NULL)) != MP_OKAY) { - return res; - } - - /* x = a, y = b */ - if ((res = mp_mod(a, b, &x)) != MP_OKAY) { - goto LBL_ERR; - } - if ((res = mp_copy (b, &y)) != MP_OKAY) { - goto LBL_ERR; - } - - /* 2. [modified] if x,y are both even then return an error! */ - if (mp_iseven (&x) == 1 && mp_iseven (&y) == 1) { - res = MP_VAL; - goto LBL_ERR; - } - - /* 3. u=x, v=y, A=1, B=0, C=0,D=1 */ - if ((res = mp_copy (&x, &u)) != MP_OKAY) { - goto LBL_ERR; - } - if ((res = mp_copy (&y, &v)) != MP_OKAY) { - goto LBL_ERR; - } - mp_set (&A, 1); - mp_set (&D, 1); - -top: - /* 4. while u is even do */ - while (mp_iseven (&u) == 1) { - /* 4.1 u = u/2 */ - if ((res = mp_div_2 (&u, &u)) != MP_OKAY) { - goto LBL_ERR; - } - /* 4.2 if A or B is odd then */ - if (mp_isodd (&A) == 1 || mp_isodd (&B) == 1) { - /* A = (A+y)/2, B = (B-x)/2 */ - if ((res = mp_add (&A, &y, &A)) != MP_OKAY) { - goto LBL_ERR; - } - if ((res = mp_sub (&B, &x, &B)) != MP_OKAY) { - goto LBL_ERR; - } - } - /* A = A/2, B = B/2 */ - if ((res = mp_div_2 (&A, &A)) != MP_OKAY) { - goto LBL_ERR; - } - if ((res = mp_div_2 (&B, &B)) != MP_OKAY) { - goto LBL_ERR; - } - } - - /* 5. while v is even do */ - while (mp_iseven (&v) == 1) { - /* 5.1 v = v/2 */ - if ((res = mp_div_2 (&v, &v)) != MP_OKAY) { - goto LBL_ERR; - } - /* 5.2 if C or D is odd then */ - if (mp_isodd (&C) == 1 || mp_isodd (&D) == 1) { - /* C = (C+y)/2, D = (D-x)/2 */ - if ((res = mp_add (&C, &y, &C)) != MP_OKAY) { - goto LBL_ERR; - } - if ((res = mp_sub (&D, &x, &D)) != MP_OKAY) { - goto LBL_ERR; - } - } - /* C = C/2, D = D/2 */ - if ((res = mp_div_2 (&C, &C)) != MP_OKAY) { - goto LBL_ERR; - } - if ((res = mp_div_2 (&D, &D)) != MP_OKAY) { - goto LBL_ERR; - } - } - - /* 6. if u >= v then */ - if (mp_cmp (&u, &v) != MP_LT) { - /* u = u - v, A = A - C, B = B - D */ - if ((res = mp_sub (&u, &v, &u)) != MP_OKAY) { - goto LBL_ERR; - } - - if ((res = mp_sub (&A, &C, &A)) != MP_OKAY) { - goto LBL_ERR; - } - - if ((res = mp_sub (&B, &D, &B)) != MP_OKAY) { - goto LBL_ERR; - } - } else { - /* v - v - u, C = C - A, D = D - B */ - if ((res = mp_sub (&v, &u, &v)) != MP_OKAY) { - goto LBL_ERR; - } - - if ((res = mp_sub (&C, &A, &C)) != MP_OKAY) { - goto LBL_ERR; - } - - if ((res = mp_sub (&D, &B, &D)) != MP_OKAY) { - goto LBL_ERR; - } - } - - /* if not zero goto step 4 */ - if (mp_iszero (&u) == 0) - goto top; - - /* now a = C, b = D, gcd == g*v */ - - /* if v != 1 then there is no inverse */ - if (mp_cmp_d (&v, 1) != MP_EQ) { - res = MP_VAL; - goto LBL_ERR; - } - - /* if its too low */ - while (mp_cmp_d(&C, 0) == MP_LT) { - if ((res = mp_add(&C, b, &C)) != MP_OKAY) { - goto LBL_ERR; - } - } - - /* too big */ - while (mp_cmp_mag(&C, b) != MP_LT) { - if ((res = mp_sub(&C, b, &C)) != MP_OKAY) { - goto LBL_ERR; - } - } - - /* C is now the inverse */ - mp_exch (&C, c); - res = MP_OKAY; -LBL_ERR:mp_clear_multi (&x, &y, &u, &v, &A, &B, &C, &D, NULL); - return res; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_invmod_slow.c */ - -/* Start: bn_mp_is_square.c */ -#include <tommath.h> -#ifdef BN_MP_IS_SQUARE_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* Check if remainders are possible squares - fast exclude non-squares */ -static const char rem_128[128] = { - 0, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, - 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, - 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, - 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, - 0, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, - 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, - 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, - 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1 -}; - -static const char rem_105[105] = { - 0, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, - 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, - 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, - 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, - 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, - 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, - 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1 -}; - -/* Store non-zero to ret if arg is square, and zero if not */ -int mp_is_square(mp_int *arg,int *ret) -{ - int res; - mp_digit c; - mp_int t; - unsigned long r; - - /* Default to Non-square :) */ - *ret = MP_NO; - - if (arg->sign == MP_NEG) { - return MP_VAL; - } - - /* digits used? (TSD) */ - if (arg->used == 0) { - return MP_OKAY; - } - - /* First check mod 128 (suppose that DIGIT_BIT is at least 7) */ - if (rem_128[127 & DIGIT(arg,0)] == 1) { - return MP_OKAY; - } - - /* Next check mod 105 (3*5*7) */ - if ((res = mp_mod_d(arg,105,&c)) != MP_OKAY) { - return res; - } - if (rem_105[c] == 1) { - return MP_OKAY; - } - - - if ((res = mp_init_set_int(&t,11L*13L*17L*19L*23L*29L*31L)) != MP_OKAY) { - return res; - } - if ((res = mp_mod(arg,&t,&t)) != MP_OKAY) { - goto ERR; - } - r = mp_get_int(&t); - /* Check for other prime modules, note it's not an ERROR but we must - * free "t" so the easiest way is to goto ERR. We know that res - * is already equal to MP_OKAY from the mp_mod call - */ - if ( (1L<<(r%11)) & 0x5C4L ) goto ERR; - if ( (1L<<(r%13)) & 0x9E4L ) goto ERR; - if ( (1L<<(r%17)) & 0x5CE8L ) goto ERR; - if ( (1L<<(r%19)) & 0x4F50CL ) goto ERR; - if ( (1L<<(r%23)) & 0x7ACCA0L ) goto ERR; - if ( (1L<<(r%29)) & 0xC2EDD0CL ) goto ERR; - if ( (1L<<(r%31)) & 0x6DE2B848L ) goto ERR; - - /* Final check - is sqr(sqrt(arg)) == arg ? */ - if ((res = mp_sqrt(arg,&t)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_sqr(&t,&t)) != MP_OKAY) { - goto ERR; - } - - *ret = (mp_cmp_mag(&t,arg) == MP_EQ) ? MP_YES : MP_NO; -ERR:mp_clear(&t); - return res; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_is_square.c */ - -/* Start: bn_mp_jacobi.c */ -#include <tommath.h> -#ifdef BN_MP_JACOBI_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* computes the jacobi c = (a | n) (or Legendre if n is prime) - * HAC pp. 73 Algorithm 2.149 - */ -int mp_jacobi (mp_int * a, mp_int * p, int *c) -{ - mp_int a1, p1; - int k, s, r, res; - mp_digit residue; - - /* if p <= 0 return MP_VAL */ - if (mp_cmp_d(p, 0) != MP_GT) { - return MP_VAL; - } - - /* step 1. if a == 0, return 0 */ - if (mp_iszero (a) == 1) { - *c = 0; - return MP_OKAY; - } - - /* step 2. if a == 1, return 1 */ - if (mp_cmp_d (a, 1) == MP_EQ) { - *c = 1; - return MP_OKAY; - } - - /* default */ - s = 0; - - /* step 3. write a = a1 * 2**k */ - if ((res = mp_init_copy (&a1, a)) != MP_OKAY) { - return res; - } - - if ((res = mp_init (&p1)) != MP_OKAY) { - goto LBL_A1; - } - - /* divide out larger power of two */ - k = mp_cnt_lsb(&a1); - if ((res = mp_div_2d(&a1, k, &a1, NULL)) != MP_OKAY) { - goto LBL_P1; - } - - /* step 4. if e is even set s=1 */ - if ((k & 1) == 0) { - s = 1; - } else { - /* else set s=1 if p = 1/7 (mod 8) or s=-1 if p = 3/5 (mod 8) */ - residue = p->dp[0] & 7; - - if (residue == 1 || residue == 7) { - s = 1; - } else if (residue == 3 || residue == 5) { - s = -1; - } - } - - /* step 5. if p == 3 (mod 4) *and* a1 == 3 (mod 4) then s = -s */ - if ( ((p->dp[0] & 3) == 3) && ((a1.dp[0] & 3) == 3)) { - s = -s; - } - - /* if a1 == 1 we're done */ - if (mp_cmp_d (&a1, 1) == MP_EQ) { - *c = s; - } else { - /* n1 = n mod a1 */ - if ((res = mp_mod (p, &a1, &p1)) != MP_OKAY) { - goto LBL_P1; - } - if ((res = mp_jacobi (&p1, &a1, &r)) != MP_OKAY) { - goto LBL_P1; - } - *c = s * r; - } - - /* done */ - res = MP_OKAY; -LBL_P1:mp_clear (&p1); -LBL_A1:mp_clear (&a1); - return res; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_jacobi.c */ - -/* Start: bn_mp_karatsuba_mul.c */ -#include <tommath.h> -#ifdef BN_MP_KARATSUBA_MUL_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* c = |a| * |b| using Karatsuba Multiplication using - * three half size multiplications - * - * Let B represent the radix [e.g. 2**DIGIT_BIT] and - * let n represent half of the number of digits in - * the min(a,b) - * - * a = a1 * B**n + a0 - * b = b1 * B**n + b0 - * - * Then, a * b => - a1b1 * B**2n + ((a1 + a0)(b1 + b0) - (a0b0 + a1b1)) * B + a0b0 - * - * Note that a1b1 and a0b0 are used twice and only need to be - * computed once. So in total three half size (half # of - * digit) multiplications are performed, a0b0, a1b1 and - * (a1+b1)(a0+b0) - * - * Note that a multiplication of half the digits requires - * 1/4th the number of single precision multiplications so in - * total after one call 25% of the single precision multiplications - * are saved. Note also that the call to mp_mul can end up back - * in this function if the a0, a1, b0, or b1 are above the threshold. - * This is known as divide-and-conquer and leads to the famous - * O(N**lg(3)) or O(N**1.584) work which is asymptopically lower than - * the standard O(N**2) that the baseline/comba methods use. - * Generally though the overhead of this method doesn't pay off - * until a certain size (N ~ 80) is reached. - */ -int mp_karatsuba_mul (mp_int * a, mp_int * b, mp_int * c) -{ - mp_int x0, x1, y0, y1, t1, x0y0, x1y1; - int B, err; - - /* default the return code to an error */ - err = MP_MEM; - - /* min # of digits */ - B = MIN (a->used, b->used); - - /* now divide in two */ - B = B >> 1; - - /* init copy all the temps */ - if (mp_init_size (&x0, B) != MP_OKAY) - goto ERR; - if (mp_init_size (&x1, a->used - B) != MP_OKAY) - goto X0; - if (mp_init_size (&y0, B) != MP_OKAY) - goto X1; - if (mp_init_size (&y1, b->used - B) != MP_OKAY) - goto Y0; - - /* init temps */ - if (mp_init_size (&t1, B * 2) != MP_OKAY) - goto Y1; - if (mp_init_size (&x0y0, B * 2) != MP_OKAY) - goto T1; - if (mp_init_size (&x1y1, B * 2) != MP_OKAY) - goto X0Y0; - - /* now shift the digits */ - x0.used = y0.used = B; - x1.used = a->used - B; - y1.used = b->used - B; - - { - register int x; - register mp_digit *tmpa, *tmpb, *tmpx, *tmpy; - - /* we copy the digits directly instead of using higher level functions - * since we also need to shift the digits - */ - tmpa = a->dp; - tmpb = b->dp; - - tmpx = x0.dp; - tmpy = y0.dp; - for (x = 0; x < B; x++) { - *tmpx++ = *tmpa++; - *tmpy++ = *tmpb++; - } - - tmpx = x1.dp; - for (x = B; x < a->used; x++) { - *tmpx++ = *tmpa++; - } - - tmpy = y1.dp; - for (x = B; x < b->used; x++) { - *tmpy++ = *tmpb++; - } - } - - /* only need to clamp the lower words since by definition the - * upper words x1/y1 must have a known number of digits - */ - mp_clamp (&x0); - mp_clamp (&y0); - - /* now calc the products x0y0 and x1y1 */ - /* after this x0 is no longer required, free temp [x0==t2]! */ - if (mp_mul (&x0, &y0, &x0y0) != MP_OKAY) - goto X1Y1; /* x0y0 = x0*y0 */ - if (mp_mul (&x1, &y1, &x1y1) != MP_OKAY) - goto X1Y1; /* x1y1 = x1*y1 */ - - /* now calc x1+x0 and y1+y0 */ - if (s_mp_add (&x1, &x0, &t1) != MP_OKAY) - goto X1Y1; /* t1 = x1 - x0 */ - if (s_mp_add (&y1, &y0, &x0) != MP_OKAY) - goto X1Y1; /* t2 = y1 - y0 */ - if (mp_mul (&t1, &x0, &t1) != MP_OKAY) - goto X1Y1; /* t1 = (x1 + x0) * (y1 + y0) */ - - /* add x0y0 */ - if (mp_add (&x0y0, &x1y1, &x0) != MP_OKAY) - goto X1Y1; /* t2 = x0y0 + x1y1 */ - if (s_mp_sub (&t1, &x0, &t1) != MP_OKAY) - goto X1Y1; /* t1 = (x1+x0)*(y1+y0) - (x1y1 + x0y0) */ - - /* shift by B */ - if (mp_lshd (&t1, B) != MP_OKAY) - goto X1Y1; /* t1 = (x0y0 + x1y1 - (x1-x0)*(y1-y0))<<B */ - if (mp_lshd (&x1y1, B * 2) != MP_OKAY) - goto X1Y1; /* x1y1 = x1y1 << 2*B */ - - if (mp_add (&x0y0, &t1, &t1) != MP_OKAY) - goto X1Y1; /* t1 = x0y0 + t1 */ - if (mp_add (&t1, &x1y1, c) != MP_OKAY) - goto X1Y1; /* t1 = x0y0 + t1 + x1y1 */ - - /* Algorithm succeeded set the return code to MP_OKAY */ - err = MP_OKAY; - -X1Y1:mp_clear (&x1y1); -X0Y0:mp_clear (&x0y0); -T1:mp_clear (&t1); -Y1:mp_clear (&y1); -Y0:mp_clear (&y0); -X1:mp_clear (&x1); -X0:mp_clear (&x0); -ERR: - return err; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_karatsuba_mul.c */ - -/* Start: bn_mp_karatsuba_sqr.c */ -#include <tommath.h> -#ifdef BN_MP_KARATSUBA_SQR_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* Karatsuba squaring, computes b = a*a using three - * half size squarings - * - * See comments of karatsuba_mul for details. It - * is essentially the same algorithm but merely - * tuned to perform recursive squarings. - */ -int mp_karatsuba_sqr (mp_int * a, mp_int * b) -{ - mp_int x0, x1, t1, t2, x0x0, x1x1; - int B, err; - - err = MP_MEM; - - /* min # of digits */ - B = a->used; - - /* now divide in two */ - B = B >> 1; - - /* init copy all the temps */ - if (mp_init_size (&x0, B) != MP_OKAY) - goto ERR; - if (mp_init_size (&x1, a->used - B) != MP_OKAY) - goto X0; - - /* init temps */ - if (mp_init_size (&t1, a->used * 2) != MP_OKAY) - goto X1; - if (mp_init_size (&t2, a->used * 2) != MP_OKAY) - goto T1; - if (mp_init_size (&x0x0, B * 2) != MP_OKAY) - goto T2; - if (mp_init_size (&x1x1, (a->used - B) * 2) != MP_OKAY) - goto X0X0; - - { - register int x; - register mp_digit *dst, *src; - - src = a->dp; - - /* now shift the digits */ - dst = x0.dp; - for (x = 0; x < B; x++) { - *dst++ = *src++; - } - - dst = x1.dp; - for (x = B; x < a->used; x++) { - *dst++ = *src++; - } - } - - x0.used = B; - x1.used = a->used - B; - - mp_clamp (&x0); - - /* now calc the products x0*x0 and x1*x1 */ - if (mp_sqr (&x0, &x0x0) != MP_OKAY) - goto X1X1; /* x0x0 = x0*x0 */ - if (mp_sqr (&x1, &x1x1) != MP_OKAY) - goto X1X1; /* x1x1 = x1*x1 */ - - /* now calc (x1+x0)**2 */ - if (s_mp_add (&x1, &x0, &t1) != MP_OKAY) - goto X1X1; /* t1 = x1 - x0 */ - if (mp_sqr (&t1, &t1) != MP_OKAY) - goto X1X1; /* t1 = (x1 - x0) * (x1 - x0) */ - - /* add x0y0 */ - if (s_mp_add (&x0x0, &x1x1, &t2) != MP_OKAY) - goto X1X1; /* t2 = x0x0 + x1x1 */ - if (s_mp_sub (&t1, &t2, &t1) != MP_OKAY) - goto X1X1; /* t1 = (x1+x0)**2 - (x0x0 + x1x1) */ - - /* shift by B */ - if (mp_lshd (&t1, B) != MP_OKAY) - goto X1X1; /* t1 = (x0x0 + x1x1 - (x1-x0)*(x1-x0))<<B */ - if (mp_lshd (&x1x1, B * 2) != MP_OKAY) - goto X1X1; /* x1x1 = x1x1 << 2*B */ - - if (mp_add (&x0x0, &t1, &t1) != MP_OKAY) - goto X1X1; /* t1 = x0x0 + t1 */ - if (mp_add (&t1, &x1x1, b) != MP_OKAY) - goto X1X1; /* t1 = x0x0 + t1 + x1x1 */ - - err = MP_OKAY; - -X1X1:mp_clear (&x1x1); -X0X0:mp_clear (&x0x0); -T2:mp_clear (&t2); -T1:mp_clear (&t1); -X1:mp_clear (&x1); -X0:mp_clear (&x0); -ERR: - return err; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_karatsuba_sqr.c */ - -/* Start: bn_mp_lcm.c */ -#include <tommath.h> -#ifdef BN_MP_LCM_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* computes least common multiple as |a*b|/(a, b) */ -int mp_lcm (mp_int * a, mp_int * b, mp_int * c) -{ - int res; - mp_int t1, t2; - - - if ((res = mp_init_multi (&t1, &t2, NULL)) != MP_OKAY) { - return res; - } - - /* t1 = get the GCD of the two inputs */ - if ((res = mp_gcd (a, b, &t1)) != MP_OKAY) { - goto LBL_T; - } - - /* divide the smallest by the GCD */ - if (mp_cmp_mag(a, b) == MP_LT) { - /* store quotient in t2 such that t2 * b is the LCM */ - if ((res = mp_div(a, &t1, &t2, NULL)) != MP_OKAY) { - goto LBL_T; - } - res = mp_mul(b, &t2, c); - } else { - /* store quotient in t2 such that t2 * a is the LCM */ - if ((res = mp_div(b, &t1, &t2, NULL)) != MP_OKAY) { - goto LBL_T; - } - res = mp_mul(a, &t2, c); - } - - /* fix the sign to positive */ - c->sign = MP_ZPOS; - -LBL_T: - mp_clear_multi (&t1, &t2, NULL); - return res; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_lcm.c */ - -/* Start: bn_mp_lshd.c */ -#include <tommath.h> -#ifdef BN_MP_LSHD_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* shift left a certain amount of digits */ -int mp_lshd (mp_int * a, int b) -{ - int x, res; - - /* if its less than zero return */ - if (b <= 0) { - return MP_OKAY; - } - - /* grow to fit the new digits */ - if (a->alloc < a->used + b) { - if ((res = mp_grow (a, a->used + b)) != MP_OKAY) { - return res; - } - } - - { - register mp_digit *top, *bottom; - - /* increment the used by the shift amount then copy upwards */ - a->used += b; - - /* top */ - top = a->dp + a->used - 1; - - /* base */ - bottom = a->dp + a->used - 1 - b; - - /* much like mp_rshd this is implemented using a sliding window - * except the window goes the otherway around. Copying from - * the bottom to the top. see bn_mp_rshd.c for more info. - */ - for (x = a->used - 1; x >= b; x--) { - *top-- = *bottom--; - } - - /* zero the lower digits */ - top = a->dp; - for (x = 0; x < b; x++) { - *top++ = 0; - } - } - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_lshd.c */ - -/* Start: bn_mp_mod.c */ -#include <tommath.h> -#ifdef BN_MP_MOD_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* c = a mod b, 0 <= c < b */ -int -mp_mod (mp_int * a, mp_int * b, mp_int * c) -{ - mp_int t; - int res; - - if ((res = mp_init (&t)) != MP_OKAY) { - return res; - } - - if ((res = mp_div (a, b, NULL, &t)) != MP_OKAY) { - mp_clear (&t); - return res; - } - - if (t.sign != b->sign) { - res = mp_add (b, &t, c); - } else { - res = MP_OKAY; - mp_exch (&t, c); - } - - mp_clear (&t); - return res; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_mod.c */ - -/* Start: bn_mp_mod_2d.c */ -#include <tommath.h> -#ifdef BN_MP_MOD_2D_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* calc a value mod 2**b */ -int -mp_mod_2d (mp_int * a, int b, mp_int * c) -{ - int x, res; - - /* if b is <= 0 then zero the int */ - if (b <= 0) { - mp_zero (c); - return MP_OKAY; - } - - /* if the modulus is larger than the value than return */ - if (b >= (int) (a->used * DIGIT_BIT)) { - res = mp_copy (a, c); - return res; - } - - /* copy */ - if ((res = mp_copy (a, c)) != MP_OKAY) { - return res; - } - - /* zero digits above the last digit of the modulus */ - for (x = (b / DIGIT_BIT) + ((b % DIGIT_BIT) == 0 ? 0 : 1); x < c->used; x++) { - c->dp[x] = 0; - } - /* clear the digit that is not completely outside/inside the modulus */ - c->dp[b / DIGIT_BIT] &= - (mp_digit) ((((mp_digit) 1) << (((mp_digit) b) % DIGIT_BIT)) - ((mp_digit) 1)); - mp_clamp (c); - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_mod_2d.c */ - -/* Start: bn_mp_mod_d.c */ -#include <tommath.h> -#ifdef BN_MP_MOD_D_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -int -mp_mod_d (mp_int * a, mp_digit b, mp_digit * c) -{ - return mp_div_d(a, b, NULL, c); -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_mod_d.c */ - -/* Start: bn_mp_montgomery_calc_normalization.c */ -#include <tommath.h> -#ifdef BN_MP_MONTGOMERY_CALC_NORMALIZATION_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* - * shifts with subtractions when the result is greater than b. - * - * The method is slightly modified to shift B unconditionally upto just under - * the leading bit of b. This saves alot of multiple precision shifting. - */ -int mp_montgomery_calc_normalization (mp_int * a, mp_int * b) -{ - int x, bits, res; - - /* how many bits of last digit does b use */ - bits = mp_count_bits (b) % DIGIT_BIT; - - if (b->used > 1) { - if ((res = mp_2expt (a, (b->used - 1) * DIGIT_BIT + bits - 1)) != MP_OKAY) { - return res; - } - } else { - mp_set(a, 1); - bits = 1; - } - - - /* now compute C = A * B mod b */ - for (x = bits - 1; x < (int)DIGIT_BIT; x++) { - if ((res = mp_mul_2 (a, a)) != MP_OKAY) { - return res; - } - if (mp_cmp_mag (a, b) != MP_LT) { - if ((res = s_mp_sub (a, b, a)) != MP_OKAY) { - return res; - } - } - } - - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_montgomery_calc_normalization.c */ - -/* Start: bn_mp_montgomery_reduce.c */ -#include <tommath.h> -#ifdef BN_MP_MONTGOMERY_REDUCE_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* computes xR**-1 == x (mod N) via Montgomery Reduction */ -int -mp_montgomery_reduce (mp_int * x, mp_int * n, mp_digit rho) -{ - int ix, res, digs; - mp_digit mu; - - /* can the fast reduction [comba] method be used? - * - * Note that unlike in mul you're safely allowed *less* - * than the available columns [255 per default] since carries - * are fixed up in the inner loop. - */ - digs = n->used * 2 + 1; - if ((digs < MP_WARRAY) && - n->used < - (1 << ((CHAR_BIT * sizeof (mp_word)) - (2 * DIGIT_BIT)))) { - return fast_mp_montgomery_reduce (x, n, rho); - } - - /* grow the input as required */ - if (x->alloc < digs) { - if ((res = mp_grow (x, digs)) != MP_OKAY) { - return res; - } - } - x->used = digs; - - for (ix = 0; ix < n->used; ix++) { - /* mu = ai * rho mod b - * - * The value of rho must be precalculated via - * montgomery_setup() such that - * it equals -1/n0 mod b this allows the - * following inner loop to reduce the - * input one digit at a time - */ - mu = (mp_digit) (((mp_word)x->dp[ix]) * ((mp_word)rho) & MP_MASK); - - /* a = a + mu * m * b**i */ - { - register int iy; - register mp_digit *tmpn, *tmpx, u; - register mp_word r; - - /* alias for digits of the modulus */ - tmpn = n->dp; - - /* alias for the digits of x [the input] */ - tmpx = x->dp + ix; - - /* set the carry to zero */ - u = 0; - - /* Multiply and add in place */ - for (iy = 0; iy < n->used; iy++) { - /* compute product and sum */ - r = ((mp_word)mu) * ((mp_word)*tmpn++) + - ((mp_word) u) + ((mp_word) * tmpx); - - /* get carry */ - u = (mp_digit)(r >> ((mp_word) DIGIT_BIT)); - - /* fix digit */ - *tmpx++ = (mp_digit)(r & ((mp_word) MP_MASK)); - } - /* At this point the ix'th digit of x should be zero */ - - - /* propagate carries upwards as required*/ - while (u) { - *tmpx += u; - u = *tmpx >> DIGIT_BIT; - *tmpx++ &= MP_MASK; - } - } - } - - /* at this point the n.used'th least - * significant digits of x are all zero - * which means we can shift x to the - * right by n.used digits and the - * residue is unchanged. - */ - - /* x = x/b**n.used */ - mp_clamp(x); - mp_rshd (x, n->used); - - /* if x >= n then x = x - n */ - if (mp_cmp_mag (x, n) != MP_LT) { - return s_mp_sub (x, n, x); - } - - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_montgomery_reduce.c */ - -/* Start: bn_mp_montgomery_setup.c */ -#include <tommath.h> -#ifdef BN_MP_MONTGOMERY_SETUP_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* setups the montgomery reduction stuff */ -int -mp_montgomery_setup (mp_int * n, mp_digit * rho) -{ - mp_digit x, b; - -/* fast inversion mod 2**k - * - * Based on the fact that - * - * XA = 1 (mod 2**n) => (X(2-XA)) A = 1 (mod 2**2n) - * => 2*X*A - X*X*A*A = 1 - * => 2*(1) - (1) = 1 - */ - b = n->dp[0]; - - if ((b & 1) == 0) { - return MP_VAL; - } - - x = (((b + 2) & 4) << 1) + b; /* here x*a==1 mod 2**4 */ - x *= 2 - b * x; /* here x*a==1 mod 2**8 */ -#if !defined(MP_8BIT) - x *= 2 - b * x; /* here x*a==1 mod 2**16 */ -#endif -#if defined(MP_64BIT) || !(defined(MP_8BIT) || defined(MP_16BIT)) - x *= 2 - b * x; /* here x*a==1 mod 2**32 */ -#endif -#ifdef MP_64BIT - x *= 2 - b * x; /* here x*a==1 mod 2**64 */ -#endif - - /* rho = -1/m mod b */ - *rho = (unsigned long)(((mp_word)1 << ((mp_word) DIGIT_BIT)) - x) & MP_MASK; - - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_montgomery_setup.c */ - -/* Start: bn_mp_mul.c */ -#include <tommath.h> -#ifdef BN_MP_MUL_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* high level multiplication (handles sign) */ -int mp_mul (mp_int * a, mp_int * b, mp_int * c) -{ - int res, neg; - neg = (a->sign == b->sign) ? MP_ZPOS : MP_NEG; - - /* use Toom-Cook? */ -#ifdef BN_MP_TOOM_MUL_C - if (MIN (a->used, b->used) >= TOOM_MUL_CUTOFF) { - res = mp_toom_mul(a, b, c); - } else -#endif -#ifdef BN_MP_KARATSUBA_MUL_C - /* use Karatsuba? */ - if (MIN (a->used, b->used) >= KARATSUBA_MUL_CUTOFF) { - res = mp_karatsuba_mul (a, b, c); - } else -#endif - { - /* can we use the fast multiplier? - * - * The fast multiplier can be used if the output will - * have less than MP_WARRAY digits and the number of - * digits won't affect carry propagation - */ - int digs = a->used + b->used + 1; - -#ifdef BN_FAST_S_MP_MUL_DIGS_C - if ((digs < MP_WARRAY) && - MIN(a->used, b->used) <= - (1 << ((CHAR_BIT * sizeof (mp_word)) - (2 * DIGIT_BIT)))) { - res = fast_s_mp_mul_digs (a, b, c, digs); - } else -#endif -#ifdef BN_S_MP_MUL_DIGS_C - res = s_mp_mul (a, b, c); /* uses s_mp_mul_digs */ -#else - res = MP_VAL; -#endif - - } - c->sign = (c->used > 0) ? neg : MP_ZPOS; - return res; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_mul.c */ - -/* Start: bn_mp_mul_2.c */ -#include <tommath.h> -#ifdef BN_MP_MUL_2_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* b = a*2 */ -int mp_mul_2(mp_int * a, mp_int * b) -{ - int x, res, oldused; - - /* grow to accomodate result */ - if (b->alloc < a->used + 1) { - if ((res = mp_grow (b, a->used + 1)) != MP_OKAY) { - return res; - } - } - - oldused = b->used; - b->used = a->used; - - { - register mp_digit r, rr, *tmpa, *tmpb; - - /* alias for source */ - tmpa = a->dp; - - /* alias for dest */ - tmpb = b->dp; - - /* carry */ - r = 0; - for (x = 0; x < a->used; x++) { - - /* get what will be the *next* carry bit from the - * MSB of the current digit - */ - rr = *tmpa >> ((mp_digit)(DIGIT_BIT - 1)); - - /* now shift up this digit, add in the carry [from the previous] */ - *tmpb++ = ((*tmpa++ << ((mp_digit)1)) | r) & MP_MASK; - - /* copy the carry that would be from the source - * digit into the next iteration - */ - r = rr; - } - - /* new leading digit? */ - if (r != 0) { - /* add a MSB which is always 1 at this point */ - *tmpb = 1; - ++(b->used); - } - - /* now zero any excess digits on the destination - * that we didn't write to - */ - tmpb = b->dp + b->used; - for (x = b->used; x < oldused; x++) { - *tmpb++ = 0; - } - } - b->sign = a->sign; - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_mul_2.c */ - -/* Start: bn_mp_mul_2d.c */ -#include <tommath.h> -#ifdef BN_MP_MUL_2D_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* shift left by a certain bit count */ -int mp_mul_2d (mp_int * a, int b, mp_int * c) -{ - mp_digit d; - int res; - - /* copy */ - if (a != c) { - if ((res = mp_copy (a, c)) != MP_OKAY) { - return res; - } - } - - if (c->alloc < (int)(c->used + b/DIGIT_BIT + 1)) { - if ((res = mp_grow (c, c->used + b / DIGIT_BIT + 1)) != MP_OKAY) { - return res; - } - } - - /* shift by as many digits in the bit count */ - if (b >= (int)DIGIT_BIT) { - if ((res = mp_lshd (c, b / DIGIT_BIT)) != MP_OKAY) { - return res; - } - } - - /* shift any bit count < DIGIT_BIT */ - d = (mp_digit) (b % DIGIT_BIT); - if (d != 0) { - register mp_digit *tmpc, shift, mask, r, rr; - register int x; - - /* bitmask for carries */ - mask = (((mp_digit)1) << d) - 1; - - /* shift for msbs */ - shift = DIGIT_BIT - d; - - /* alias */ - tmpc = c->dp; - - /* carry */ - r = 0; - for (x = 0; x < c->used; x++) { - /* get the higher bits of the current word */ - rr = (*tmpc >> shift) & mask; - - /* shift the current word and OR in the carry */ - *tmpc = ((*tmpc << d) | r) & MP_MASK; - ++tmpc; - - /* set the carry to the carry bits of the current word */ - r = rr; - } - - /* set final carry */ - if (r != 0) { - c->dp[(c->used)++] = r; - } - } - mp_clamp (c); - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_mul_2d.c */ - -/* Start: bn_mp_mul_d.c */ -#include <tommath.h> -#ifdef BN_MP_MUL_D_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* multiply by a digit */ -int -mp_mul_d (mp_int * a, mp_digit b, mp_int * c) -{ - mp_digit u, *tmpa, *tmpc; - mp_word r; - int ix, res, olduse; - - /* make sure c is big enough to hold a*b */ - if (c->alloc < a->used + 1) { - if ((res = mp_grow (c, a->used + 1)) != MP_OKAY) { - return res; - } - } - - /* get the original destinations used count */ - olduse = c->used; - - /* set the sign */ - c->sign = a->sign; - - /* alias for a->dp [source] */ - tmpa = a->dp; - - /* alias for c->dp [dest] */ - tmpc = c->dp; - - /* zero carry */ - u = 0; - - /* compute columns */ - for (ix = 0; ix < a->used; ix++) { - /* compute product and carry sum for this term */ - r = ((mp_word) u) + ((mp_word)*tmpa++) * ((mp_word)b); - - /* mask off higher bits to get a single digit */ - *tmpc++ = (mp_digit) (r & ((mp_word) MP_MASK)); - - /* send carry into next iteration */ - u = (mp_digit) (r >> ((mp_word) DIGIT_BIT)); - } - - /* store final carry [if any] and increment ix offset */ - *tmpc++ = u; - ++ix; - - /* now zero digits above the top */ - while (ix++ < olduse) { - *tmpc++ = 0; - } - - /* set used count */ - c->used = a->used + 1; - mp_clamp(c); - - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_mul_d.c */ - -/* Start: bn_mp_mulmod.c */ -#include <tommath.h> -#ifdef BN_MP_MULMOD_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* d = a * b (mod c) */ -int mp_mulmod (mp_int * a, mp_int * b, mp_int * c, mp_int * d) -{ - int res; - mp_int t; - - if ((res = mp_init (&t)) != MP_OKAY) { - return res; - } - - if ((res = mp_mul (a, b, &t)) != MP_OKAY) { - mp_clear (&t); - return res; - } - res = mp_mod (&t, c, d); - mp_clear (&t); - return res; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_mulmod.c */ - -/* Start: bn_mp_n_root.c */ -#include <tommath.h> -#ifdef BN_MP_N_ROOT_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* find the n'th root of an integer - * - * Result found such that (c)**b <= a and (c+1)**b > a - * - * This algorithm uses Newton's approximation - * x[i+1] = x[i] - f(x[i])/f'(x[i]) - * which will find the root in log(N) time where - * each step involves a fair bit. This is not meant to - * find huge roots [square and cube, etc]. - */ -int mp_n_root (mp_int * a, mp_digit b, mp_int * c) -{ - mp_int t1, t2, t3; - int res, neg; - - /* input must be positive if b is even */ - if ((b & 1) == 0 && a->sign == MP_NEG) { - return MP_VAL; - } - - if ((res = mp_init (&t1)) != MP_OKAY) { - return res; - } - - if ((res = mp_init (&t2)) != MP_OKAY) { - goto LBL_T1; - } - - if ((res = mp_init (&t3)) != MP_OKAY) { - goto LBL_T2; - } - - /* if a is negative fudge the sign but keep track */ - neg = a->sign; - a->sign = MP_ZPOS; - - /* t2 = 2 */ - mp_set (&t2, 2); - - do { - /* t1 = t2 */ - if ((res = mp_copy (&t2, &t1)) != MP_OKAY) { - goto LBL_T3; - } - - /* t2 = t1 - ((t1**b - a) / (b * t1**(b-1))) */ - - /* t3 = t1**(b-1) */ - if ((res = mp_expt_d (&t1, b - 1, &t3)) != MP_OKAY) { - goto LBL_T3; - } - - /* numerator */ - /* t2 = t1**b */ - if ((res = mp_mul (&t3, &t1, &t2)) != MP_OKAY) { - goto LBL_T3; - } - - /* t2 = t1**b - a */ - if ((res = mp_sub (&t2, a, &t2)) != MP_OKAY) { - goto LBL_T3; - } - - /* denominator */ - /* t3 = t1**(b-1) * b */ - if ((res = mp_mul_d (&t3, b, &t3)) != MP_OKAY) { - goto LBL_T3; - } - - /* t3 = (t1**b - a)/(b * t1**(b-1)) */ - if ((res = mp_div (&t2, &t3, &t3, NULL)) != MP_OKAY) { - goto LBL_T3; - } - - if ((res = mp_sub (&t1, &t3, &t2)) != MP_OKAY) { - goto LBL_T3; - } - } while (mp_cmp (&t1, &t2) != MP_EQ); - - /* result can be off by a few so check */ - for (;;) { - if ((res = mp_expt_d (&t1, b, &t2)) != MP_OKAY) { - goto LBL_T3; - } - - if (mp_cmp (&t2, a) == MP_GT) { - if ((res = mp_sub_d (&t1, 1, &t1)) != MP_OKAY) { - goto LBL_T3; - } - } else { - break; - } - } - - /* reset the sign of a first */ - a->sign = neg; - - /* set the result */ - mp_exch (&t1, c); - - /* set the sign of the result */ - c->sign = neg; - - res = MP_OKAY; - -LBL_T3:mp_clear (&t3); -LBL_T2:mp_clear (&t2); -LBL_T1:mp_clear (&t1); - return res; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_n_root.c */ - -/* Start: bn_mp_neg.c */ -#include <tommath.h> -#ifdef BN_MP_NEG_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* b = -a */ -int mp_neg (mp_int * a, mp_int * b) -{ - int res; - if (a != b) { - if ((res = mp_copy (a, b)) != MP_OKAY) { - return res; - } - } - - if (mp_iszero(b) != MP_YES) { - b->sign = (a->sign == MP_ZPOS) ? MP_NEG : MP_ZPOS; - } else { - b->sign = MP_ZPOS; - } - - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_neg.c */ - -/* Start: bn_mp_or.c */ -#include <tommath.h> -#ifdef BN_MP_OR_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* OR two ints together */ -int mp_or (mp_int * a, mp_int * b, mp_int * c) -{ - int res, ix, px; - mp_int t, *x; - - if (a->used > b->used) { - if ((res = mp_init_copy (&t, a)) != MP_OKAY) { - return res; - } - px = b->used; - x = b; - } else { - if ((res = mp_init_copy (&t, b)) != MP_OKAY) { - return res; - } - px = a->used; - x = a; - } - - for (ix = 0; ix < px; ix++) { - t.dp[ix] |= x->dp[ix]; - } - mp_clamp (&t); - mp_exch (c, &t); - mp_clear (&t); - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_or.c */ - -/* Start: bn_mp_prime_fermat.c */ -#include <tommath.h> -#ifdef BN_MP_PRIME_FERMAT_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* performs one Fermat test. - * - * If "a" were prime then b**a == b (mod a) since the order of - * the multiplicative sub-group would be phi(a) = a-1. That means - * it would be the same as b**(a mod (a-1)) == b**1 == b (mod a). - * - * Sets result to 1 if the congruence holds, or zero otherwise. - */ -int mp_prime_fermat (mp_int * a, mp_int * b, int *result) -{ - mp_int t; - int err; - - /* default to composite */ - *result = MP_NO; - - /* ensure b > 1 */ - if (mp_cmp_d(b, 1) != MP_GT) { - return MP_VAL; - } - - /* init t */ - if ((err = mp_init (&t)) != MP_OKAY) { - return err; - } - - /* compute t = b**a mod a */ - if ((err = mp_exptmod (b, a, a, &t)) != MP_OKAY) { - goto LBL_T; - } - - /* is it equal to b? */ - if (mp_cmp (&t, b) == MP_EQ) { - *result = MP_YES; - } - - err = MP_OKAY; -LBL_T:mp_clear (&t); - return err; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_prime_fermat.c */ - -/* Start: bn_mp_prime_is_divisible.c */ -#include <tommath.h> -#ifdef BN_MP_PRIME_IS_DIVISIBLE_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* determines if an integers is divisible by one - * of the first PRIME_SIZE primes or not - * - * sets result to 0 if not, 1 if yes - */ -int mp_prime_is_divisible (mp_int * a, int *result) -{ - int err, ix; - mp_digit res; - - /* default to not */ - *result = MP_NO; - - for (ix = 0; ix < PRIME_SIZE; ix++) { - /* what is a mod LBL_prime_tab[ix] */ - if ((err = mp_mod_d (a, ltm_prime_tab[ix], &res)) != MP_OKAY) { - return err; - } - - /* is the residue zero? */ - if (res == 0) { - *result = MP_YES; - return MP_OKAY; - } - } - - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_prime_is_divisible.c */ - -/* Start: bn_mp_prime_is_prime.c */ -#include <tommath.h> -#ifdef BN_MP_PRIME_IS_PRIME_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* performs a variable number of rounds of Miller-Rabin - * - * Probability of error after t rounds is no more than - - * - * Sets result to 1 if probably prime, 0 otherwise - */ -int mp_prime_is_prime (mp_int * a, int t, int *result) -{ - mp_int b; - int ix, err, res; - - /* default to no */ - *result = MP_NO; - - /* valid value of t? */ - if (t <= 0 || t > PRIME_SIZE) { - return MP_VAL; - } - - /* is the input equal to one of the primes in the table? */ - for (ix = 0; ix < PRIME_SIZE; ix++) { - if (mp_cmp_d(a, ltm_prime_tab[ix]) == MP_EQ) { - *result = 1; - return MP_OKAY; - } - } - - /* first perform trial division */ - if ((err = mp_prime_is_divisible (a, &res)) != MP_OKAY) { - return err; - } - - /* return if it was trivially divisible */ - if (res == MP_YES) { - return MP_OKAY; - } - - /* now perform the miller-rabin rounds */ - if ((err = mp_init (&b)) != MP_OKAY) { - return err; - } - - for (ix = 0; ix < t; ix++) { - /* set the prime */ - mp_set (&b, ltm_prime_tab[ix]); - - if ((err = mp_prime_miller_rabin (a, &b, &res)) != MP_OKAY) { - goto LBL_B; - } - - if (res == MP_NO) { - goto LBL_B; - } - } - - /* passed the test */ - *result = MP_YES; -LBL_B:mp_clear (&b); - return err; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_prime_is_prime.c */ - -/* Start: bn_mp_prime_miller_rabin.c */ -#include <tommath.h> -#ifdef BN_MP_PRIME_MILLER_RABIN_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* Miller-Rabin test of "a" to the base of "b" as described in - * HAC pp. 139 Algorithm 4.24 - * - * Sets result to 0 if definitely composite or 1 if probably prime. - * Randomly the chance of error is no more than 1/4 and often - * very much lower. - */ -int mp_prime_miller_rabin (mp_int * a, mp_int * b, int *result) -{ - mp_int n1, y, r; - int s, j, err; - - /* default */ - *result = MP_NO; - - /* ensure b > 1 */ - if (mp_cmp_d(b, 1) != MP_GT) { - return MP_VAL; - } - - /* get n1 = a - 1 */ - if ((err = mp_init_copy (&n1, a)) != MP_OKAY) { - return err; - } - if ((err = mp_sub_d (&n1, 1, &n1)) != MP_OKAY) { - goto LBL_N1; - } - - /* set 2**s * r = n1 */ - if ((err = mp_init_copy (&r, &n1)) != MP_OKAY) { - goto LBL_N1; - } - - /* count the number of least significant bits - * which are zero - */ - s = mp_cnt_lsb(&r); - - /* now divide n - 1 by 2**s */ - if ((err = mp_div_2d (&r, s, &r, NULL)) != MP_OKAY) { - goto LBL_R; - } - - /* compute y = b**r mod a */ - if ((err = mp_init (&y)) != MP_OKAY) { - goto LBL_R; - } - if ((err = mp_exptmod (b, &r, a, &y)) != MP_OKAY) { - goto LBL_Y; - } - - /* if y != 1 and y != n1 do */ - if (mp_cmp_d (&y, 1) != MP_EQ && mp_cmp (&y, &n1) != MP_EQ) { - j = 1; - /* while j <= s-1 and y != n1 */ - while ((j <= (s - 1)) && mp_cmp (&y, &n1) != MP_EQ) { - if ((err = mp_sqrmod (&y, a, &y)) != MP_OKAY) { - goto LBL_Y; - } - - /* if y == 1 then composite */ - if (mp_cmp_d (&y, 1) == MP_EQ) { - goto LBL_Y; - } - - ++j; - } - - /* if y != n1 then composite */ - if (mp_cmp (&y, &n1) != MP_EQ) { - goto LBL_Y; - } - } - - /* probably prime now */ - *result = MP_YES; -LBL_Y:mp_clear (&y); -LBL_R:mp_clear (&r); -LBL_N1:mp_clear (&n1); - return err; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_prime_miller_rabin.c */ - -/* Start: bn_mp_prime_next_prime.c */ -#include <tommath.h> -#ifdef BN_MP_PRIME_NEXT_PRIME_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* finds the next prime after the number "a" using "t" trials - * of Miller-Rabin. - * - * bbs_style = 1 means the prime must be congruent to 3 mod 4 - */ -int mp_prime_next_prime(mp_int *a, int t, int bbs_style) -{ - int err, res, x, y; - mp_digit res_tab[PRIME_SIZE], step, kstep; - mp_int b; - - /* ensure t is valid */ - if (t <= 0 || t > PRIME_SIZE) { - return MP_VAL; - } - - /* force positive */ - a->sign = MP_ZPOS; - - /* simple algo if a is less than the largest prime in the table */ - if (mp_cmp_d(a, ltm_prime_tab[PRIME_SIZE-1]) == MP_LT) { - /* find which prime it is bigger than */ - for (x = PRIME_SIZE - 2; x >= 0; x--) { - if (mp_cmp_d(a, ltm_prime_tab[x]) != MP_LT) { - if (bbs_style == 1) { - /* ok we found a prime smaller or - * equal [so the next is larger] - * - * however, the prime must be - * congruent to 3 mod 4 - */ - if ((ltm_prime_tab[x + 1] & 3) != 3) { - /* scan upwards for a prime congruent to 3 mod 4 */ - for (y = x + 1; y < PRIME_SIZE; y++) { - if ((ltm_prime_tab[y] & 3) == 3) { - mp_set(a, ltm_prime_tab[y]); - return MP_OKAY; - } - } - } - } else { - mp_set(a, ltm_prime_tab[x + 1]); - return MP_OKAY; - } - } - } - /* at this point a maybe 1 */ - if (mp_cmp_d(a, 1) == MP_EQ) { - mp_set(a, 2); - return MP_OKAY; - } - /* fall through to the sieve */ - } - - /* generate a prime congruent to 3 mod 4 or 1/3 mod 4? */ - if (bbs_style == 1) { - kstep = 4; - } else { - kstep = 2; - } - - /* at this point we will use a combination of a sieve and Miller-Rabin */ - - if (bbs_style == 1) { - /* if a mod 4 != 3 subtract the correct value to make it so */ - if ((a->dp[0] & 3) != 3) { - if ((err = mp_sub_d(a, (a->dp[0] & 3) + 1, a)) != MP_OKAY) { return err; }; - } - } else { - if (mp_iseven(a) == 1) { - /* force odd */ - if ((err = mp_sub_d(a, 1, a)) != MP_OKAY) { - return err; - } - } - } - - /* generate the restable */ - for (x = 1; x < PRIME_SIZE; x++) { - if ((err = mp_mod_d(a, ltm_prime_tab[x], res_tab + x)) != MP_OKAY) { - return err; - } - } - - /* init temp used for Miller-Rabin Testing */ - if ((err = mp_init(&b)) != MP_OKAY) { - return err; - } - - for (;;) { - /* skip to the next non-trivially divisible candidate */ - step = 0; - do { - /* y == 1 if any residue was zero [e.g. cannot be prime] */ - y = 0; - - /* increase step to next candidate */ - step += kstep; - - /* compute the new residue without using division */ - for (x = 1; x < PRIME_SIZE; x++) { - /* add the step to each residue */ - res_tab[x] += kstep; - - /* subtract the modulus [instead of using division] */ - if (res_tab[x] >= ltm_prime_tab[x]) { - res_tab[x] -= ltm_prime_tab[x]; - } - - /* set flag if zero */ - if (res_tab[x] == 0) { - y = 1; - } - } - } while (y == 1 && step < ((((mp_digit)1)<<DIGIT_BIT) - kstep)); - - /* add the step */ - if ((err = mp_add_d(a, step, a)) != MP_OKAY) { - goto LBL_ERR; - } - - /* if didn't pass sieve and step == MAX then skip test */ - if (y == 1 && step >= ((((mp_digit)1)<<DIGIT_BIT) - kstep)) { - continue; - } - - /* is this prime? */ - for (x = 0; x < t; x++) { - mp_set(&b, ltm_prime_tab[x]); - if ((err = mp_prime_miller_rabin(a, &b, &res)) != MP_OKAY) { - goto LBL_ERR; - } - if (res == MP_NO) { - break; - } - } - - if (res == MP_YES) { - break; - } - } - - err = MP_OKAY; -LBL_ERR: - mp_clear(&b); - return err; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_prime_next_prime.c */ - -/* Start: bn_mp_prime_rabin_miller_trials.c */ -#include <tommath.h> -#ifdef BN_MP_PRIME_RABIN_MILLER_TRIALS_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - - -static const struct { - int k, t; -} sizes[] = { -{ 128, 28 }, -{ 256, 16 }, -{ 384, 10 }, -{ 512, 7 }, -{ 640, 6 }, -{ 768, 5 }, -{ 896, 4 }, -{ 1024, 4 } -}; - -/* returns # of RM trials required for a given bit size */ -int mp_prime_rabin_miller_trials(int size) -{ - int x; - - for (x = 0; x < (int)(sizeof(sizes)/(sizeof(sizes[0]))); x++) { - if (sizes[x].k == size) { - return sizes[x].t; - } else if (sizes[x].k > size) { - return (x == 0) ? sizes[0].t : sizes[x - 1].t; - } - } - return sizes[x-1].t + 1; -} - - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_prime_rabin_miller_trials.c */ - -/* Start: bn_mp_prime_random_ex.c */ -#include <tommath.h> -#ifdef BN_MP_PRIME_RANDOM_EX_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* makes a truly random prime of a given size (bits), - * - * Flags are as follows: - * - * LTM_PRIME_BBS - make prime congruent to 3 mod 4 - * LTM_PRIME_SAFE - make sure (p-1)/2 is prime as well (implies LTM_PRIME_BBS) - * LTM_PRIME_2MSB_OFF - make the 2nd highest bit zero - * LTM_PRIME_2MSB_ON - make the 2nd highest bit one - * - * You have to supply a callback which fills in a buffer with random bytes. "dat" is a parameter you can - * have passed to the callback (e.g. a state or something). This function doesn't use "dat" itself - * so it can be NULL - * - */ - -/* This is possibly the mother of all prime generation functions, muahahahahaha! */ -int mp_prime_random_ex(mp_int *a, int t, int size, int flags, ltm_prime_callback cb, void *dat) -{ - unsigned char *tmp, maskAND, maskOR_msb, maskOR_lsb; - int res, err, bsize, maskOR_msb_offset; - - /* sanity check the input */ - if (size <= 1 || t <= 0) { - return MP_VAL; - } - - /* LTM_PRIME_SAFE implies LTM_PRIME_BBS */ - if (flags & LTM_PRIME_SAFE) { - flags |= LTM_PRIME_BBS; - } - - /* calc the byte size */ - bsize = (size>>3) + ((size&7)?1:0); - - /* we need a buffer of bsize bytes */ - tmp = OPT_CAST(unsigned char) XMALLOC(bsize); - if (tmp == NULL) { - return MP_MEM; - } - - /* calc the maskAND value for the MSbyte*/ - maskAND = ((size&7) == 0) ? 0xFF : (0xFF >> (8 - (size & 7))); - - /* calc the maskOR_msb */ - maskOR_msb = 0; - maskOR_msb_offset = ((size & 7) == 1) ? 1 : 0; - if (flags & LTM_PRIME_2MSB_ON) { - maskOR_msb |= 0x80 >> ((9 - size) & 7); - } - - /* get the maskOR_lsb */ - maskOR_lsb = 1; - if (flags & LTM_PRIME_BBS) { - maskOR_lsb |= 3; - } - - do { - /* read the bytes */ - if (cb(tmp, bsize, dat) != bsize) { - err = MP_VAL; - goto error; - } - - /* work over the MSbyte */ - tmp[0] &= maskAND; - tmp[0] |= 1 << ((size - 1) & 7); - - /* mix in the maskORs */ - tmp[maskOR_msb_offset] |= maskOR_msb; - tmp[bsize-1] |= maskOR_lsb; - - /* read it in */ - if ((err = mp_read_unsigned_bin(a, tmp, bsize)) != MP_OKAY) { goto error; } - - /* is it prime? */ - if ((err = mp_prime_is_prime(a, t, &res)) != MP_OKAY) { goto error; } - if (res == MP_NO) { - continue; - } - - if (flags & LTM_PRIME_SAFE) { - /* see if (a-1)/2 is prime */ - if ((err = mp_sub_d(a, 1, a)) != MP_OKAY) { goto error; } - if ((err = mp_div_2(a, a)) != MP_OKAY) { goto error; } - - /* is it prime? */ - if ((err = mp_prime_is_prime(a, t, &res)) != MP_OKAY) { goto error; } - } - } while (res == MP_NO); - - if (flags & LTM_PRIME_SAFE) { - /* restore a to the original value */ - if ((err = mp_mul_2(a, a)) != MP_OKAY) { goto error; } - if ((err = mp_add_d(a, 1, a)) != MP_OKAY) { goto error; } - } - - err = MP_OKAY; -error: - XFREE(tmp); - return err; -} - - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_prime_random_ex.c */ - -/* Start: bn_mp_radix_size.c */ -#include <tommath.h> -#ifdef BN_MP_RADIX_SIZE_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* returns size of ASCII reprensentation */ -int mp_radix_size (mp_int * a, int radix, int *size) -{ - int res, digs; - mp_int t; - mp_digit d; - - *size = 0; - - /* special case for binary */ - if (radix == 2) { - *size = mp_count_bits (a) + (a->sign == MP_NEG ? 1 : 0) + 1; - return MP_OKAY; - } - - /* make sure the radix is in range */ - if (radix < 2 || radix > 64) { - return MP_VAL; - } - - if (mp_iszero(a) == MP_YES) { - *size = 2; - return MP_OKAY; - } - - /* digs is the digit count */ - digs = 0; - - /* if it's negative add one for the sign */ - if (a->sign == MP_NEG) { - ++digs; - } - - /* init a copy of the input */ - if ((res = mp_init_copy (&t, a)) != MP_OKAY) { - return res; - } - - /* force temp to positive */ - t.sign = MP_ZPOS; - - /* fetch out all of the digits */ - while (mp_iszero (&t) == MP_NO) { - if ((res = mp_div_d (&t, (mp_digit) radix, &t, &d)) != MP_OKAY) { - mp_clear (&t); - return res; - } - ++digs; - } - mp_clear (&t); - - /* return digs + 1, the 1 is for the NULL byte that would be required. */ - *size = digs + 1; - return MP_OKAY; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_radix_size.c */ - -/* Start: bn_mp_radix_smap.c */ -#include <tommath.h> -#ifdef BN_MP_RADIX_SMAP_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* chars used in radix conversions */ -const char *mp_s_rmap = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz+/"; -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_radix_smap.c */ - -/* Start: bn_mp_rand.c */ -#include <tommath.h> -#ifdef BN_MP_RAND_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* makes a pseudo-random int of a given size */ -int -mp_rand (mp_int * a, int digits) -{ - int res; - mp_digit d; - - mp_zero (a); - if (digits <= 0) { - return MP_OKAY; - } - - /* first place a random non-zero digit */ - do { - d = ((mp_digit) abs (rand ())) & MP_MASK; - } while (d == 0); - - if ((res = mp_add_d (a, d, a)) != MP_OKAY) { - return res; - } - - while (--digits > 0) { - if ((res = mp_lshd (a, 1)) != MP_OKAY) { - return res; - } - - if ((res = mp_add_d (a, ((mp_digit) abs (rand ())), a)) != MP_OKAY) { - return res; - } - } - - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_rand.c */ - -/* Start: bn_mp_read_radix.c */ -#include <tommath.h> -#ifdef BN_MP_READ_RADIX_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* read a string [ASCII] in a given radix */ -int mp_read_radix (mp_int * a, const char *str, int radix) -{ - int y, res, neg; - char ch; - - /* zero the digit bignum */ - mp_zero(a); - - /* make sure the radix is ok */ - if (radix < 2 || radix > 64) { - return MP_VAL; - } - - /* if the leading digit is a - * minus set the sign to negative. - */ - if (*str == '-') { - ++str; - neg = MP_NEG; - } else { - neg = MP_ZPOS; - } - - /* set the integer to the default of zero */ - mp_zero (a); - - /* process each digit of the string */ - while (*str) { - /* if the radix < 36 the conversion is case insensitive - * this allows numbers like 1AB and 1ab to represent the same value - * [e.g. in hex] - */ - ch = (char) ((radix < 36) ? toupper ((int)*str) : *str); - for (y = 0; y < 64; y++) { - if (ch == mp_s_rmap[y]) { - break; - } - } - - /* if the char was found in the map - * and is less than the given radix add it - * to the number, otherwise exit the loop. - */ - if (y < radix) { - if ((res = mp_mul_d (a, (mp_digit) radix, a)) != MP_OKAY) { - return res; - } - if ((res = mp_add_d (a, (mp_digit) y, a)) != MP_OKAY) { - return res; - } - } else { - break; - } - ++str; - } - - /* set the sign only if a != 0 */ - if (mp_iszero(a) != 1) { - a->sign = neg; - } - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_read_radix.c */ - -/* Start: bn_mp_read_signed_bin.c */ -#include <tommath.h> -#ifdef BN_MP_READ_SIGNED_BIN_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* read signed bin, big endian, first byte is 0==positive or 1==negative */ -int mp_read_signed_bin (mp_int * a, const unsigned char *b, int c) -{ - int res; - - /* read magnitude */ - if ((res = mp_read_unsigned_bin (a, b + 1, c - 1)) != MP_OKAY) { - return res; - } - - /* first byte is 0 for positive, non-zero for negative */ - if (b[0] == 0) { - a->sign = MP_ZPOS; - } else { - a->sign = MP_NEG; - } - - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_read_signed_bin.c */ - -/* Start: bn_mp_read_unsigned_bin.c */ -#include <tommath.h> -#ifdef BN_MP_READ_UNSIGNED_BIN_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* reads a unsigned char array, assumes the msb is stored first [big endian] */ -int mp_read_unsigned_bin (mp_int * a, const unsigned char *b, int c) -{ - int res; - - /* make sure there are at least two digits */ - if (a->alloc < 2) { - if ((res = mp_grow(a, 2)) != MP_OKAY) { - return res; - } - } - - /* zero the int */ - mp_zero (a); - - /* read the bytes in */ - while (c-- > 0) { - if ((res = mp_mul_2d (a, 8, a)) != MP_OKAY) { - return res; - } - -#ifndef MP_8BIT - a->dp[0] |= *b++; - a->used += 1; -#else - a->dp[0] = (*b & MP_MASK); - a->dp[1] |= ((*b++ >> 7U) & 1); - a->used += 2; -#endif - } - mp_clamp (a); - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_read_unsigned_bin.c */ - -/* Start: bn_mp_reduce.c */ -#include <tommath.h> -#ifdef BN_MP_REDUCE_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* reduces x mod m, assumes 0 < x < m**2, mu is - * precomputed via mp_reduce_setup. - * From HAC pp.604 Algorithm 14.42 - */ -int mp_reduce (mp_int * x, mp_int * m, mp_int * mu) -{ - mp_int q; - int res, um = m->used; - - /* q = x */ - if ((res = mp_init_copy (&q, x)) != MP_OKAY) { - return res; - } - - /* q1 = x / b**(k-1) */ - mp_rshd (&q, um - 1); - - /* according to HAC this optimization is ok */ - if (((unsigned long) um) > (((mp_digit)1) << (DIGIT_BIT - 1))) { - if ((res = mp_mul (&q, mu, &q)) != MP_OKAY) { - goto CLEANUP; - } - } else { -#ifdef BN_S_MP_MUL_HIGH_DIGS_C - if ((res = s_mp_mul_high_digs (&q, mu, &q, um)) != MP_OKAY) { - goto CLEANUP; - } -#elif defined(BN_FAST_S_MP_MUL_HIGH_DIGS_C) - if ((res = fast_s_mp_mul_high_digs (&q, mu, &q, um)) != MP_OKAY) { - goto CLEANUP; - } -#else - { - res = MP_VAL; - goto CLEANUP; - } -#endif - } - - /* q3 = q2 / b**(k+1) */ - mp_rshd (&q, um + 1); - - /* x = x mod b**(k+1), quick (no division) */ - if ((res = mp_mod_2d (x, DIGIT_BIT * (um + 1), x)) != MP_OKAY) { - goto CLEANUP; - } - - /* q = q * m mod b**(k+1), quick (no division) */ - if ((res = s_mp_mul_digs (&q, m, &q, um + 1)) != MP_OKAY) { - goto CLEANUP; - } - - /* x = x - q */ - if ((res = mp_sub (x, &q, x)) != MP_OKAY) { - goto CLEANUP; - } - - /* If x < 0, add b**(k+1) to it */ - if (mp_cmp_d (x, 0) == MP_LT) { - mp_set (&q, 1); - if ((res = mp_lshd (&q, um + 1)) != MP_OKAY) - goto CLEANUP; - if ((res = mp_add (x, &q, x)) != MP_OKAY) - goto CLEANUP; - } - - /* Back off if it's too big */ - while (mp_cmp (x, m) != MP_LT) { - if ((res = s_mp_sub (x, m, x)) != MP_OKAY) { - goto CLEANUP; - } - } - -CLEANUP: - mp_clear (&q); - - return res; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_reduce.c */ - -/* Start: bn_mp_reduce_2k.c */ -#include <tommath.h> -#ifdef BN_MP_REDUCE_2K_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* reduces a modulo n where n is of the form 2**p - d */ -int mp_reduce_2k(mp_int *a, mp_int *n, mp_digit d) -{ - mp_int q; - int p, res; - - if ((res = mp_init(&q)) != MP_OKAY) { - return res; - } - - p = mp_count_bits(n); -top: - /* q = a/2**p, a = a mod 2**p */ - if ((res = mp_div_2d(a, p, &q, a)) != MP_OKAY) { - goto ERR; - } - - if (d != 1) { - /* q = q * d */ - if ((res = mp_mul_d(&q, d, &q)) != MP_OKAY) { - goto ERR; - } - } - - /* a = a + q */ - if ((res = s_mp_add(a, &q, a)) != MP_OKAY) { - goto ERR; - } - - if (mp_cmp_mag(a, n) != MP_LT) { - s_mp_sub(a, n, a); - goto top; - } - -ERR: - mp_clear(&q); - return res; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_reduce_2k.c */ - -/* Start: bn_mp_reduce_2k_l.c */ -#include <tommath.h> -#ifdef BN_MP_REDUCE_2K_L_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* reduces a modulo n where n is of the form 2**p - d - This differs from reduce_2k since "d" can be larger - than a single digit. -*/ -int mp_reduce_2k_l(mp_int *a, mp_int *n, mp_int *d) -{ - mp_int q; - int p, res; - - if ((res = mp_init(&q)) != MP_OKAY) { - return res; - } - - p = mp_count_bits(n); -top: - /* q = a/2**p, a = a mod 2**p */ - if ((res = mp_div_2d(a, p, &q, a)) != MP_OKAY) { - goto ERR; - } - - /* q = q * d */ - if ((res = mp_mul(&q, d, &q)) != MP_OKAY) { - goto ERR; - } - - /* a = a + q */ - if ((res = s_mp_add(a, &q, a)) != MP_OKAY) { - goto ERR; - } - - if (mp_cmp_mag(a, n) != MP_LT) { - s_mp_sub(a, n, a); - goto top; - } - -ERR: - mp_clear(&q); - return res; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_reduce_2k_l.c */ - -/* Start: bn_mp_reduce_2k_setup.c */ -#include <tommath.h> -#ifdef BN_MP_REDUCE_2K_SETUP_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* determines the setup value */ -int mp_reduce_2k_setup(mp_int *a, mp_digit *d) -{ - int res, p; - mp_int tmp; - - if ((res = mp_init(&tmp)) != MP_OKAY) { - return res; - } - - p = mp_count_bits(a); - if ((res = mp_2expt(&tmp, p)) != MP_OKAY) { - mp_clear(&tmp); - return res; - } - - if ((res = s_mp_sub(&tmp, a, &tmp)) != MP_OKAY) { - mp_clear(&tmp); - return res; - } - - *d = tmp.dp[0]; - mp_clear(&tmp); - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_reduce_2k_setup.c */ - -/* Start: bn_mp_reduce_2k_setup_l.c */ -#include <tommath.h> -#ifdef BN_MP_REDUCE_2K_SETUP_L_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* determines the setup value */ -int mp_reduce_2k_setup_l(mp_int *a, mp_int *d) -{ - int res; - mp_int tmp; - - if ((res = mp_init(&tmp)) != MP_OKAY) { - return res; - } - - if ((res = mp_2expt(&tmp, mp_count_bits(a))) != MP_OKAY) { - goto ERR; - } - - if ((res = s_mp_sub(&tmp, a, d)) != MP_OKAY) { - goto ERR; - } - -ERR: - mp_clear(&tmp); - return res; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_reduce_2k_setup_l.c */ - -/* Start: bn_mp_reduce_is_2k.c */ -#include <tommath.h> -#ifdef BN_MP_REDUCE_IS_2K_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* determines if mp_reduce_2k can be used */ -int mp_reduce_is_2k(mp_int *a) -{ - int ix, iy, iw; - mp_digit iz; - - if (a->used == 0) { - return MP_NO; - } else if (a->used == 1) { - return MP_YES; - } else if (a->used > 1) { - iy = mp_count_bits(a); - iz = 1; - iw = 1; - - /* Test every bit from the second digit up, must be 1 */ - for (ix = DIGIT_BIT; ix < iy; ix++) { - if ((a->dp[iw] & iz) == 0) { - return MP_NO; - } - iz <<= 1; - if (iz > (mp_digit)MP_MASK) { - ++iw; - iz = 1; - } - } - } - return MP_YES; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_reduce_is_2k.c */ - -/* Start: bn_mp_reduce_is_2k_l.c */ -#include <tommath.h> -#ifdef BN_MP_REDUCE_IS_2K_L_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* determines if reduce_2k_l can be used */ -int mp_reduce_is_2k_l(mp_int *a) -{ - int ix, iy; - - if (a->used == 0) { - return MP_NO; - } else if (a->used == 1) { - return MP_YES; - } else if (a->used > 1) { - /* if more than half of the digits are -1 we're sold */ - for (iy = ix = 0; ix < a->used; ix++) { - if (a->dp[ix] == MP_MASK) { - ++iy; - } - } - return (iy >= (a->used/2)) ? MP_YES : MP_NO; - - } - return MP_NO; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_reduce_is_2k_l.c */ - -/* Start: bn_mp_reduce_setup.c */ -#include <tommath.h> -#ifdef BN_MP_REDUCE_SETUP_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* pre-calculate the value required for Barrett reduction - * For a given modulus "b" it calulates the value required in "a" - */ -int mp_reduce_setup (mp_int * a, mp_int * b) -{ - int res; - - if ((res = mp_2expt (a, b->used * 2 * DIGIT_BIT)) != MP_OKAY) { - return res; - } - return mp_div (a, b, a, NULL); -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_reduce_setup.c */ - -/* Start: bn_mp_rshd.c */ -#include <tommath.h> -#ifdef BN_MP_RSHD_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* shift right a certain amount of digits */ -void mp_rshd (mp_int * a, int b) -{ - int x; - - /* if b <= 0 then ignore it */ - if (b <= 0) { - return; - } - - /* if b > used then simply zero it and return */ - if (a->used <= b) { - mp_zero (a); - return; - } - - { - register mp_digit *bottom, *top; - - /* shift the digits down */ - - /* bottom */ - bottom = a->dp; - - /* top [offset into digits] */ - top = a->dp + b; - - /* this is implemented as a sliding window where - * the window is b-digits long and digits from - * the top of the window are copied to the bottom - * - * e.g. - - b-2 | b-1 | b0 | b1 | b2 | ... | bb | ----> - /\ | ----> - \-------------------/ ----> - */ - for (x = 0; x < (a->used - b); x++) { - *bottom++ = *top++; - } - - /* zero the top digits */ - for (; x < a->used; x++) { - *bottom++ = 0; - } - } - - /* remove excess digits */ - a->used -= b; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_rshd.c */ - -/* Start: bn_mp_set.c */ -#include <tommath.h> -#ifdef BN_MP_SET_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* set to a digit */ -void mp_set (mp_int * a, mp_digit b) -{ - mp_zero (a); - a->dp[0] = b & MP_MASK; - a->used = (a->dp[0] != 0) ? 1 : 0; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_set.c */ - -/* Start: bn_mp_set_int.c */ -#include <tommath.h> -#ifdef BN_MP_SET_INT_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* set a 32-bit const */ -int mp_set_int (mp_int * a, unsigned long b) -{ - int x, res; - - mp_zero (a); - - /* set four bits at a time */ - for (x = 0; x < 8; x++) { - /* shift the number up four bits */ - if ((res = mp_mul_2d (a, 4, a)) != MP_OKAY) { - return res; - } - - /* OR in the top four bits of the source */ - a->dp[0] |= (b >> 28) & 15; - - /* shift the source up to the next four bits */ - b <<= 4; - - /* ensure that digits are not clamped off */ - a->used += 1; - } - mp_clamp (a); - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_set_int.c */ - -/* Start: bn_mp_shrink.c */ -#include <tommath.h> -#ifdef BN_MP_SHRINK_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* shrink a bignum */ -int mp_shrink (mp_int * a) -{ - mp_digit *tmp; - int used = 1; - - if(a->used > 0) - used = a->used; - - if (a->alloc != used) { - if ((tmp = OPT_CAST(mp_digit) XREALLOC (a->dp, sizeof (mp_digit) * used)) == NULL) { - return MP_MEM; - } - a->dp = tmp; - a->alloc = used; - } - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_shrink.c */ - -/* Start: bn_mp_signed_bin_size.c */ -#include <tommath.h> -#ifdef BN_MP_SIGNED_BIN_SIZE_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* get the size for an signed equivalent */ -int mp_signed_bin_size (mp_int * a) -{ - return 1 + mp_unsigned_bin_size (a); -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_signed_bin_size.c */ - -/* Start: bn_mp_sqr.c */ -#include <tommath.h> -#ifdef BN_MP_SQR_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* computes b = a*a */ -int -mp_sqr (mp_int * a, mp_int * b) -{ - int res; - -#ifdef BN_MP_TOOM_SQR_C - /* use Toom-Cook? */ - if (a->used >= TOOM_SQR_CUTOFF) { - res = mp_toom_sqr(a, b); - /* Karatsuba? */ - } else -#endif -#ifdef BN_MP_KARATSUBA_SQR_C -if (a->used >= KARATSUBA_SQR_CUTOFF) { - res = mp_karatsuba_sqr (a, b); - } else -#endif - { -#ifdef BN_FAST_S_MP_SQR_C - /* can we use the fast comba multiplier? */ - if ((a->used * 2 + 1) < MP_WARRAY && - a->used < - (1 << (sizeof(mp_word) * CHAR_BIT - 2*DIGIT_BIT - 1))) { - res = fast_s_mp_sqr (a, b); - } else -#endif -#ifdef BN_S_MP_SQR_C - res = s_mp_sqr (a, b); -#else - res = MP_VAL; -#endif - } - b->sign = MP_ZPOS; - return res; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_sqr.c */ - -/* Start: bn_mp_sqrmod.c */ -#include <tommath.h> -#ifdef BN_MP_SQRMOD_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* c = a * a (mod b) */ -int -mp_sqrmod (mp_int * a, mp_int * b, mp_int * c) -{ - int res; - mp_int t; - - if ((res = mp_init (&t)) != MP_OKAY) { - return res; - } - - if ((res = mp_sqr (a, &t)) != MP_OKAY) { - mp_clear (&t); - return res; - } - res = mp_mod (&t, b, c); - mp_clear (&t); - return res; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_sqrmod.c */ - -/* Start: bn_mp_sqrt.c */ -#include <tommath.h> -#ifdef BN_MP_SQRT_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* this function is less generic than mp_n_root, simpler and faster */ -int mp_sqrt(mp_int *arg, mp_int *ret) -{ - int res; - mp_int t1,t2; - - /* must be positive */ - if (arg->sign == MP_NEG) { - return MP_VAL; - } - - /* easy out */ - if (mp_iszero(arg) == MP_YES) { - mp_zero(ret); - return MP_OKAY; - } - - if ((res = mp_init_copy(&t1, arg)) != MP_OKAY) { - return res; - } - - if ((res = mp_init(&t2)) != MP_OKAY) { - goto E2; - } - - /* First approx. (not very bad for large arg) */ - mp_rshd (&t1,t1.used/2); - - /* t1 > 0 */ - if ((res = mp_div(arg,&t1,&t2,NULL)) != MP_OKAY) { - goto E1; - } - if ((res = mp_add(&t1,&t2,&t1)) != MP_OKAY) { - goto E1; - } - if ((res = mp_div_2(&t1,&t1)) != MP_OKAY) { - goto E1; - } - /* And now t1 > sqrt(arg) */ - do { - if ((res = mp_div(arg,&t1,&t2,NULL)) != MP_OKAY) { - goto E1; - } - if ((res = mp_add(&t1,&t2,&t1)) != MP_OKAY) { - goto E1; - } - if ((res = mp_div_2(&t1,&t1)) != MP_OKAY) { - goto E1; - } - /* t1 >= sqrt(arg) >= t2 at this point */ - } while (mp_cmp_mag(&t1,&t2) == MP_GT); - - mp_exch(&t1,ret); - -E1: mp_clear(&t2); -E2: mp_clear(&t1); - return res; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_sqrt.c */ - -/* Start: bn_mp_sub.c */ -#include <tommath.h> -#ifdef BN_MP_SUB_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* high level subtraction (handles signs) */ -int -mp_sub (mp_int * a, mp_int * b, mp_int * c) -{ - int sa, sb, res; - - sa = a->sign; - sb = b->sign; - - if (sa != sb) { - /* subtract a negative from a positive, OR */ - /* subtract a positive from a negative. */ - /* In either case, ADD their magnitudes, */ - /* and use the sign of the first number. */ - c->sign = sa; - res = s_mp_add (a, b, c); - } else { - /* subtract a positive from a positive, OR */ - /* subtract a negative from a negative. */ - /* First, take the difference between their */ - /* magnitudes, then... */ - if (mp_cmp_mag (a, b) != MP_LT) { - /* Copy the sign from the first */ - c->sign = sa; - /* The first has a larger or equal magnitude */ - res = s_mp_sub (a, b, c); - } else { - /* The result has the *opposite* sign from */ - /* the first number. */ - c->sign = (sa == MP_ZPOS) ? MP_NEG : MP_ZPOS; - /* The second has a larger magnitude */ - res = s_mp_sub (b, a, c); - } - } - return res; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_sub.c */ - -/* Start: bn_mp_sub_d.c */ -#include <tommath.h> -#ifdef BN_MP_SUB_D_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* single digit subtraction */ -int -mp_sub_d (mp_int * a, mp_digit b, mp_int * c) -{ - mp_digit *tmpa, *tmpc, mu; - int res, ix, oldused; - - /* grow c as required */ - if (c->alloc < a->used + 1) { - if ((res = mp_grow(c, a->used + 1)) != MP_OKAY) { - return res; - } - } - - /* if a is negative just do an unsigned - * addition [with fudged signs] - */ - if (a->sign == MP_NEG) { - a->sign = MP_ZPOS; - res = mp_add_d(a, b, c); - a->sign = c->sign = MP_NEG; - - /* clamp */ - mp_clamp(c); - - return res; - } - - /* setup regs */ - oldused = c->used; - tmpa = a->dp; - tmpc = c->dp; - - /* if a <= b simply fix the single digit */ - if ((a->used == 1 && a->dp[0] <= b) || a->used == 0) { - if (a->used == 1) { - *tmpc++ = b - *tmpa; - } else { - *tmpc++ = b; - } - ix = 1; - - /* negative/1digit */ - c->sign = MP_NEG; - c->used = 1; - } else { - /* positive/size */ - c->sign = MP_ZPOS; - c->used = a->used; - - /* subtract first digit */ - *tmpc = *tmpa++ - b; - mu = *tmpc >> (sizeof(mp_digit) * CHAR_BIT - 1); - *tmpc++ &= MP_MASK; - - /* handle rest of the digits */ - for (ix = 1; ix < a->used; ix++) { - *tmpc = *tmpa++ - mu; - mu = *tmpc >> (sizeof(mp_digit) * CHAR_BIT - 1); - *tmpc++ &= MP_MASK; - } - } - - /* zero excess digits */ - while (ix++ < oldused) { - *tmpc++ = 0; - } - mp_clamp(c); - return MP_OKAY; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_sub_d.c */ - -/* Start: bn_mp_submod.c */ -#include <tommath.h> -#ifdef BN_MP_SUBMOD_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* d = a - b (mod c) */ -int -mp_submod (mp_int * a, mp_int * b, mp_int * c, mp_int * d) -{ - int res; - mp_int t; - - - if ((res = mp_init (&t)) != MP_OKAY) { - return res; - } - - if ((res = mp_sub (a, b, &t)) != MP_OKAY) { - mp_clear (&t); - return res; - } - res = mp_mod (&t, c, d); - mp_clear (&t); - return res; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_submod.c */ - -/* Start: bn_mp_to_signed_bin.c */ -#include <tommath.h> -#ifdef BN_MP_TO_SIGNED_BIN_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* store in signed [big endian] format */ -int mp_to_signed_bin (mp_int * a, unsigned char *b) -{ - int res; - - if ((res = mp_to_unsigned_bin (a, b + 1)) != MP_OKAY) { - return res; - } - b[0] = (unsigned char) ((a->sign == MP_ZPOS) ? 0 : 1); - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_to_signed_bin.c */ - -/* Start: bn_mp_to_signed_bin_n.c */ -#include <tommath.h> -#ifdef BN_MP_TO_SIGNED_BIN_N_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* store in signed [big endian] format */ -int mp_to_signed_bin_n (mp_int * a, unsigned char *b, unsigned long *outlen) -{ - if (*outlen < (unsigned long)mp_signed_bin_size(a)) { - return MP_VAL; - } - *outlen = mp_signed_bin_size(a); - return mp_to_signed_bin(a, b); -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_to_signed_bin_n.c */ - -/* Start: bn_mp_to_unsigned_bin.c */ -#include <tommath.h> -#ifdef BN_MP_TO_UNSIGNED_BIN_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* store in unsigned [big endian] format */ -int mp_to_unsigned_bin (mp_int * a, unsigned char *b) -{ - int x, res; - mp_int t; - - if ((res = mp_init_copy (&t, a)) != MP_OKAY) { - return res; - } - - x = 0; - while (mp_iszero (&t) == 0) { -#ifndef MP_8BIT - b[x++] = (unsigned char) (t.dp[0] & 255); -#else - b[x++] = (unsigned char) (t.dp[0] | ((t.dp[1] & 0x01) << 7)); -#endif - if ((res = mp_div_2d (&t, 8, &t, NULL)) != MP_OKAY) { - mp_clear (&t); - return res; - } - } - bn_reverse (b, x); - mp_clear (&t); - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_to_unsigned_bin.c */ - -/* Start: bn_mp_to_unsigned_bin_n.c */ -#include <tommath.h> -#ifdef BN_MP_TO_UNSIGNED_BIN_N_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* store in unsigned [big endian] format */ -int mp_to_unsigned_bin_n (mp_int * a, unsigned char *b, unsigned long *outlen) -{ - if (*outlen < (unsigned long)mp_unsigned_bin_size(a)) { - return MP_VAL; - } - *outlen = mp_unsigned_bin_size(a); - return mp_to_unsigned_bin(a, b); -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_to_unsigned_bin_n.c */ - -/* Start: bn_mp_toom_mul.c */ -#include <tommath.h> -#ifdef BN_MP_TOOM_MUL_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* multiplication using the Toom-Cook 3-way algorithm - * - * Much more complicated than Karatsuba but has a lower - * asymptotic running time of O(N**1.464). This algorithm is - * only particularly useful on VERY large inputs - * (we're talking 1000s of digits here...). -*/ -int mp_toom_mul(mp_int *a, mp_int *b, mp_int *c) -{ - mp_int w0, w1, w2, w3, w4, tmp1, tmp2, a0, a1, a2, b0, b1, b2; - int res, B; - - /* init temps */ - if ((res = mp_init_multi(&w0, &w1, &w2, &w3, &w4, - &a0, &a1, &a2, &b0, &b1, - &b2, &tmp1, &tmp2, NULL)) != MP_OKAY) { - return res; - } - - /* B */ - B = MIN(a->used, b->used) / 3; - - /* a = a2 * B**2 + a1 * B + a0 */ - if ((res = mp_mod_2d(a, DIGIT_BIT * B, &a0)) != MP_OKAY) { - goto ERR; - } - - if ((res = mp_copy(a, &a1)) != MP_OKAY) { - goto ERR; - } - mp_rshd(&a1, B); - mp_mod_2d(&a1, DIGIT_BIT * B, &a1); - - if ((res = mp_copy(a, &a2)) != MP_OKAY) { - goto ERR; - } - mp_rshd(&a2, B*2); - - /* b = b2 * B**2 + b1 * B + b0 */ - if ((res = mp_mod_2d(b, DIGIT_BIT * B, &b0)) != MP_OKAY) { - goto ERR; - } - - if ((res = mp_copy(b, &b1)) != MP_OKAY) { - goto ERR; - } - mp_rshd(&b1, B); - mp_mod_2d(&b1, DIGIT_BIT * B, &b1); - - if ((res = mp_copy(b, &b2)) != MP_OKAY) { - goto ERR; - } - mp_rshd(&b2, B*2); - - /* w0 = a0*b0 */ - if ((res = mp_mul(&a0, &b0, &w0)) != MP_OKAY) { - goto ERR; - } - - /* w4 = a2 * b2 */ - if ((res = mp_mul(&a2, &b2, &w4)) != MP_OKAY) { - goto ERR; - } - - /* w1 = (a2 + 2(a1 + 2a0))(b2 + 2(b1 + 2b0)) */ - if ((res = mp_mul_2(&a0, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_add(&tmp1, &a1, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_mul_2(&tmp1, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_add(&tmp1, &a2, &tmp1)) != MP_OKAY) { - goto ERR; - } - - if ((res = mp_mul_2(&b0, &tmp2)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_add(&tmp2, &b1, &tmp2)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_mul_2(&tmp2, &tmp2)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_add(&tmp2, &b2, &tmp2)) != MP_OKAY) { - goto ERR; - } - - if ((res = mp_mul(&tmp1, &tmp2, &w1)) != MP_OKAY) { - goto ERR; - } - - /* w3 = (a0 + 2(a1 + 2a2))(b0 + 2(b1 + 2b2)) */ - if ((res = mp_mul_2(&a2, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_add(&tmp1, &a1, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_mul_2(&tmp1, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_add(&tmp1, &a0, &tmp1)) != MP_OKAY) { - goto ERR; - } - - if ((res = mp_mul_2(&b2, &tmp2)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_add(&tmp2, &b1, &tmp2)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_mul_2(&tmp2, &tmp2)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_add(&tmp2, &b0, &tmp2)) != MP_OKAY) { - goto ERR; - } - - if ((res = mp_mul(&tmp1, &tmp2, &w3)) != MP_OKAY) { - goto ERR; - } - - - /* w2 = (a2 + a1 + a0)(b2 + b1 + b0) */ - if ((res = mp_add(&a2, &a1, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_add(&tmp1, &a0, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_add(&b2, &b1, &tmp2)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_add(&tmp2, &b0, &tmp2)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_mul(&tmp1, &tmp2, &w2)) != MP_OKAY) { - goto ERR; - } - - /* now solve the matrix - - 0 0 0 0 1 - 1 2 4 8 16 - 1 1 1 1 1 - 16 8 4 2 1 - 1 0 0 0 0 - - using 12 subtractions, 4 shifts, - 2 small divisions and 1 small multiplication - */ - - /* r1 - r4 */ - if ((res = mp_sub(&w1, &w4, &w1)) != MP_OKAY) { - goto ERR; - } - /* r3 - r0 */ - if ((res = mp_sub(&w3, &w0, &w3)) != MP_OKAY) { - goto ERR; - } - /* r1/2 */ - if ((res = mp_div_2(&w1, &w1)) != MP_OKAY) { - goto ERR; - } - /* r3/2 */ - if ((res = mp_div_2(&w3, &w3)) != MP_OKAY) { - goto ERR; - } - /* r2 - r0 - r4 */ - if ((res = mp_sub(&w2, &w0, &w2)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_sub(&w2, &w4, &w2)) != MP_OKAY) { - goto ERR; - } - /* r1 - r2 */ - if ((res = mp_sub(&w1, &w2, &w1)) != MP_OKAY) { - goto ERR; - } - /* r3 - r2 */ - if ((res = mp_sub(&w3, &w2, &w3)) != MP_OKAY) { - goto ERR; - } - /* r1 - 8r0 */ - if ((res = mp_mul_2d(&w0, 3, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_sub(&w1, &tmp1, &w1)) != MP_OKAY) { - goto ERR; - } - /* r3 - 8r4 */ - if ((res = mp_mul_2d(&w4, 3, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_sub(&w3, &tmp1, &w3)) != MP_OKAY) { - goto ERR; - } - /* 3r2 - r1 - r3 */ - if ((res = mp_mul_d(&w2, 3, &w2)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_sub(&w2, &w1, &w2)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_sub(&w2, &w3, &w2)) != MP_OKAY) { - goto ERR; - } - /* r1 - r2 */ - if ((res = mp_sub(&w1, &w2, &w1)) != MP_OKAY) { - goto ERR; - } - /* r3 - r2 */ - if ((res = mp_sub(&w3, &w2, &w3)) != MP_OKAY) { - goto ERR; - } - /* r1/3 */ - if ((res = mp_div_3(&w1, &w1, NULL)) != MP_OKAY) { - goto ERR; - } - /* r3/3 */ - if ((res = mp_div_3(&w3, &w3, NULL)) != MP_OKAY) { - goto ERR; - } - - /* at this point shift W[n] by B*n */ - if ((res = mp_lshd(&w1, 1*B)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_lshd(&w2, 2*B)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_lshd(&w3, 3*B)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_lshd(&w4, 4*B)) != MP_OKAY) { - goto ERR; - } - - if ((res = mp_add(&w0, &w1, c)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_add(&w2, &w3, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_add(&w4, &tmp1, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_add(&tmp1, c, c)) != MP_OKAY) { - goto ERR; - } - -ERR: - mp_clear_multi(&w0, &w1, &w2, &w3, &w4, - &a0, &a1, &a2, &b0, &b1, - &b2, &tmp1, &tmp2, NULL); - return res; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_toom_mul.c */ - -/* Start: bn_mp_toom_sqr.c */ -#include <tommath.h> -#ifdef BN_MP_TOOM_SQR_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* squaring using Toom-Cook 3-way algorithm */ -int -mp_toom_sqr(mp_int *a, mp_int *b) -{ - mp_int w0, w1, w2, w3, w4, tmp1, a0, a1, a2; - int res, B; - - /* init temps */ - if ((res = mp_init_multi(&w0, &w1, &w2, &w3, &w4, &a0, &a1, &a2, &tmp1, NULL)) != MP_OKAY) { - return res; - } - - /* B */ - B = a->used / 3; - - /* a = a2 * B**2 + a1 * B + a0 */ - if ((res = mp_mod_2d(a, DIGIT_BIT * B, &a0)) != MP_OKAY) { - goto ERR; - } - - if ((res = mp_copy(a, &a1)) != MP_OKAY) { - goto ERR; - } - mp_rshd(&a1, B); - mp_mod_2d(&a1, DIGIT_BIT * B, &a1); - - if ((res = mp_copy(a, &a2)) != MP_OKAY) { - goto ERR; - } - mp_rshd(&a2, B*2); - - /* w0 = a0*a0 */ - if ((res = mp_sqr(&a0, &w0)) != MP_OKAY) { - goto ERR; - } - - /* w4 = a2 * a2 */ - if ((res = mp_sqr(&a2, &w4)) != MP_OKAY) { - goto ERR; - } - - /* w1 = (a2 + 2(a1 + 2a0))**2 */ - if ((res = mp_mul_2(&a0, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_add(&tmp1, &a1, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_mul_2(&tmp1, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_add(&tmp1, &a2, &tmp1)) != MP_OKAY) { - goto ERR; - } - - if ((res = mp_sqr(&tmp1, &w1)) != MP_OKAY) { - goto ERR; - } - - /* w3 = (a0 + 2(a1 + 2a2))**2 */ - if ((res = mp_mul_2(&a2, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_add(&tmp1, &a1, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_mul_2(&tmp1, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_add(&tmp1, &a0, &tmp1)) != MP_OKAY) { - goto ERR; - } - - if ((res = mp_sqr(&tmp1, &w3)) != MP_OKAY) { - goto ERR; - } - - - /* w2 = (a2 + a1 + a0)**2 */ - if ((res = mp_add(&a2, &a1, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_add(&tmp1, &a0, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_sqr(&tmp1, &w2)) != MP_OKAY) { - goto ERR; - } - - /* now solve the matrix - - 0 0 0 0 1 - 1 2 4 8 16 - 1 1 1 1 1 - 16 8 4 2 1 - 1 0 0 0 0 - - using 12 subtractions, 4 shifts, 2 small divisions and 1 small multiplication. - */ - - /* r1 - r4 */ - if ((res = mp_sub(&w1, &w4, &w1)) != MP_OKAY) { - goto ERR; - } - /* r3 - r0 */ - if ((res = mp_sub(&w3, &w0, &w3)) != MP_OKAY) { - goto ERR; - } - /* r1/2 */ - if ((res = mp_div_2(&w1, &w1)) != MP_OKAY) { - goto ERR; - } - /* r3/2 */ - if ((res = mp_div_2(&w3, &w3)) != MP_OKAY) { - goto ERR; - } - /* r2 - r0 - r4 */ - if ((res = mp_sub(&w2, &w0, &w2)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_sub(&w2, &w4, &w2)) != MP_OKAY) { - goto ERR; - } - /* r1 - r2 */ - if ((res = mp_sub(&w1, &w2, &w1)) != MP_OKAY) { - goto ERR; - } - /* r3 - r2 */ - if ((res = mp_sub(&w3, &w2, &w3)) != MP_OKAY) { - goto ERR; - } - /* r1 - 8r0 */ - if ((res = mp_mul_2d(&w0, 3, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_sub(&w1, &tmp1, &w1)) != MP_OKAY) { - goto ERR; - } - /* r3 - 8r4 */ - if ((res = mp_mul_2d(&w4, 3, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_sub(&w3, &tmp1, &w3)) != MP_OKAY) { - goto ERR; - } - /* 3r2 - r1 - r3 */ - if ((res = mp_mul_d(&w2, 3, &w2)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_sub(&w2, &w1, &w2)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_sub(&w2, &w3, &w2)) != MP_OKAY) { - goto ERR; - } - /* r1 - r2 */ - if ((res = mp_sub(&w1, &w2, &w1)) != MP_OKAY) { - goto ERR; - } - /* r3 - r2 */ - if ((res = mp_sub(&w3, &w2, &w3)) != MP_OKAY) { - goto ERR; - } - /* r1/3 */ - if ((res = mp_div_3(&w1, &w1, NULL)) != MP_OKAY) { - goto ERR; - } - /* r3/3 */ - if ((res = mp_div_3(&w3, &w3, NULL)) != MP_OKAY) { - goto ERR; - } - - /* at this point shift W[n] by B*n */ - if ((res = mp_lshd(&w1, 1*B)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_lshd(&w2, 2*B)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_lshd(&w3, 3*B)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_lshd(&w4, 4*B)) != MP_OKAY) { - goto ERR; - } - - if ((res = mp_add(&w0, &w1, b)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_add(&w2, &w3, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_add(&w4, &tmp1, &tmp1)) != MP_OKAY) { - goto ERR; - } - if ((res = mp_add(&tmp1, b, b)) != MP_OKAY) { - goto ERR; - } - -ERR: - mp_clear_multi(&w0, &w1, &w2, &w3, &w4, &a0, &a1, &a2, &tmp1, NULL); - return res; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_toom_sqr.c */ - -/* Start: bn_mp_toradix.c */ -#include <tommath.h> -#ifdef BN_MP_TORADIX_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* stores a bignum as a ASCII string in a given radix (2..64) */ -int mp_toradix (mp_int * a, char *str, int radix) -{ - int res, digs; - mp_int t; - mp_digit d; - char *_s = str; - - /* check range of the radix */ - if (radix < 2 || radix > 64) { - return MP_VAL; - } - - /* quick out if its zero */ - if (mp_iszero(a) == 1) { - *str++ = '0'; - *str = '\0'; - return MP_OKAY; - } - - if ((res = mp_init_copy (&t, a)) != MP_OKAY) { - return res; - } - - /* if it is negative output a - */ - if (t.sign == MP_NEG) { - ++_s; - *str++ = '-'; - t.sign = MP_ZPOS; - } - - digs = 0; - while (mp_iszero (&t) == 0) { - if ((res = mp_div_d (&t, (mp_digit) radix, &t, &d)) != MP_OKAY) { - mp_clear (&t); - return res; - } - *str++ = mp_s_rmap[d]; - ++digs; - } - - /* reverse the digits of the string. In this case _s points - * to the first digit [exluding the sign] of the number] - */ - bn_reverse ((unsigned char *)_s, digs); - - /* append a NULL so the string is properly terminated */ - *str = '\0'; - - mp_clear (&t); - return MP_OKAY; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_toradix.c */ - -/* Start: bn_mp_toradix_n.c */ -#include <tommath.h> -#ifdef BN_MP_TORADIX_N_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* stores a bignum as a ASCII string in a given radix (2..64) - * - * Stores upto maxlen-1 chars and always a NULL byte - */ -int mp_toradix_n(mp_int * a, char *str, int radix, int maxlen) -{ - int res, digs; - mp_int t; - mp_digit d; - char *_s = str; - - /* check range of the maxlen, radix */ - if (maxlen < 2 || radix < 2 || radix > 64) { - return MP_VAL; - } - - /* quick out if its zero */ - if (mp_iszero(a) == MP_YES) { - *str++ = '0'; - *str = '\0'; - return MP_OKAY; - } - - if ((res = mp_init_copy (&t, a)) != MP_OKAY) { - return res; - } - - /* if it is negative output a - */ - if (t.sign == MP_NEG) { - /* we have to reverse our digits later... but not the - sign!! */ - ++_s; - - /* store the flag and mark the number as positive */ - *str++ = '-'; - t.sign = MP_ZPOS; - - /* subtract a char */ - --maxlen; - } - - digs = 0; - while (mp_iszero (&t) == 0) { - if (--maxlen < 1) { - /* no more room */ - break; - } - if ((res = mp_div_d (&t, (mp_digit) radix, &t, &d)) != MP_OKAY) { - mp_clear (&t); - return res; - } - *str++ = mp_s_rmap[d]; - ++digs; - } - - /* reverse the digits of the string. In this case _s points - * to the first digit [exluding the sign] of the number - */ - bn_reverse ((unsigned char *)_s, digs); - - /* append a NULL so the string is properly terminated */ - *str = '\0'; - - mp_clear (&t); - return MP_OKAY; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_toradix_n.c */ - -/* Start: bn_mp_unsigned_bin_size.c */ -#include <tommath.h> -#ifdef BN_MP_UNSIGNED_BIN_SIZE_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* get the size for an unsigned equivalent */ -int mp_unsigned_bin_size (mp_int * a) -{ - int size = mp_count_bits (a); - return (size / 8 + ((size & 7) != 0 ? 1 : 0)); -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_unsigned_bin_size.c */ - -/* Start: bn_mp_xor.c */ -#include <tommath.h> -#ifdef BN_MP_XOR_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* XOR two ints together */ -int -mp_xor (mp_int * a, mp_int * b, mp_int * c) -{ - int res, ix, px; - mp_int t, *x; - - if (a->used > b->used) { - if ((res = mp_init_copy (&t, a)) != MP_OKAY) { - return res; - } - px = b->used; - x = b; - } else { - if ((res = mp_init_copy (&t, b)) != MP_OKAY) { - return res; - } - px = a->used; - x = a; - } - - for (ix = 0; ix < px; ix++) { - t.dp[ix] ^= x->dp[ix]; - } - mp_clamp (&t); - mp_exch (c, &t); - mp_clear (&t); - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_xor.c */ - -/* Start: bn_mp_zero.c */ -#include <tommath.h> -#ifdef BN_MP_ZERO_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* set to zero */ -void mp_zero (mp_int * a) -{ - int n; - mp_digit *tmp; - - a->sign = MP_ZPOS; - a->used = 0; - - tmp = a->dp; - for (n = 0; n < a->alloc; n++) { - *tmp++ = 0; - } -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_mp_zero.c */ - -/* Start: bn_prime_tab.c */ -#include <tommath.h> -#ifdef BN_PRIME_TAB_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ -const mp_digit ltm_prime_tab[] = { - 0x0002, 0x0003, 0x0005, 0x0007, 0x000B, 0x000D, 0x0011, 0x0013, - 0x0017, 0x001D, 0x001F, 0x0025, 0x0029, 0x002B, 0x002F, 0x0035, - 0x003B, 0x003D, 0x0043, 0x0047, 0x0049, 0x004F, 0x0053, 0x0059, - 0x0061, 0x0065, 0x0067, 0x006B, 0x006D, 0x0071, 0x007F, -#ifndef MP_8BIT - 0x0083, - 0x0089, 0x008B, 0x0095, 0x0097, 0x009D, 0x00A3, 0x00A7, 0x00AD, - 0x00B3, 0x00B5, 0x00BF, 0x00C1, 0x00C5, 0x00C7, 0x00D3, 0x00DF, - 0x00E3, 0x00E5, 0x00E9, 0x00EF, 0x00F1, 0x00FB, 0x0101, 0x0107, - 0x010D, 0x010F, 0x0115, 0x0119, 0x011B, 0x0125, 0x0133, 0x0137, - - 0x0139, 0x013D, 0x014B, 0x0151, 0x015B, 0x015D, 0x0161, 0x0167, - 0x016F, 0x0175, 0x017B, 0x017F, 0x0185, 0x018D, 0x0191, 0x0199, - 0x01A3, 0x01A5, 0x01AF, 0x01B1, 0x01B7, 0x01BB, 0x01C1, 0x01C9, - 0x01CD, 0x01CF, 0x01D3, 0x01DF, 0x01E7, 0x01EB, 0x01F3, 0x01F7, - 0x01FD, 0x0209, 0x020B, 0x021D, 0x0223, 0x022D, 0x0233, 0x0239, - 0x023B, 0x0241, 0x024B, 0x0251, 0x0257, 0x0259, 0x025F, 0x0265, - 0x0269, 0x026B, 0x0277, 0x0281, 0x0283, 0x0287, 0x028D, 0x0293, - 0x0295, 0x02A1, 0x02A5, 0x02AB, 0x02B3, 0x02BD, 0x02C5, 0x02CF, - - 0x02D7, 0x02DD, 0x02E3, 0x02E7, 0x02EF, 0x02F5, 0x02F9, 0x0301, - 0x0305, 0x0313, 0x031D, 0x0329, 0x032B, 0x0335, 0x0337, 0x033B, - 0x033D, 0x0347, 0x0355, 0x0359, 0x035B, 0x035F, 0x036D, 0x0371, - 0x0373, 0x0377, 0x038B, 0x038F, 0x0397, 0x03A1, 0x03A9, 0x03AD, - 0x03B3, 0x03B9, 0x03C7, 0x03CB, 0x03D1, 0x03D7, 0x03DF, 0x03E5, - 0x03F1, 0x03F5, 0x03FB, 0x03FD, 0x0407, 0x0409, 0x040F, 0x0419, - 0x041B, 0x0425, 0x0427, 0x042D, 0x043F, 0x0443, 0x0445, 0x0449, - 0x044F, 0x0455, 0x045D, 0x0463, 0x0469, 0x047F, 0x0481, 0x048B, - - 0x0493, 0x049D, 0x04A3, 0x04A9, 0x04B1, 0x04BD, 0x04C1, 0x04C7, - 0x04CD, 0x04CF, 0x04D5, 0x04E1, 0x04EB, 0x04FD, 0x04FF, 0x0503, - 0x0509, 0x050B, 0x0511, 0x0515, 0x0517, 0x051B, 0x0527, 0x0529, - 0x052F, 0x0551, 0x0557, 0x055D, 0x0565, 0x0577, 0x0581, 0x058F, - 0x0593, 0x0595, 0x0599, 0x059F, 0x05A7, 0x05AB, 0x05AD, 0x05B3, - 0x05BF, 0x05C9, 0x05CB, 0x05CF, 0x05D1, 0x05D5, 0x05DB, 0x05E7, - 0x05F3, 0x05FB, 0x0607, 0x060D, 0x0611, 0x0617, 0x061F, 0x0623, - 0x062B, 0x062F, 0x063D, 0x0641, 0x0647, 0x0649, 0x064D, 0x0653 -#endif -}; -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_prime_tab.c */ - -/* Start: bn_reverse.c */ -#include <tommath.h> -#ifdef BN_REVERSE_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* reverse an array, used for radix code */ -void -bn_reverse (unsigned char *s, int len) -{ - int ix, iy; - unsigned char t; - - ix = 0; - iy = len - 1; - while (ix < iy) { - t = s[ix]; - s[ix] = s[iy]; - s[iy] = t; - ++ix; - --iy; - } -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_reverse.c */ - -/* Start: bn_s_mp_add.c */ -#include <tommath.h> -#ifdef BN_S_MP_ADD_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* low level addition, based on HAC pp.594, Algorithm 14.7 */ -int -s_mp_add (mp_int * a, mp_int * b, mp_int * c) -{ - mp_int *x; - int olduse, res, min, max; - - /* find sizes, we let |a| <= |b| which means we have to sort - * them. "x" will point to the input with the most digits - */ - if (a->used > b->used) { - min = b->used; - max = a->used; - x = a; - } else { - min = a->used; - max = b->used; - x = b; - } - - /* init result */ - if (c->alloc < max + 1) { - if ((res = mp_grow (c, max + 1)) != MP_OKAY) { - return res; - } - } - - /* get old used digit count and set new one */ - olduse = c->used; - c->used = max + 1; - - { - register mp_digit u, *tmpa, *tmpb, *tmpc; - register int i; - - /* alias for digit pointers */ - - /* first input */ - tmpa = a->dp; - - /* second input */ - tmpb = b->dp; - - /* destination */ - tmpc = c->dp; - - /* zero the carry */ - u = 0; - for (i = 0; i < min; i++) { - /* Compute the sum at one digit, T[i] = A[i] + B[i] + U */ - *tmpc = *tmpa++ + *tmpb++ + u; - - /* U = carry bit of T[i] */ - u = *tmpc >> ((mp_digit)DIGIT_BIT); - - /* take away carry bit from T[i] */ - *tmpc++ &= MP_MASK; - } - - /* now copy higher words if any, that is in A+B - * if A or B has more digits add those in - */ - if (min != max) { - for (; i < max; i++) { - /* T[i] = X[i] + U */ - *tmpc = x->dp[i] + u; - - /* U = carry bit of T[i] */ - u = *tmpc >> ((mp_digit)DIGIT_BIT); - - /* take away carry bit from T[i] */ - *tmpc++ &= MP_MASK; - } - } - - /* add carry */ - *tmpc++ = u; - - /* clear digits above oldused */ - for (i = c->used; i < olduse; i++) { - *tmpc++ = 0; - } - } - - mp_clamp (c); - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_s_mp_add.c */ - -/* Start: bn_s_mp_exptmod.c */ -#include <tommath.h> -#ifdef BN_S_MP_EXPTMOD_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ -#ifdef MP_LOW_MEM - #define TAB_SIZE 32 -#else - #define TAB_SIZE 256 -#endif - -int s_mp_exptmod (mp_int * G, mp_int * X, mp_int * P, mp_int * Y, int redmode) -{ - mp_int M[TAB_SIZE], res, mu; - mp_digit buf; - int err, bitbuf, bitcpy, bitcnt, mode, digidx, x, y, winsize; - int (*redux)(mp_int*,mp_int*,mp_int*); - - /* find window size */ - x = mp_count_bits (X); - if (x <= 7) { - winsize = 2; - } else if (x <= 36) { - winsize = 3; - } else if (x <= 140) { - winsize = 4; - } else if (x <= 450) { - winsize = 5; - } else if (x <= 1303) { - winsize = 6; - } else if (x <= 3529) { - winsize = 7; - } else { - winsize = 8; - } - -#ifdef MP_LOW_MEM - if (winsize > 5) { - winsize = 5; - } -#endif - - /* init M array */ - /* init first cell */ - if ((err = mp_init(&M[1])) != MP_OKAY) { - return err; - } - - /* now init the second half of the array */ - for (x = 1<<(winsize-1); x < (1 << winsize); x++) { - if ((err = mp_init(&M[x])) != MP_OKAY) { - for (y = 1<<(winsize-1); y < x; y++) { - mp_clear (&M[y]); - } - mp_clear(&M[1]); - return err; - } - } - - /* create mu, used for Barrett reduction */ - if ((err = mp_init (&mu)) != MP_OKAY) { - goto LBL_M; - } - - if (redmode == 0) { - if ((err = mp_reduce_setup (&mu, P)) != MP_OKAY) { - goto LBL_MU; - } - redux = mp_reduce; - } else { - if ((err = mp_reduce_2k_setup_l (P, &mu)) != MP_OKAY) { - goto LBL_MU; - } - redux = mp_reduce_2k_l; - } - - /* create M table - * - * The M table contains powers of the base, - * e.g. M[x] = G**x mod P - * - * The first half of the table is not - * computed though accept for M[0] and M[1] - */ - if ((err = mp_mod (G, P, &M[1])) != MP_OKAY) { - goto LBL_MU; - } - - /* compute the value at M[1<<(winsize-1)] by squaring - * M[1] (winsize-1) times - */ - if ((err = mp_copy (&M[1], &M[1 << (winsize - 1)])) != MP_OKAY) { - goto LBL_MU; - } - - for (x = 0; x < (winsize - 1); x++) { - /* square it */ - if ((err = mp_sqr (&M[1 << (winsize - 1)], - &M[1 << (winsize - 1)])) != MP_OKAY) { - goto LBL_MU; - } - - /* reduce modulo P */ - if ((err = redux (&M[1 << (winsize - 1)], P, &mu)) != MP_OKAY) { - goto LBL_MU; - } - } - - /* create upper table, that is M[x] = M[x-1] * M[1] (mod P) - * for x = (2**(winsize - 1) + 1) to (2**winsize - 1) - */ - for (x = (1 << (winsize - 1)) + 1; x < (1 << winsize); x++) { - if ((err = mp_mul (&M[x - 1], &M[1], &M[x])) != MP_OKAY) { - goto LBL_MU; - } - if ((err = redux (&M[x], P, &mu)) != MP_OKAY) { - goto LBL_MU; - } - } - - /* setup result */ - if ((err = mp_init (&res)) != MP_OKAY) { - goto LBL_MU; - } - mp_set (&res, 1); - - /* set initial mode and bit cnt */ - mode = 0; - bitcnt = 1; - buf = 0; - digidx = X->used - 1; - bitcpy = 0; - bitbuf = 0; - - for (;;) { - /* grab next digit as required */ - if (--bitcnt == 0) { - /* if digidx == -1 we are out of digits */ - if (digidx == -1) { - break; - } - /* read next digit and reset the bitcnt */ - buf = X->dp[digidx--]; - bitcnt = (int) DIGIT_BIT; - } - - /* grab the next msb from the exponent */ - y = (buf >> (mp_digit)(DIGIT_BIT - 1)) & 1; - buf <<= (mp_digit)1; - - /* if the bit is zero and mode == 0 then we ignore it - * These represent the leading zero bits before the first 1 bit - * in the exponent. Technically this opt is not required but it - * does lower the # of trivial squaring/reductions used - */ - if (mode == 0 && y == 0) { - continue; - } - - /* if the bit is zero and mode == 1 then we square */ - if (mode == 1 && y == 0) { - if ((err = mp_sqr (&res, &res)) != MP_OKAY) { - goto LBL_RES; - } - if ((err = redux (&res, P, &mu)) != MP_OKAY) { - goto LBL_RES; - } - continue; - } - - /* else we add it to the window */ - bitbuf |= (y << (winsize - ++bitcpy)); - mode = 2; - - if (bitcpy == winsize) { - /* ok window is filled so square as required and multiply */ - /* square first */ - for (x = 0; x < winsize; x++) { - if ((err = mp_sqr (&res, &res)) != MP_OKAY) { - goto LBL_RES; - } - if ((err = redux (&res, P, &mu)) != MP_OKAY) { - goto LBL_RES; - } - } - - /* then multiply */ - if ((err = mp_mul (&res, &M[bitbuf], &res)) != MP_OKAY) { - goto LBL_RES; - } - if ((err = redux (&res, P, &mu)) != MP_OKAY) { - goto LBL_RES; - } - - /* empty window and reset */ - bitcpy = 0; - bitbuf = 0; - mode = 1; - } - } - - /* if bits remain then square/multiply */ - if (mode == 2 && bitcpy > 0) { - /* square then multiply if the bit is set */ - for (x = 0; x < bitcpy; x++) { - if ((err = mp_sqr (&res, &res)) != MP_OKAY) { - goto LBL_RES; - } - if ((err = redux (&res, P, &mu)) != MP_OKAY) { - goto LBL_RES; - } - - bitbuf <<= 1; - if ((bitbuf & (1 << winsize)) != 0) { - /* then multiply */ - if ((err = mp_mul (&res, &M[1], &res)) != MP_OKAY) { - goto LBL_RES; - } - if ((err = redux (&res, P, &mu)) != MP_OKAY) { - goto LBL_RES; - } - } - } - } - - mp_exch (&res, Y); - err = MP_OKAY; -LBL_RES:mp_clear (&res); -LBL_MU:mp_clear (&mu); -LBL_M: - mp_clear(&M[1]); - for (x = 1<<(winsize-1); x < (1 << winsize); x++) { - mp_clear (&M[x]); - } - return err; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_s_mp_exptmod.c */ - -/* Start: bn_s_mp_mul_digs.c */ -#include <tommath.h> -#ifdef BN_S_MP_MUL_DIGS_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* multiplies |a| * |b| and only computes upto digs digits of result - * HAC pp. 595, Algorithm 14.12 Modified so you can control how - * many digits of output are created. - */ -int s_mp_mul_digs (mp_int * a, mp_int * b, mp_int * c, int digs) -{ - mp_int t; - int res, pa, pb, ix, iy; - mp_digit u; - mp_word r; - mp_digit tmpx, *tmpt, *tmpy; - - /* can we use the fast multiplier? */ - if (((digs) < MP_WARRAY) && - MIN (a->used, b->used) < - (1 << ((CHAR_BIT * sizeof (mp_word)) - (2 * DIGIT_BIT)))) { - return fast_s_mp_mul_digs (a, b, c, digs); - } - - if ((res = mp_init_size (&t, digs)) != MP_OKAY) { - return res; - } - t.used = digs; - - /* compute the digits of the product directly */ - pa = a->used; - for (ix = 0; ix < pa; ix++) { - /* set the carry to zero */ - u = 0; - - /* limit ourselves to making digs digits of output */ - pb = MIN (b->used, digs - ix); - - /* setup some aliases */ - /* copy of the digit from a used within the nested loop */ - tmpx = a->dp[ix]; - - /* an alias for the destination shifted ix places */ - tmpt = t.dp + ix; - - /* an alias for the digits of b */ - tmpy = b->dp; - - /* compute the columns of the output and propagate the carry */ - for (iy = 0; iy < pb; iy++) { - /* compute the column as a mp_word */ - r = ((mp_word)*tmpt) + - ((mp_word)tmpx) * ((mp_word)*tmpy++) + - ((mp_word) u); - - /* the new column is the lower part of the result */ - *tmpt++ = (mp_digit) (r & ((mp_word) MP_MASK)); - - /* get the carry word from the result */ - u = (mp_digit) (r >> ((mp_word) DIGIT_BIT)); - } - /* set carry if it is placed below digs */ - if (ix + iy < digs) { - *tmpt = u; - } - } - - mp_clamp (&t); - mp_exch (&t, c); - - mp_clear (&t); - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_s_mp_mul_digs.c */ - -/* Start: bn_s_mp_mul_high_digs.c */ -#include <tommath.h> -#ifdef BN_S_MP_MUL_HIGH_DIGS_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* multiplies |a| * |b| and does not compute the lower digs digits - * [meant to get the higher part of the product] - */ -int -s_mp_mul_high_digs (mp_int * a, mp_int * b, mp_int * c, int digs) -{ - mp_int t; - int res, pa, pb, ix, iy; - mp_digit u; - mp_word r; - mp_digit tmpx, *tmpt, *tmpy; - - /* can we use the fast multiplier? */ -#ifdef BN_FAST_S_MP_MUL_HIGH_DIGS_C - if (((a->used + b->used + 1) < MP_WARRAY) - && MIN (a->used, b->used) < (1 << ((CHAR_BIT * sizeof (mp_word)) - (2 * DIGIT_BIT)))) { - return fast_s_mp_mul_high_digs (a, b, c, digs); - } -#endif - - if ((res = mp_init_size (&t, a->used + b->used + 1)) != MP_OKAY) { - return res; - } - t.used = a->used + b->used + 1; - - pa = a->used; - pb = b->used; - for (ix = 0; ix < pa; ix++) { - /* clear the carry */ - u = 0; - - /* left hand side of A[ix] * B[iy] */ - tmpx = a->dp[ix]; - - /* alias to the address of where the digits will be stored */ - tmpt = &(t.dp[digs]); - - /* alias for where to read the right hand side from */ - tmpy = b->dp + (digs - ix); - - for (iy = digs - ix; iy < pb; iy++) { - /* calculate the double precision result */ - r = ((mp_word)*tmpt) + - ((mp_word)tmpx) * ((mp_word)*tmpy++) + - ((mp_word) u); - - /* get the lower part */ - *tmpt++ = (mp_digit) (r & ((mp_word) MP_MASK)); - - /* carry the carry */ - u = (mp_digit) (r >> ((mp_word) DIGIT_BIT)); - } - *tmpt = u; - } - mp_clamp (&t); - mp_exch (&t, c); - mp_clear (&t); - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_s_mp_mul_high_digs.c */ - -/* Start: bn_s_mp_sqr.c */ -#include <tommath.h> -#ifdef BN_S_MP_SQR_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* low level squaring, b = a*a, HAC pp.596-597, Algorithm 14.16 */ -int s_mp_sqr (mp_int * a, mp_int * b) -{ - mp_int t; - int res, ix, iy, pa; - mp_word r; - mp_digit u, tmpx, *tmpt; - - pa = a->used; - if ((res = mp_init_size (&t, 2*pa + 1)) != MP_OKAY) { - return res; - } - - /* default used is maximum possible size */ - t.used = 2*pa + 1; - - for (ix = 0; ix < pa; ix++) { - /* first calculate the digit at 2*ix */ - /* calculate double precision result */ - r = ((mp_word) t.dp[2*ix]) + - ((mp_word)a->dp[ix])*((mp_word)a->dp[ix]); - - /* store lower part in result */ - t.dp[ix+ix] = (mp_digit) (r & ((mp_word) MP_MASK)); - - /* get the carry */ - u = (mp_digit)(r >> ((mp_word) DIGIT_BIT)); - - /* left hand side of A[ix] * A[iy] */ - tmpx = a->dp[ix]; - - /* alias for where to store the results */ - tmpt = t.dp + (2*ix + 1); - - for (iy = ix + 1; iy < pa; iy++) { - /* first calculate the product */ - r = ((mp_word)tmpx) * ((mp_word)a->dp[iy]); - - /* now calculate the double precision result, note we use - * addition instead of *2 since it's easier to optimize - */ - r = ((mp_word) *tmpt) + r + r + ((mp_word) u); - - /* store lower part */ - *tmpt++ = (mp_digit) (r & ((mp_word) MP_MASK)); - - /* get carry */ - u = (mp_digit)(r >> ((mp_word) DIGIT_BIT)); - } - /* propagate upwards */ - while (u != ((mp_digit) 0)) { - r = ((mp_word) *tmpt) + ((mp_word) u); - *tmpt++ = (mp_digit) (r & ((mp_word) MP_MASK)); - u = (mp_digit)(r >> ((mp_word) DIGIT_BIT)); - } - } - - mp_clamp (&t); - mp_exch (&t, b); - mp_clear (&t); - return MP_OKAY; -} -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_s_mp_sqr.c */ - -/* Start: bn_s_mp_sub.c */ -#include <tommath.h> -#ifdef BN_S_MP_SUB_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* low level subtraction (assumes |a| > |b|), HAC pp.595 Algorithm 14.9 */ -int -s_mp_sub (mp_int * a, mp_int * b, mp_int * c) -{ - int olduse, res, min, max; - - /* find sizes */ - min = b->used; - max = a->used; - - /* init result */ - if (c->alloc < max) { - if ((res = mp_grow (c, max)) != MP_OKAY) { - return res; - } - } - olduse = c->used; - c->used = max; - - { - register mp_digit u, *tmpa, *tmpb, *tmpc; - register int i; - - /* alias for digit pointers */ - tmpa = a->dp; - tmpb = b->dp; - tmpc = c->dp; - - /* set carry to zero */ - u = 0; - for (i = 0; i < min; i++) { - /* T[i] = A[i] - B[i] - U */ - *tmpc = *tmpa++ - *tmpb++ - u; - - /* U = carry bit of T[i] - * Note this saves performing an AND operation since - * if a carry does occur it will propagate all the way to the - * MSB. As a result a single shift is enough to get the carry - */ - u = *tmpc >> ((mp_digit)(CHAR_BIT * sizeof (mp_digit) - 1)); - - /* Clear carry from T[i] */ - *tmpc++ &= MP_MASK; - } - - /* now copy higher words if any, e.g. if A has more digits than B */ - for (; i < max; i++) { - /* T[i] = A[i] - U */ - *tmpc = *tmpa++ - u; - - /* U = carry bit of T[i] */ - u = *tmpc >> ((mp_digit)(CHAR_BIT * sizeof (mp_digit) - 1)); - - /* Clear carry from T[i] */ - *tmpc++ &= MP_MASK; - } - - /* clear digits above used (since we may not have grown result above) */ - for (i = c->used; i < olduse; i++) { - *tmpc++ = 0; - } - } - - mp_clamp (c); - return MP_OKAY; -} - -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bn_s_mp_sub.c */ - -/* Start: bncore.c */ -#include <tommath.h> -#ifdef BNCORE_C -/* LibTomMath, multiple-precision integer library -- Tom St Denis - * - * LibTomMath is a library that provides multiple-precision - * integer arithmetic as well as number theoretic functionality. - * - * The library was designed directly after the MPI library by - * Michael Fromberger but has been written from scratch with - * additional optimizations in place. - * - * The library is free for all purposes without any express - * guarantee it works. - * - * Tom St Denis, tomstdenis@gmail.com, http://libtom.org - */ - -/* Known optimal configurations - - CPU /Compiler /MUL CUTOFF/SQR CUTOFF -------------------------------------------------------------- - Intel P4 Northwood /GCC v3.4.1 / 88/ 128/LTM 0.32 ;-) - AMD Athlon64 /GCC v3.4.4 / 80/ 120/LTM 0.35 - -*/ - -int KARATSUBA_MUL_CUTOFF = 80, /* Min. number of digits before Karatsuba multiplication is used. */ - KARATSUBA_SQR_CUTOFF = 120, /* Min. number of digits before Karatsuba squaring is used. */ - - TOOM_MUL_CUTOFF = 350, /* no optimal values of these are known yet so set em high */ - TOOM_SQR_CUTOFF = 400; -#endif - -/* $Source$ */ -/* $Revision$ */ -/* $Date$ */ - -/* End: bncore.c */ - - -/* EOF */ diff --git a/libtommath/pretty.build b/libtommath/pretty.build deleted file mode 100644 index a708b8a..0000000 --- a/libtommath/pretty.build +++ /dev/null @@ -1,66 +0,0 @@ -#!/bin/perl -w -# -# Cute little builder for perl -# Total waste of development time... -# -# This will build all the object files and then the archive .a file -# requires GCC, GNU make and a sense of humour. -# -# Tom St Denis -use strict; - -my $count = 0; -my $starttime = time; -my $rate = 0; -print "Scanning for source files...\n"; -foreach my $filename (glob "*.c") { - ++$count; -} -print "Source files to build: $count\nBuilding...\n"; -my $i = 0; -my $lines = 0; -my $filesbuilt = 0; -foreach my $filename (glob "*.c") { - printf("Building %3.2f%%, ", (++$i/$count)*100.0); - if ($i % 4 == 0) { print "/, "; } - if ($i % 4 == 1) { print "-, "; } - if ($i % 4 == 2) { print "\\, "; } - if ($i % 4 == 3) { print "|, "; } - if ($rate > 0) { - my $tleft = ($count - $i) / $rate; - my $tsec = $tleft%60; - my $tmin = ($tleft/60)%60; - my $thour = ($tleft/3600)%60; - printf("%2d:%02d:%02d left, ", $thour, $tmin, $tsec); - } - my $cnt = ($i/$count)*30.0; - my $x = 0; - print "["; - for (; $x < $cnt; $x++) { print "#"; } - for (; $x < 30; $x++) { print " "; } - print "]\r"; - my $tmp = $filename; - $tmp =~ s/\.c/".o"/ge; - if (open(SRC, "<$tmp")) { - close SRC; - } else { - !system("make $tmp > /dev/null 2>/dev/null") or die "\nERROR: Failed to make $tmp!!!\n"; - open( SRC, "<$filename" ) or die "Couldn't open $filename for reading: $!"; - ++$lines while (<SRC>); - close SRC or die "Error closing $filename after reading: $!"; - ++$filesbuilt; - } - - # update timer - if (time != $starttime) { - my $delay = time - $starttime; - $rate = $i/$delay; - } -} - -# finish building the library -printf("\nFinished building source (%d seconds, %3.2f files per second).\n", time - $starttime, $rate); -print "Compiled approximately $filesbuilt files and $lines lines of code.\n"; -print "Doing final make (building archive...)\n"; -!system("make > /dev/null 2>/dev/null") or die "\nERROR: Failed to perform last make command!!!\n"; -print "done.\n";
\ No newline at end of file diff --git a/libtommath/testme.sh b/libtommath/testme.sh deleted file mode 100755 index 6324525..0000000 --- a/libtommath/testme.sh +++ /dev/null @@ -1,174 +0,0 @@ -#!/bin/bash -# -# return values of this script are: -# 0 success -# 128 a test failed -# >0 the number of timed-out tests - -set -e - -if [ -f /proc/cpuinfo ] -then - MAKE_JOBS=$(( ($(cat /proc/cpuinfo | grep -E '^processor[[:space:]]*:' | tail -n -1 | cut -d':' -f2) + 1) * 2 + 1 )) -else - MAKE_JOBS=8 -fi - -ret=0 -TEST_CFLAGS="" - -_help() -{ - echo "Usage options for $(basename $0) [--with-cc=arg [other options]]" - echo - echo "Executing this script without any parameter will only run the default configuration" - echo "that has automatically been determined for the architecture you're running." - echo - echo " --with-cc=* The compiler(s) to use for the tests" - echo " This is an option that will be iterated." - echo - echo "To be able to specify options a compiler has to be given." - echo "All options will be tested with all MP_xBIT configurations." - echo - echo " --with-{m64,m32,mx32} The architecture(s) to build and test for," - echo " e.g. --with-mx32." - echo " This is an option that will be iterated, multiple selections are possible." - echo " The mx32 architecture is not supported by clang and will not be executed." - echo - echo " --cflags=* Give an option to the compiler," - echo " e.g. --cflags=-g" - echo " This is an option that will always be passed as parameter to CC." - echo - echo " --make-option=* Give an option to make," - echo " e.g. --make-option=\"-f makefile.shared\"" - echo " This is an option that will always be passed as parameter to make." - echo - echo "Godmode:" - echo - echo " --all Choose all architectures and gcc and clang as compilers" - echo - echo " --help This message" - exit 0 -} - -_die() -{ - echo "error $2 while $1" - if [ "$2" != "124" ] - then - exit 128 - else - echo "assuming timeout while running test - continue" - ret=$(( $ret + 1 )) - fi -} - -_runtest() -{ - echo -ne " Compile $1 $2" - make clean > /dev/null - CC="$1" CFLAGS="$2 $TEST_CFLAGS" make -j$MAKE_JOBS test_standalone $MAKE_OPTIONS > /dev/null 2>test_errors.txt - echo -e "\rRun test $1 $2" - timeout --foreground 90 ./test > test_$(echo ${1}${2} | tr ' ' '_').txt || _die "running tests" $? -} - -_banner() -{ - echo "uname="$(uname -a) - [[ "$#" != "0" ]] && (echo $1=$($1 -dumpversion)) || true -} - -_exit() -{ - if [ "$ret" == "0" ] - then - echo "Tests successful" - else - echo "$ret tests timed out" - fi - - exit $ret -} - -ARCHFLAGS="" -COMPILERS="" -CFLAGS="" - -while [ $# -gt 0 ]; -do - case $1 in - "--with-m64" | "--with-m32" | "--with-mx32") - ARCHFLAGS="$ARCHFLAGS ${1:6}" - ;; - --with-cc=*) - COMPILERS="$COMPILERS ${1#*=}" - ;; - --cflags=*) - CFLAGS="$CFLAGS ${1#*=}" - ;; - --make-option=*) - MAKE_OPTIONS="$MAKE_OPTIONS ${1#*=}" - ;; - --all) - COMPILERS="gcc clang" - ARCHFLAGS="-m64 -m32 -mx32" - ;; - --help) - _help - ;; - esac - shift -done - -# default to gcc if nothing is given -if [[ "$COMPILERS" == "" ]] -then - _banner gcc - _runtest "gcc" "" - _exit -fi - -archflags=( $ARCHFLAGS ) -compilers=( $COMPILERS ) - -# choosing a compiler without specifying an architecture will use the default architecture -if [ "${#archflags[@]}" == "0" ] -then - archflags[0]=" " -fi - -_banner - -for i in "${compilers[@]}" -do - if [ -z "$(which $i)" ] - then - echo "Skipped compiler $i, file not found" - continue - fi - compiler_version=$(echo "$i="$($i -dumpversion)) - if [ "$compiler_version" == "clang=4.2.1" ] - then - # one of my versions of clang complains about some stuff in stdio.h and stdarg.h ... - TEST_CFLAGS="-Wno-typedef-redefinition" - else - TEST_CFLAGS="" - fi - echo $compiler_version - - for a in "${archflags[@]}" - do - if [[ $(expr "$i" : "clang") && "$a" == "-mx32" ]] - then - echo "clang -mx32 tests skipped" - continue - fi - - _runtest "$i $a" "" - _runtest "$i $a" "-DMP_8BIT" - _runtest "$i $a" "-DMP_16BIT" - _runtest "$i $a" "-DMP_32BIT" - done -done - -_exit diff --git a/libtommath/tombc/grammar.txt b/libtommath/tombc/grammar.txt deleted file mode 100644 index a780e75..0000000 --- a/libtommath/tombc/grammar.txt +++ /dev/null @@ -1,35 +0,0 @@ -program := program statement | statement | empty -statement := { statement } | - identifier = numexpression; | - identifier[numexpression] = numexpression; | - function(expressionlist); | - for (identifer = numexpression; numexpression; identifier = numexpression) { statement } | - while (numexpression) { statement } | - if (numexpresion) { statement } elif | - break; | - continue; - -elif := else statement | empty -function := abs | countbits | exptmod | jacobi | print | isprime | nextprime | issquare | readinteger | exit -expressionlist := expressionlist, expression | expression - -// LR(1) !!!? -expression := string | numexpression -numexpression := cmpexpr && cmpexpr | cmpexpr \|\| cmpexpr | cmpexpr -cmpexpr := boolexpr < boolexpr | boolexpr > boolexpr | boolexpr == boolexpr | - boolexpr <= boolexpr | boolexpr >= boolexpr | boolexpr -boolexpr := shiftexpr & shiftexpr | shiftexpr ^ shiftexpr | shiftexpr \| shiftexpr | shiftexpr -shiftexpr := addsubexpr << addsubexpr | addsubexpr >> addsubexpr | addsubexpr -addsubexpr := mulexpr + mulexpr | mulexpr - mulexpr | mulexpr -mulexpr := expr * expr | expr / expr | expr % expr | expr -expr := -nexpr | nexpr -nexpr := integer | identifier | ( numexpression ) | identifier[numexpression] - -identifier := identifer digits | identifier alpha | alpha -alpha := a ... z | A ... Z -integer := hexnumber | digits -hexnumber := 0xhexdigits -hexdigits := hexdigits hexdigit | hexdigit -hexdigit := 0 ... 9 | a ... f | A ... F -digits := digits digit | digit -digit := 0 ... 9 diff --git a/libtommath/tommath.h b/libtommath/tommath.h index 4547488..fc6b409 100644 --- a/libtommath/tommath.h +++ b/libtommath/tommath.h @@ -203,7 +203,7 @@ int mp_init_size(mp_int *a, int size); /* ---> Basic Manipulations <--- */ #define mp_iszero(a) (((a)->used == 0) ? MP_YES : MP_NO) -#define mp_iseven(a) ((((a)->used > 0) && (((a)->dp[0] & 1u) == 0u)) ? MP_YES : MP_NO) +#define mp_iseven(a) ((((a)->used == 0) || (((a)->dp[0] & 1u) == 0u)) ? MP_YES : MP_NO) #define mp_isodd(a) ((((a)->used > 0) && (((a)->dp[0] & 1u) == 1u)) ? MP_YES : MP_NO) #define mp_isneg(a) (((a)->sign != MP_ZPOS) ? MP_YES : MP_NO) diff --git a/libtommath/tommath.out b/libtommath/tommath.out deleted file mode 100644 index de4aada..0000000 --- a/libtommath/tommath.out +++ /dev/null @@ -1,139 +0,0 @@ -\BOOKMARK [0][-]{chapter.1}{Introduction}{}% 1 -\BOOKMARK [1][-]{section.1.1}{Multiple Precision Arithmetic}{chapter.1}% 2 -\BOOKMARK [2][-]{subsection.1.1.1}{What is Multiple Precision Arithmetic?}{section.1.1}% 3 -\BOOKMARK [2][-]{subsection.1.1.2}{The Need for Multiple Precision Arithmetic}{section.1.1}% 4 -\BOOKMARK [2][-]{subsection.1.1.3}{Benefits of Multiple Precision Arithmetic}{section.1.1}% 5 -\BOOKMARK [1][-]{section.1.2}{Purpose of This Text}{chapter.1}% 6 -\BOOKMARK [1][-]{section.1.3}{Discussion and Notation}{chapter.1}% 7 -\BOOKMARK [2][-]{subsection.1.3.1}{Notation}{section.1.3}% 8 -\BOOKMARK [2][-]{subsection.1.3.2}{Precision Notation}{section.1.3}% 9 -\BOOKMARK [2][-]{subsection.1.3.3}{Algorithm Inputs and Outputs}{section.1.3}% 10 -\BOOKMARK [2][-]{subsection.1.3.4}{Mathematical Expressions}{section.1.3}% 11 -\BOOKMARK [2][-]{subsection.1.3.5}{Work Effort}{section.1.3}% 12 -\BOOKMARK [1][-]{section.1.4}{Exercises}{chapter.1}% 13 -\BOOKMARK [1][-]{section.1.5}{Introduction to LibTomMath}{chapter.1}% 14 -\BOOKMARK [2][-]{subsection.1.5.1}{What is LibTomMath?}{section.1.5}% 15 -\BOOKMARK [2][-]{subsection.1.5.2}{Goals of LibTomMath}{section.1.5}% 16 -\BOOKMARK [1][-]{section.1.6}{Choice of LibTomMath}{chapter.1}% 17 -\BOOKMARK [2][-]{subsection.1.6.1}{Code Base}{section.1.6}% 18 -\BOOKMARK [2][-]{subsection.1.6.2}{API Simplicity}{section.1.6}% 19 -\BOOKMARK [2][-]{subsection.1.6.3}{Optimizations}{section.1.6}% 20 -\BOOKMARK [2][-]{subsection.1.6.4}{Portability and Stability}{section.1.6}% 21 -\BOOKMARK [2][-]{subsection.1.6.5}{Choice}{section.1.6}% 22 -\BOOKMARK [0][-]{chapter.2}{Getting Started}{}% 23 -\BOOKMARK [1][-]{section.2.1}{Library Basics}{chapter.2}% 24 -\BOOKMARK [1][-]{section.2.2}{What is a Multiple Precision Integer?}{chapter.2}% 25 -\BOOKMARK [2][-]{subsection.2.2.1}{The mp\137int Structure}{section.2.2}% 26 -\BOOKMARK [1][-]{section.2.3}{Argument Passing}{chapter.2}% 27 -\BOOKMARK [1][-]{section.2.4}{Return Values}{chapter.2}% 28 -\BOOKMARK [1][-]{section.2.5}{Initialization and Clearing}{chapter.2}% 29 -\BOOKMARK [2][-]{subsection.2.5.1}{Initializing an mp\137int}{section.2.5}% 30 -\BOOKMARK [2][-]{subsection.2.5.2}{Clearing an mp\137int}{section.2.5}% 31 -\BOOKMARK [1][-]{section.2.6}{Maintenance Algorithms}{chapter.2}% 32 -\BOOKMARK [2][-]{subsection.2.6.1}{Augmenting an mp\137int's Precision}{section.2.6}% 33 -\BOOKMARK [2][-]{subsection.2.6.2}{Initializing Variable Precision mp\137ints}{section.2.6}% 34 -\BOOKMARK [2][-]{subsection.2.6.3}{Multiple Integer Initializations and Clearings}{section.2.6}% 35 -\BOOKMARK [2][-]{subsection.2.6.4}{Clamping Excess Digits}{section.2.6}% 36 -\BOOKMARK [0][-]{chapter.3}{Basic Operations}{}% 37 -\BOOKMARK [1][-]{section.3.1}{Introduction}{chapter.3}% 38 -\BOOKMARK [1][-]{section.3.2}{Assigning Values to mp\137int Structures}{chapter.3}% 39 -\BOOKMARK [2][-]{subsection.3.2.1}{Copying an mp\137int}{section.3.2}% 40 -\BOOKMARK [2][-]{subsection.3.2.2}{Creating a Clone}{section.3.2}% 41 -\BOOKMARK [1][-]{section.3.3}{Zeroing an Integer}{chapter.3}% 42 -\BOOKMARK [1][-]{section.3.4}{Sign Manipulation}{chapter.3}% 43 -\BOOKMARK [2][-]{subsection.3.4.1}{Absolute Value}{section.3.4}% 44 -\BOOKMARK [2][-]{subsection.3.4.2}{Integer Negation}{section.3.4}% 45 -\BOOKMARK [1][-]{section.3.5}{Small Constants}{chapter.3}% 46 -\BOOKMARK [2][-]{subsection.3.5.1}{Setting Small Constants}{section.3.5}% 47 -\BOOKMARK [2][-]{subsection.3.5.2}{Setting Large Constants}{section.3.5}% 48 -\BOOKMARK [1][-]{section.3.6}{Comparisons}{chapter.3}% 49 -\BOOKMARK [2][-]{subsection.3.6.1}{Unsigned Comparisions}{section.3.6}% 50 -\BOOKMARK [2][-]{subsection.3.6.2}{Signed Comparisons}{section.3.6}% 51 -\BOOKMARK [0][-]{chapter.4}{Basic Arithmetic}{}% 52 -\BOOKMARK [1][-]{section.4.1}{Introduction}{chapter.4}% 53 -\BOOKMARK [1][-]{section.4.2}{Addition and Subtraction}{chapter.4}% 54 -\BOOKMARK [2][-]{subsection.4.2.1}{Low Level Addition}{section.4.2}% 55 -\BOOKMARK [2][-]{subsection.4.2.2}{Low Level Subtraction}{section.4.2}% 56 -\BOOKMARK [2][-]{subsection.4.2.3}{High Level Addition}{section.4.2}% 57 -\BOOKMARK [2][-]{subsection.4.2.4}{High Level Subtraction}{section.4.2}% 58 -\BOOKMARK [1][-]{section.4.3}{Bit and Digit Shifting}{chapter.4}% 59 -\BOOKMARK [2][-]{subsection.4.3.1}{Multiplication by Two}{section.4.3}% 60 -\BOOKMARK [2][-]{subsection.4.3.2}{Division by Two}{section.4.3}% 61 -\BOOKMARK [1][-]{section.4.4}{Polynomial Basis Operations}{chapter.4}% 62 -\BOOKMARK [2][-]{subsection.4.4.1}{Multiplication by x}{section.4.4}% 63 -\BOOKMARK [2][-]{subsection.4.4.2}{Division by x}{section.4.4}% 64 -\BOOKMARK [1][-]{section.4.5}{Powers of Two}{chapter.4}% 65 -\BOOKMARK [2][-]{subsection.4.5.1}{Multiplication by Power of Two}{section.4.5}% 66 -\BOOKMARK [2][-]{subsection.4.5.2}{Division by Power of Two}{section.4.5}% 67 -\BOOKMARK [2][-]{subsection.4.5.3}{Remainder of Division by Power of Two}{section.4.5}% 68 -\BOOKMARK [0][-]{chapter.5}{Multiplication and Squaring}{}% 69 -\BOOKMARK [1][-]{section.5.1}{The Multipliers}{chapter.5}% 70 -\BOOKMARK [1][-]{section.5.2}{Multiplication}{chapter.5}% 71 -\BOOKMARK [2][-]{subsection.5.2.1}{The Baseline Multiplication}{section.5.2}% 72 -\BOOKMARK [2][-]{subsection.5.2.2}{Faster Multiplication by the ``Comba'' Method}{section.5.2}% 73 -\BOOKMARK [2][-]{subsection.5.2.3}{Polynomial Basis Multiplication}{section.5.2}% 74 -\BOOKMARK [2][-]{subsection.5.2.4}{Karatsuba Multiplication}{section.5.2}% 75 -\BOOKMARK [2][-]{subsection.5.2.5}{Toom-Cook 3-Way Multiplication}{section.5.2}% 76 -\BOOKMARK [2][-]{subsection.5.2.6}{Signed Multiplication}{section.5.2}% 77 -\BOOKMARK [1][-]{section.5.3}{Squaring}{chapter.5}% 78 -\BOOKMARK [2][-]{subsection.5.3.1}{The Baseline Squaring Algorithm}{section.5.3}% 79 -\BOOKMARK [2][-]{subsection.5.3.2}{Faster Squaring by the ``Comba'' Method}{section.5.3}% 80 -\BOOKMARK [2][-]{subsection.5.3.3}{Polynomial Basis Squaring}{section.5.3}% 81 -\BOOKMARK [2][-]{subsection.5.3.4}{Karatsuba Squaring}{section.5.3}% 82 -\BOOKMARK [2][-]{subsection.5.3.5}{Toom-Cook Squaring}{section.5.3}% 83 -\BOOKMARK [2][-]{subsection.5.3.6}{High Level Squaring}{section.5.3}% 84 -\BOOKMARK [0][-]{chapter.6}{Modular Reduction}{}% 85 -\BOOKMARK [1][-]{section.6.1}{Basics of Modular Reduction}{chapter.6}% 86 -\BOOKMARK [1][-]{section.6.2}{The Barrett Reduction}{chapter.6}% 87 -\BOOKMARK [2][-]{subsection.6.2.1}{Fixed Point Arithmetic}{section.6.2}% 88 -\BOOKMARK [2][-]{subsection.6.2.2}{Choosing a Radix Point}{section.6.2}% 89 -\BOOKMARK [2][-]{subsection.6.2.3}{Trimming the Quotient}{section.6.2}% 90 -\BOOKMARK [2][-]{subsection.6.2.4}{Trimming the Residue}{section.6.2}% 91 -\BOOKMARK [2][-]{subsection.6.2.5}{The Barrett Algorithm}{section.6.2}% 92 -\BOOKMARK [2][-]{subsection.6.2.6}{The Barrett Setup Algorithm}{section.6.2}% 93 -\BOOKMARK [1][-]{section.6.3}{The Montgomery Reduction}{chapter.6}% 94 -\BOOKMARK [2][-]{subsection.6.3.1}{Digit Based Montgomery Reduction}{section.6.3}% 95 -\BOOKMARK [2][-]{subsection.6.3.2}{Baseline Montgomery Reduction}{section.6.3}% 96 -\BOOKMARK [2][-]{subsection.6.3.3}{Faster ``Comba'' Montgomery Reduction}{section.6.3}% 97 -\BOOKMARK [2][-]{subsection.6.3.4}{Montgomery Setup}{section.6.3}% 98 -\BOOKMARK [1][-]{section.6.4}{The Diminished Radix Algorithm}{chapter.6}% 99 -\BOOKMARK [2][-]{subsection.6.4.1}{Choice of Moduli}{section.6.4}% 100 -\BOOKMARK [2][-]{subsection.6.4.2}{Choice of k}{section.6.4}% 101 -\BOOKMARK [2][-]{subsection.6.4.3}{Restricted Diminished Radix Reduction}{section.6.4}% 102 -\BOOKMARK [2][-]{subsection.6.4.4}{Unrestricted Diminished Radix Reduction}{section.6.4}% 103 -\BOOKMARK [1][-]{section.6.5}{Algorithm Comparison}{chapter.6}% 104 -\BOOKMARK [0][-]{chapter.7}{Exponentiation}{}% 105 -\BOOKMARK [1][-]{section.7.1}{Exponentiation Basics}{chapter.7}% 106 -\BOOKMARK [2][-]{subsection.7.1.1}{Single Digit Exponentiation}{section.7.1}% 107 -\BOOKMARK [1][-]{section.7.2}{k-ary Exponentiation}{chapter.7}% 108 -\BOOKMARK [2][-]{subsection.7.2.1}{Optimal Values of k}{section.7.2}% 109 -\BOOKMARK [2][-]{subsection.7.2.2}{Sliding-Window Exponentiation}{section.7.2}% 110 -\BOOKMARK [1][-]{section.7.3}{Modular Exponentiation}{chapter.7}% 111 -\BOOKMARK [2][-]{subsection.7.3.1}{Barrett Modular Exponentiation}{section.7.3}% 112 -\BOOKMARK [1][-]{section.7.4}{Quick Power of Two}{chapter.7}% 113 -\BOOKMARK [0][-]{chapter.8}{Higher Level Algorithms}{}% 114 -\BOOKMARK [1][-]{section.8.1}{Integer Division with Remainder}{chapter.8}% 115 -\BOOKMARK [2][-]{subsection.8.1.1}{Quotient Estimation}{section.8.1}% 116 -\BOOKMARK [2][-]{subsection.8.1.2}{Normalized Integers}{section.8.1}% 117 -\BOOKMARK [2][-]{subsection.8.1.3}{Radix- Division with Remainder}{section.8.1}% 118 -\BOOKMARK [1][-]{section.8.2}{Single Digit Helpers}{chapter.8}% 119 -\BOOKMARK [2][-]{subsection.8.2.1}{Single Digit Addition and Subtraction}{section.8.2}% 120 -\BOOKMARK [2][-]{subsection.8.2.2}{Single Digit Multiplication}{section.8.2}% 121 -\BOOKMARK [2][-]{subsection.8.2.3}{Single Digit Division}{section.8.2}% 122 -\BOOKMARK [2][-]{subsection.8.2.4}{Single Digit Root Extraction}{section.8.2}% 123 -\BOOKMARK [1][-]{section.8.3}{Random Number Generation}{chapter.8}% 124 -\BOOKMARK [1][-]{section.8.4}{Formatted Representations}{chapter.8}% 125 -\BOOKMARK [2][-]{subsection.8.4.1}{Reading Radix-n Input}{section.8.4}% 126 -\BOOKMARK [2][-]{subsection.8.4.2}{Generating Radix-n Output}{section.8.4}% 127 -\BOOKMARK [0][-]{chapter.9}{Number Theoretic Algorithms}{}% 128 -\BOOKMARK [1][-]{section.9.1}{Greatest Common Divisor}{chapter.9}% 129 -\BOOKMARK [2][-]{subsection.9.1.1}{Complete Greatest Common Divisor}{section.9.1}% 130 -\BOOKMARK [1][-]{section.9.2}{Least Common Multiple}{chapter.9}% 131 -\BOOKMARK [1][-]{section.9.3}{Jacobi Symbol Computation}{chapter.9}% 132 -\BOOKMARK [2][-]{subsection.9.3.1}{Jacobi Symbol}{section.9.3}% 133 -\BOOKMARK [1][-]{section.9.4}{Modular Inverse}{chapter.9}% 134 -\BOOKMARK [2][-]{subsection.9.4.1}{General Case}{section.9.4}% 135 -\BOOKMARK [1][-]{section.9.5}{Primality Tests}{chapter.9}% 136 -\BOOKMARK [2][-]{subsection.9.5.1}{Trial Division}{section.9.5}% 137 -\BOOKMARK [2][-]{subsection.9.5.2}{The Fermat Test}{section.9.5}% 138 -\BOOKMARK [2][-]{subsection.9.5.3}{The Miller-Rabin Test}{section.9.5}% 139 diff --git a/libtommath/tommath.pdf b/libtommath/tommath.pdf Binary files differdeleted file mode 100644 index 6a6787e..0000000 --- a/libtommath/tommath.pdf +++ /dev/null diff --git a/libtommath/tommath.src b/libtommath/tommath.src deleted file mode 100644 index 768ed10..0000000 --- a/libtommath/tommath.src +++ /dev/null @@ -1,6339 +0,0 @@ -\documentclass[b5paper]{book} -\usepackage{hyperref} -\usepackage{makeidx} -\usepackage{amssymb} -\usepackage{color} -\usepackage{alltt} -\usepackage{graphicx} -\usepackage{layout} -\def\union{\cup} -\def\intersect{\cap} -\def\getsrandom{\stackrel{\rm R}{\gets}} -\def\cross{\times} -\def\cat{\hspace{0.5em} \| \hspace{0.5em}} -\def\catn{$\|$} -\def\divides{\hspace{0.3em} | \hspace{0.3em}} -\def\nequiv{\not\equiv} -\def\approx{\raisebox{0.2ex}{\mbox{\small $\sim$}}} -\def\lcm{{\rm lcm}} -\def\gcd{{\rm gcd}} -\def\log{{\rm log}} -\def\ord{{\rm ord}} -\def\abs{{\mathit abs}} -\def\rep{{\mathit rep}} -\def\mod{{\mathit\ mod\ }} -\renewcommand{\pmod}[1]{\ ({\rm mod\ }{#1})} -\newcommand{\floor}[1]{\left\lfloor{#1}\right\rfloor} -\newcommand{\ceil}[1]{\left\lceil{#1}\right\rceil} -\def\Or{{\rm\ or\ }} -\def\And{{\rm\ and\ }} -\def\iff{\hspace{1em}\Longleftrightarrow\hspace{1em}} -\def\implies{\Rightarrow} -\def\undefined{{\rm ``undefined"}} -\def\Proof{\vspace{1ex}\noindent {\bf Proof:}\hspace{1em}} -\let\oldphi\phi -\def\phi{\varphi} -\def\Pr{{\rm Pr}} -\newcommand{\str}[1]{{\mathbf{#1}}} -\def\F{{\mathbb F}} -\def\N{{\mathbb N}} -\def\Z{{\mathbb Z}} -\def\R{{\mathbb R}} -\def\C{{\mathbb C}} -\def\Q{{\mathbb Q}} -\definecolor{DGray}{gray}{0.5} -\newcommand{\emailaddr}[1]{\mbox{$<${#1}$>$}} -\def\twiddle{\raisebox{0.3ex}{\mbox{\tiny $\sim$}}} -\def\gap{\vspace{0.5ex}} -\makeindex -\begin{document} -\frontmatter -\pagestyle{empty} -\title{Multi--Precision Math} -\author{\mbox{ -%\begin{small} -\begin{tabular}{c} -Tom St Denis \\ -Algonquin College \\ -\\ -Mads Rasmussen \\ -Open Communications Security \\ -\\ -Greg Rose \\ -QUALCOMM Australia \\ -\end{tabular} -%\end{small} -} -} -\maketitle -This text has been placed in the public domain. This text corresponds to the v0.39 release of the -LibTomMath project. - -This text is formatted to the international B5 paper size of 176mm wide by 250mm tall using the \LaTeX{} -{\em book} macro package and the Perl {\em booker} package. - -\tableofcontents -\listoffigures -\chapter*{Prefaces} -When I tell people about my LibTom projects and that I release them as public domain they are often puzzled. -They ask why I did it and especially why I continue to work on them for free. The best I can explain it is ``Because I can.'' -Which seems odd and perhaps too terse for adult conversation. I often qualify it with ``I am able, I am willing.'' which -perhaps explains it better. I am the first to admit there is not anything that special with what I have done. Perhaps -others can see that too and then we would have a society to be proud of. My LibTom projects are what I am doing to give -back to society in the form of tools and knowledge that can help others in their endeavours. - -I started writing this book because it was the most logical task to further my goal of open academia. The LibTomMath source -code itself was written to be easy to follow and learn from. There are times, however, where pure C source code does not -explain the algorithms properly. Hence this book. The book literally starts with the foundation of the library and works -itself outwards to the more complicated algorithms. The use of both pseudo--code and verbatim source code provides a duality -of ``theory'' and ``practice'' that the computer science students of the world shall appreciate. I never deviate too far -from relatively straightforward algebra and I hope that this book can be a valuable learning asset. - -This book and indeed much of the LibTom projects would not exist in their current form if it was not for a plethora -of kind people donating their time, resources and kind words to help support my work. Writing a text of significant -length (along with the source code) is a tiresome and lengthy process. Currently the LibTom project is four years old, -comprises of literally thousands of users and over 100,000 lines of source code, TeX and other material. People like Mads and Greg -were there at the beginning to encourage me to work well. It is amazing how timely validation from others can boost morale to -continue the project. Definitely my parents were there for me by providing room and board during the many months of work in 2003. - -To my many friends whom I have met through the years I thank you for the good times and the words of encouragement. I hope I -honour your kind gestures with this project. - -Open Source. Open Academia. Open Minds. - -\begin{flushright} Tom St Denis \end{flushright} - -\newpage -I found the opportunity to work with Tom appealing for several reasons, not only could I broaden my own horizons, but also -contribute to educate others facing the problem of having to handle big number mathematical calculations. - -This book is Tom's child and he has been caring and fostering the project ever since the beginning with a clear mind of -how he wanted the project to turn out. I have helped by proofreading the text and we have had several discussions about -the layout and language used. - -I hold a masters degree in cryptography from the University of Southern Denmark and have always been interested in the -practical aspects of cryptography. - -Having worked in the security consultancy business for several years in S\~{a}o Paulo, Brazil, I have been in touch with a -great deal of work in which multiple precision mathematics was needed. Understanding the possibilities for speeding up -multiple precision calculations is often very important since we deal with outdated machine architecture where modular -reductions, for example, become painfully slow. - -This text is for people who stop and wonder when first examining algorithms such as RSA for the first time and asks -themselves, ``You tell me this is only secure for large numbers, fine; but how do you implement these numbers?'' - -\begin{flushright} -Mads Rasmussen - -S\~{a}o Paulo - SP - -Brazil -\end{flushright} - -\newpage -It's all because I broke my leg. That just happened to be at about the same time that Tom asked for someone to review the section of the book about -Karatsuba multiplication. I was laid up, alone and immobile, and thought ``Why not?'' I vaguely knew what Karatsuba multiplication was, but not -really, so I thought I could help, learn, and stop myself from watching daytime cable TV, all at once. - -At the time of writing this, I've still not met Tom or Mads in meatspace. I've been following Tom's progress since his first splash on the -sci.crypt Usenet news group. I watched him go from a clueless newbie, to the cryptographic equivalent of a reformed smoker, to a real -contributor to the field, over a period of about two years. I've been impressed with his obvious intelligence, and astounded by his productivity. -Of course, he's young enough to be my own child, so he doesn't have my problems with staying awake. - -When I reviewed that single section of the book, in its very earliest form, I was very pleasantly surprised. So I decided to collaborate more fully, -and at least review all of it, and perhaps write some bits too. There's still a long way to go with it, and I have watched a number of close -friends go through the mill of publication, so I think that the way to go is longer than Tom thinks it is. Nevertheless, it's a good effort, -and I'm pleased to be involved with it. - -\begin{flushright} -Greg Rose, Sydney, Australia, June 2003. -\end{flushright} - -\mainmatter -\pagestyle{headings} -\chapter{Introduction} -\section{Multiple Precision Arithmetic} - -\subsection{What is Multiple Precision Arithmetic?} -When we think of long-hand arithmetic such as addition or multiplication we rarely consider the fact that we instinctively -raise or lower the precision of the numbers we are dealing with. For example, in decimal we almost immediate can -reason that $7$ times $6$ is $42$. However, $42$ has two digits of precision as opposed to one digit we started with. -Further multiplications of say $3$ result in a larger precision result $126$. In these few examples we have multiple -precisions for the numbers we are working with. Despite the various levels of precision a single subset\footnote{With the occasional optimization.} - of algorithms can be designed to accomodate them. - -By way of comparison a fixed or single precision operation would lose precision on various operations. For example, in -the decimal system with fixed precision $6 \cdot 7 = 2$. - -Essentially at the heart of computer based multiple precision arithmetic are the same long-hand algorithms taught in -schools to manually add, subtract, multiply and divide. - -\subsection{The Need for Multiple Precision Arithmetic} -The most prevalent need for multiple precision arithmetic, often referred to as ``bignum'' math, is within the implementation -of public-key cryptography algorithms. Algorithms such as RSA \cite{RSAREF} and Diffie-Hellman \cite{DHREF} require -integers of significant magnitude to resist known cryptanalytic attacks. For example, at the time of this writing a -typical RSA modulus would be at least greater than $10^{309}$. However, modern programming languages such as ISO C \cite{ISOC} and -Java \cite{JAVA} only provide instrinsic support for integers which are relatively small and single precision. - -\begin{figure}[!here] -\begin{center} -\begin{tabular}{|r|c|} -\hline \textbf{Data Type} & \textbf{Range} \\ -\hline char & $-128 \ldots 127$ \\ -\hline short & $-32768 \ldots 32767$ \\ -\hline long & $-2147483648 \ldots 2147483647$ \\ -\hline long long & $-9223372036854775808 \ldots 9223372036854775807$ \\ -\hline -\end{tabular} -\end{center} -\caption{Typical Data Types for the C Programming Language} -\label{fig:ISOC} -\end{figure} - -The largest data type guaranteed to be provided by the ISO C programming -language\footnote{As per the ISO C standard. However, each compiler vendor is allowed to augment the precision as they -see fit.} can only represent values up to $10^{19}$ as shown in figure \ref{fig:ISOC}. On its own the C language is -insufficient to accomodate the magnitude required for the problem at hand. An RSA modulus of magnitude $10^{19}$ could be -trivially factored\footnote{A Pollard-Rho factoring would take only $2^{16}$ time.} on the average desktop computer, -rendering any protocol based on the algorithm insecure. Multiple precision algorithms solve this very problem by -extending the range of representable integers while using single precision data types. - -Most advancements in fast multiple precision arithmetic stem from the need for faster and more efficient cryptographic -primitives. Faster modular reduction and exponentiation algorithms such as Barrett's algorithm, which have appeared in -various cryptographic journals, can render algorithms such as RSA and Diffie-Hellman more efficient. In fact, several -major companies such as RSA Security, Certicom and Entrust have built entire product lines on the implementation and -deployment of efficient algorithms. - -However, cryptography is not the only field of study that can benefit from fast multiple precision integer routines. -Another auxiliary use of multiple precision integers is high precision floating point data types. -The basic IEEE \cite{IEEE} standard floating point type is made up of an integer mantissa $q$, an exponent $e$ and a sign bit $s$. -Numbers are given in the form $n = q \cdot b^e \cdot -1^s$ where $b = 2$ is the most common base for IEEE. Since IEEE -floating point is meant to be implemented in hardware the precision of the mantissa is often fairly small -(\textit{23, 48 and 64 bits}). The mantissa is merely an integer and a multiple precision integer could be used to create -a mantissa of much larger precision than hardware alone can efficiently support. This approach could be useful where -scientific applications must minimize the total output error over long calculations. - -Yet another use for large integers is within arithmetic on polynomials of large characteristic (i.e. $GF(p)[x]$ for large $p$). -In fact the library discussed within this text has already been used to form a polynomial basis library\footnote{See \url{http://poly.libtomcrypt.org} for more details.}. - -\subsection{Benefits of Multiple Precision Arithmetic} -\index{precision} -The benefit of multiple precision representations over single or fixed precision representations is that -no precision is lost while representing the result of an operation which requires excess precision. For example, -the product of two $n$-bit integers requires at least $2n$ bits of precision to be represented faithfully. A multiple -precision algorithm would augment the precision of the destination to accomodate the result while a single precision system -would truncate excess bits to maintain a fixed level of precision. - -It is possible to implement algorithms which require large integers with fixed precision algorithms. For example, elliptic -curve cryptography (\textit{ECC}) is often implemented on smartcards by fixing the precision of the integers to the maximum -size the system will ever need. Such an approach can lead to vastly simpler algorithms which can accomodate the -integers required even if the host platform cannot natively accomodate them\footnote{For example, the average smartcard -processor has an 8 bit accumulator.}. However, as efficient as such an approach may be, the resulting source code is not -normally very flexible. It cannot, at runtime, accomodate inputs of higher magnitude than the designer anticipated. - -Multiple precision algorithms have the most overhead of any style of arithmetic. For the the most part the -overhead can be kept to a minimum with careful planning, but overall, it is not well suited for most memory starved -platforms. However, multiple precision algorithms do offer the most flexibility in terms of the magnitude of the -inputs. That is, the same algorithms based on multiple precision integers can accomodate any reasonable size input -without the designer's explicit forethought. This leads to lower cost of ownership for the code as it only has to -be written and tested once. - -\section{Purpose of This Text} -The purpose of this text is to instruct the reader regarding how to implement efficient multiple precision algorithms. -That is to not only explain a limited subset of the core theory behind the algorithms but also the various ``house keeping'' -elements that are neglected by authors of other texts on the subject. Several well reknowned texts \cite{TAOCPV2,HAC} -give considerably detailed explanations of the theoretical aspects of algorithms and often very little information -regarding the practical implementation aspects. - -In most cases how an algorithm is explained and how it is actually implemented are two very different concepts. For -example, the Handbook of Applied Cryptography (\textit{HAC}), algorithm 14.7 on page 594, gives a relatively simple -algorithm for performing multiple precision integer addition. However, the description lacks any discussion concerning -the fact that the two integer inputs may be of differing magnitudes. As a result the implementation is not as simple -as the text would lead people to believe. Similarly the division routine (\textit{algorithm 14.20, pp. 598}) does not -discuss how to handle sign or handle the dividend's decreasing magnitude in the main loop (\textit{step \#3}). - -Both texts also do not discuss several key optimal algorithms required such as ``Comba'' and Karatsuba multipliers -and fast modular inversion, which we consider practical oversights. These optimal algorithms are vital to achieve -any form of useful performance in non-trivial applications. - -To solve this problem the focus of this text is on the practical aspects of implementing a multiple precision integer -package. As a case study the ``LibTomMath''\footnote{Available at \url{http://math.libtomcrypt.com}} package is used -to demonstrate algorithms with real implementations\footnote{In the ISO C programming language.} that have been field -tested and work very well. The LibTomMath library is freely available on the Internet for all uses and this text -discusses a very large portion of the inner workings of the library. - -The algorithms that are presented will always include at least one ``pseudo-code'' description followed -by the actual C source code that implements the algorithm. The pseudo-code can be used to implement the same -algorithm in other programming languages as the reader sees fit. - -This text shall also serve as a walkthrough of the creation of multiple precision algorithms from scratch. Showing -the reader how the algorithms fit together as well as where to start on various taskings. - -\section{Discussion and Notation} -\subsection{Notation} -A multiple precision integer of $n$-digits shall be denoted as $x = (x_{n-1}, \ldots, x_1, x_0)_{ \beta }$ and represent -the integer $x \equiv \sum_{i=0}^{n-1} x_i\beta^i$. The elements of the array $x$ are said to be the radix $\beta$ digits -of the integer. For example, $x = (1,2,3)_{10}$ would represent the integer -$1\cdot 10^2 + 2\cdot10^1 + 3\cdot10^0 = 123$. - -\index{mp\_int} -The term ``mp\_int'' shall refer to a composite structure which contains the digits of the integer it represents, as well -as auxilary data required to manipulate the data. These additional members are discussed further in section -\ref{sec:MPINT}. For the purposes of this text a ``multiple precision integer'' and an ``mp\_int'' are assumed to be -synonymous. When an algorithm is specified to accept an mp\_int variable it is assumed the various auxliary data members -are present as well. An expression of the type \textit{variablename.item} implies that it should evaluate to the -member named ``item'' of the variable. For example, a string of characters may have a member ``length'' which would -evaluate to the number of characters in the string. If the string $a$ equals ``hello'' then it follows that -$a.length = 5$. - -For certain discussions more generic algorithms are presented to help the reader understand the final algorithm used -to solve a given problem. When an algorithm is described as accepting an integer input it is assumed the input is -a plain integer with no additional multiple-precision members. That is, algorithms that use integers as opposed to -mp\_ints as inputs do not concern themselves with the housekeeping operations required such as memory management. These -algorithms will be used to establish the relevant theory which will subsequently be used to describe a multiple -precision algorithm to solve the same problem. - -\subsection{Precision Notation} -The variable $\beta$ represents the radix of a single digit of a multiple precision integer and -must be of the form $q^p$ for $q, p \in \Z^+$. A single precision variable must be able to represent integers in -the range $0 \le x < q \beta$ while a double precision variable must be able to represent integers in the range -$0 \le x < q \beta^2$. The extra radix-$q$ factor allows additions and subtractions to proceed without truncation of the -carry. Since all modern computers are binary, it is assumed that $q$ is two. - -\index{mp\_digit} \index{mp\_word} -Within the source code that will be presented for each algorithm, the data type \textbf{mp\_digit} will represent -a single precision integer type, while, the data type \textbf{mp\_word} will represent a double precision integer type. In -several algorithms (notably the Comba routines) temporary results will be stored in arrays of double precision mp\_words. -For the purposes of this text $x_j$ will refer to the $j$'th digit of a single precision array and $\hat x_j$ will refer to -the $j$'th digit of a double precision array. Whenever an expression is to be assigned to a double precision -variable it is assumed that all single precision variables are promoted to double precision during the evaluation. -Expressions that are assigned to a single precision variable are truncated to fit within the precision of a single -precision data type. - -For example, if $\beta = 10^2$ a single precision data type may represent a value in the -range $0 \le x < 10^3$, while a double precision data type may represent a value in the range $0 \le x < 10^5$. Let -$a = 23$ and $b = 49$ represent two single precision variables. The single precision product shall be written -as $c \leftarrow a \cdot b$ while the double precision product shall be written as $\hat c \leftarrow a \cdot b$. -In this particular case, $\hat c = 1127$ and $c = 127$. The most significant digit of the product would not fit -in a single precision data type and as a result $c \ne \hat c$. - -\subsection{Algorithm Inputs and Outputs} -Within the algorithm descriptions all variables are assumed to be scalars of either single or double precision -as indicated. The only exception to this rule is when variables have been indicated to be of type mp\_int. This -distinction is important as scalars are often used as array indicies and various other counters. - -\subsection{Mathematical Expressions} -The $\lfloor \mbox{ } \rfloor$ brackets imply an expression truncated to an integer not greater than the expression -itself. For example, $\lfloor 5.7 \rfloor = 5$. Similarly the $\lceil \mbox{ } \rceil$ brackets imply an expression -rounded to an integer not less than the expression itself. For example, $\lceil 5.1 \rceil = 6$. Typically when -the $/$ division symbol is used the intention is to perform an integer division with truncation. For example, -$5/2 = 2$ which will often be written as $\lfloor 5/2 \rfloor = 2$ for clarity. When an expression is written as a -fraction a real value division is implied, for example ${5 \over 2} = 2.5$. - -The norm of a multiple precision integer, for example $\vert \vert x \vert \vert$, will be used to represent the number of digits in the representation -of the integer. For example, $\vert \vert 123 \vert \vert = 3$ and $\vert \vert 79452 \vert \vert = 5$. - -\subsection{Work Effort} -\index{big-Oh} -To measure the efficiency of the specified algorithms, a modified big-Oh notation is used. In this system all -single precision operations are considered to have the same cost\footnote{Except where explicitly noted.}. -That is a single precision addition, multiplication and division are assumed to take the same time to -complete. While this is generally not true in practice, it will simplify the discussions considerably. - -Some algorithms have slight advantages over others which is why some constants will not be removed in -the notation. For example, a normal baseline multiplication (section \ref{sec:basemult}) requires $O(n^2)$ work while a -baseline squaring (section \ref{sec:basesquare}) requires $O({{n^2 + n}\over 2})$ work. In standard big-Oh notation these -would both be said to be equivalent to $O(n^2)$. However, -in the context of the this text this is not the case as the magnitude of the inputs will typically be rather small. As a -result small constant factors in the work effort will make an observable difference in algorithm efficiency. - -All of the algorithms presented in this text have a polynomial time work level. That is, of the form -$O(n^k)$ for $n, k \in \Z^{+}$. This will help make useful comparisons in terms of the speed of the algorithms and how -various optimizations will help pay off in the long run. - -\section{Exercises} -Within the more advanced chapters a section will be set aside to give the reader some challenging exercises related to -the discussion at hand. These exercises are not designed to be prize winning problems, but instead to be thought -provoking. Wherever possible the problems are forward minded, stating problems that will be answered in subsequent -chapters. The reader is encouraged to finish the exercises as they appear to get a better understanding of the -subject material. - -That being said, the problems are designed to affirm knowledge of a particular subject matter. Students in particular -are encouraged to verify they can answer the problems correctly before moving on. - -Similar to the exercises of \cite[pp. ix]{TAOCPV2} these exercises are given a scoring system based on the difficulty of -the problem. However, unlike \cite{TAOCPV2} the problems do not get nearly as hard. The scoring of these -exercises ranges from one (the easiest) to five (the hardest). The following table sumarizes the -scoring system used. - -\begin{figure}[here] -\begin{center} -\begin{small} -\begin{tabular}{|c|l|} -\hline $\left [ 1 \right ]$ & An easy problem that should only take the reader a manner of \\ - & minutes to solve. Usually does not involve much computer time \\ - & to solve. \\ -\hline $\left [ 2 \right ]$ & An easy problem that involves a marginal amount of computer \\ - & time usage. Usually requires a program to be written to \\ - & solve the problem. \\ -\hline $\left [ 3 \right ]$ & A moderately hard problem that requires a non-trivial amount \\ - & of work. Usually involves trivial research and development of \\ - & new theory from the perspective of a student. \\ -\hline $\left [ 4 \right ]$ & A moderately hard problem that involves a non-trivial amount \\ - & of work and research, the solution to which will demonstrate \\ - & a higher mastery of the subject matter. \\ -\hline $\left [ 5 \right ]$ & A hard problem that involves concepts that are difficult for a \\ - & novice to solve. Solutions to these problems will demonstrate a \\ - & complete mastery of the given subject. \\ -\hline -\end{tabular} -\end{small} -\end{center} -\caption{Exercise Scoring System} -\end{figure} - -Problems at the first level are meant to be simple questions that the reader can answer quickly without programming a solution or -devising new theory. These problems are quick tests to see if the material is understood. Problems at the second level -are also designed to be easy but will require a program or algorithm to be implemented to arrive at the answer. These -two levels are essentially entry level questions. - -Problems at the third level are meant to be a bit more difficult than the first two levels. The answer is often -fairly obvious but arriving at an exacting solution requires some thought and skill. These problems will almost always -involve devising a new algorithm or implementing a variation of another algorithm previously presented. Readers who can -answer these questions will feel comfortable with the concepts behind the topic at hand. - -Problems at the fourth level are meant to be similar to those of the level three questions except they will require -additional research to be completed. The reader will most likely not know the answer right away, nor will the text provide -the exact details of the answer until a subsequent chapter. - -Problems at the fifth level are meant to be the hardest -problems relative to all the other problems in the chapter. People who can correctly answer fifth level problems have a -mastery of the subject matter at hand. - -Often problems will be tied together. The purpose of this is to start a chain of thought that will be discussed in future chapters. The reader -is encouraged to answer the follow-up problems and try to draw the relevance of problems. - -\section{Introduction to LibTomMath} - -\subsection{What is LibTomMath?} -LibTomMath is a free and open source multiple precision integer library written entirely in portable ISO C. By portable it -is meant that the library does not contain any code that is computer platform dependent or otherwise problematic to use on -any given platform. - -The library has been successfully tested under numerous operating systems including Unix\footnote{All of these -trademarks belong to their respective rightful owners.}, MacOS, Windows, Linux, PalmOS and on standalone hardware such -as the Gameboy Advance. The library is designed to contain enough functionality to be able to develop applications such -as public key cryptosystems and still maintain a relatively small footprint. - -\subsection{Goals of LibTomMath} - -Libraries which obtain the most efficiency are rarely written in a high level programming language such as C. However, -even though this library is written entirely in ISO C, considerable care has been taken to optimize the algorithm implementations within the -library. Specifically the code has been written to work well with the GNU C Compiler (\textit{GCC}) on both x86 and ARM -processors. Wherever possible, highly efficient algorithms, such as Karatsuba multiplication, sliding window -exponentiation and Montgomery reduction have been provided to make the library more efficient. - -Even with the nearly optimal and specialized algorithms that have been included the Application Programing Interface -(\textit{API}) has been kept as simple as possible. Often generic place holder routines will make use of specialized -algorithms automatically without the developer's specific attention. One such example is the generic multiplication -algorithm \textbf{mp\_mul()} which will automatically use Toom--Cook, Karatsuba, Comba or baseline multiplication -based on the magnitude of the inputs and the configuration of the library. - -Making LibTomMath as efficient as possible is not the only goal of the LibTomMath project. Ideally the library should -be source compatible with another popular library which makes it more attractive for developers to use. In this case the -MPI library was used as a API template for all the basic functions. MPI was chosen because it is another library that fits -in the same niche as LibTomMath. Even though LibTomMath uses MPI as the template for the function names and argument -passing conventions, it has been written from scratch by Tom St Denis. - -The project is also meant to act as a learning tool for students, the logic being that no easy-to-follow ``bignum'' -library exists which can be used to teach computer science students how to perform fast and reliable multiple precision -integer arithmetic. To this end the source code has been given quite a few comments and algorithm discussion points. - -\section{Choice of LibTomMath} -LibTomMath was chosen as the case study of this text not only because the author of both projects is one and the same but -for more worthy reasons. Other libraries such as GMP \cite{GMP}, MPI \cite{MPI}, LIP \cite{LIP} and OpenSSL -\cite{OPENSSL} have multiple precision integer arithmetic routines but would not be ideal for this text for -reasons that will be explained in the following sub-sections. - -\subsection{Code Base} -The LibTomMath code base is all portable ISO C source code. This means that there are no platform dependent conditional -segments of code littered throughout the source. This clean and uncluttered approach to the library means that a -developer can more readily discern the true intent of a given section of source code without trying to keep track of -what conditional code will be used. - -The code base of LibTomMath is well organized. Each function is in its own separate source code file -which allows the reader to find a given function very quickly. On average there are $76$ lines of code per source -file which makes the source very easily to follow. By comparison MPI and LIP are single file projects making code tracing -very hard. GMP has many conditional code segments which also hinder tracing. - -When compiled with GCC for the x86 processor and optimized for speed the entire library is approximately $100$KiB\footnote{The notation ``KiB'' means $2^{10}$ octets, similarly ``MiB'' means $2^{20}$ octets.} - which is fairly small compared to GMP (over $250$KiB). LibTomMath is slightly larger than MPI (which compiles to about -$50$KiB) but LibTomMath is also much faster and more complete than MPI. - -\subsection{API Simplicity} -LibTomMath is designed after the MPI library and shares the API design. Quite often programs that use MPI will build -with LibTomMath without change. The function names correlate directly to the action they perform. Almost all of the -functions share the same parameter passing convention. The learning curve is fairly shallow with the API provided -which is an extremely valuable benefit for the student and developer alike. - -The LIP library is an example of a library with an API that is awkward to work with. LIP uses function names that are often ``compressed'' to -illegible short hand. LibTomMath does not share this characteristic. - -The GMP library also does not return error codes. Instead it uses a POSIX.1 \cite{POSIX1} signal system where errors -are signaled to the host application. This happens to be the fastest approach but definitely not the most versatile. In -effect a math error (i.e. invalid input, heap error, etc) can cause a program to stop functioning which is definitely -undersireable in many situations. - -\subsection{Optimizations} -While LibTomMath is certainly not the fastest library (GMP often beats LibTomMath by a factor of two) it does -feature a set of optimal algorithms for tasks such as modular reduction, exponentiation, multiplication and squaring. GMP -and LIP also feature such optimizations while MPI only uses baseline algorithms with no optimizations. GMP lacks a few -of the additional modular reduction optimizations that LibTomMath features\footnote{At the time of this writing GMP -only had Barrett and Montgomery modular reduction algorithms.}. - -LibTomMath is almost always an order of magnitude faster than the MPI library at computationally expensive tasks such as modular -exponentiation. In the grand scheme of ``bignum'' libraries LibTomMath is faster than the average library and usually -slower than the best libraries such as GMP and OpenSSL by only a small factor. - -\subsection{Portability and Stability} -LibTomMath will build ``out of the box'' on any platform equipped with a modern version of the GNU C Compiler -(\textit{GCC}). This means that without changes the library will build without configuration or setting up any -variables. LIP and MPI will build ``out of the box'' as well but have numerous known bugs. Most notably the author of -MPI has recently stopped working on his library and LIP has long since been discontinued. - -GMP requires a configuration script to run and will not build out of the box. GMP and LibTomMath are still in active -development and are very stable across a variety of platforms. - -\subsection{Choice} -LibTomMath is a relatively compact, well documented, highly optimized and portable library which seems only natural for -the case study of this text. Various source files from the LibTomMath project will be included within the text. However, -the reader is encouraged to download their own copy of the library to actually be able to work with the library. - -\chapter{Getting Started} -\section{Library Basics} -The trick to writing any useful library of source code is to build a solid foundation and work outwards from it. First, -a problem along with allowable solution parameters should be identified and analyzed. In this particular case the -inability to accomodate multiple precision integers is the problem. Futhermore, the solution must be written -as portable source code that is reasonably efficient across several different computer platforms. - -After a foundation is formed the remainder of the library can be designed and implemented in a hierarchical fashion. -That is, to implement the lowest level dependencies first and work towards the most abstract functions last. For example, -before implementing a modular exponentiation algorithm one would implement a modular reduction algorithm. -By building outwards from a base foundation instead of using a parallel design methodology the resulting project is -highly modular. Being highly modular is a desirable property of any project as it often means the resulting product -has a small footprint and updates are easy to perform. - -Usually when I start a project I will begin with the header files. I define the data types I think I will need and -prototype the initial functions that are not dependent on other functions (within the library). After I -implement these base functions I prototype more dependent functions and implement them. The process repeats until -I implement all of the functions I require. For example, in the case of LibTomMath I implemented functions such as -mp\_init() well before I implemented mp\_mul() and even further before I implemented mp\_exptmod(). As an example as to -why this design works note that the Karatsuba and Toom-Cook multipliers were written \textit{after} the -dependent function mp\_exptmod() was written. Adding the new multiplication algorithms did not require changes to the -mp\_exptmod() function itself and lowered the total cost of ownership (\textit{so to speak}) and of development -for new algorithms. This methodology allows new algorithms to be tested in a complete framework with relative ease. - -FIGU,design_process,Design Flow of the First Few Original LibTomMath Functions. - -Only after the majority of the functions were in place did I pursue a less hierarchical approach to auditing and optimizing -the source code. For example, one day I may audit the multipliers and the next day the polynomial basis functions. - -It only makes sense to begin the text with the preliminary data types and support algorithms required as well. -This chapter discusses the core algorithms of the library which are the dependents for every other algorithm. - -\section{What is a Multiple Precision Integer?} -Recall that most programming languages, in particular ISO C \cite{ISOC}, only have fixed precision data types that on their own cannot -be used to represent values larger than their precision will allow. The purpose of multiple precision algorithms is -to use fixed precision data types to create and manipulate multiple precision integers which may represent values -that are very large. - -As a well known analogy, school children are taught how to form numbers larger than nine by prepending more radix ten digits. In the decimal system -the largest single digit value is $9$. However, by concatenating digits together larger numbers may be represented. Newly prepended digits -(\textit{to the left}) are said to be in a different power of ten column. That is, the number $123$ can be described as having a $1$ in the hundreds -column, $2$ in the tens column and $3$ in the ones column. Or more formally $123 = 1 \cdot 10^2 + 2 \cdot 10^1 + 3 \cdot 10^0$. Computer based -multiple precision arithmetic is essentially the same concept. Larger integers are represented by adjoining fixed -precision computer words with the exception that a different radix is used. - -What most people probably do not think about explicitly are the various other attributes that describe a multiple precision -integer. For example, the integer $154_{10}$ has two immediately obvious properties. First, the integer is positive, -that is the sign of this particular integer is positive as opposed to negative. Second, the integer has three digits in -its representation. There is an additional property that the integer posesses that does not concern pencil-and-paper -arithmetic. The third property is how many digits placeholders are available to hold the integer. - -The human analogy of this third property is ensuring there is enough space on the paper to write the integer. For example, -if one starts writing a large number too far to the right on a piece of paper they will have to erase it and move left. -Similarly, computer algorithms must maintain strict control over memory usage to ensure that the digits of an integer -will not exceed the allowed boundaries. These three properties make up what is known as a multiple precision -integer or mp\_int for short. - -\subsection{The mp\_int Structure} -\label{sec:MPINT} -The mp\_int structure is the ISO C based manifestation of what represents a multiple precision integer. The ISO C standard does not provide for -any such data type but it does provide for making composite data types known as structures. The following is the structure definition -used within LibTomMath. - -\index{mp\_int} -\begin{figure}[here] -\begin{center} -\begin{small} -%\begin{verbatim} -\begin{tabular}{|l|} -\hline -typedef struct \{ \\ -\hspace{3mm}int used, alloc, sign;\\ -\hspace{3mm}mp\_digit *dp;\\ -\} \textbf{mp\_int}; \\ -\hline -\end{tabular} -%\end{verbatim} -\end{small} -\caption{The mp\_int Structure} -\label{fig:mpint} -\end{center} -\end{figure} - -The mp\_int structure (fig. \ref{fig:mpint}) can be broken down as follows. - -\begin{enumerate} -\item The \textbf{used} parameter denotes how many digits of the array \textbf{dp} contain the digits used to represent -a given integer. The \textbf{used} count must be positive (or zero) and may not exceed the \textbf{alloc} count. - -\item The \textbf{alloc} parameter denotes how -many digits are available in the array to use by functions before it has to increase in size. When the \textbf{used} count -of a result would exceed the \textbf{alloc} count all of the algorithms will automatically increase the size of the -array to accommodate the precision of the result. - -\item The pointer \textbf{dp} points to a dynamically allocated array of digits that represent the given multiple -precision integer. It is padded with $(\textbf{alloc} - \textbf{used})$ zero digits. The array is maintained in a least -significant digit order. As a pencil and paper analogy the array is organized such that the right most digits are stored -first starting at the location indexed by zero\footnote{In C all arrays begin at zero.} in the array. For example, -if \textbf{dp} contains $\lbrace a, b, c, \ldots \rbrace$ where \textbf{dp}$_0 = a$, \textbf{dp}$_1 = b$, \textbf{dp}$_2 = c$, $\ldots$ then -it would represent the integer $a + b\beta + c\beta^2 + \ldots$ - -\index{MP\_ZPOS} \index{MP\_NEG} -\item The \textbf{sign} parameter denotes the sign as either zero/positive (\textbf{MP\_ZPOS}) or negative (\textbf{MP\_NEG}). -\end{enumerate} - -\subsubsection{Valid mp\_int Structures} -Several rules are placed on the state of an mp\_int structure and are assumed to be followed for reasons of efficiency. -The only exceptions are when the structure is passed to initialization functions such as mp\_init() and mp\_init\_copy(). - -\begin{enumerate} -\item The value of \textbf{alloc} may not be less than one. That is \textbf{dp} always points to a previously allocated -array of digits. -\item The value of \textbf{used} may not exceed \textbf{alloc} and must be greater than or equal to zero. -\item The value of \textbf{used} implies the digit at index $(used - 1)$ of the \textbf{dp} array is non-zero. That is, -leading zero digits in the most significant positions must be trimmed. - \begin{enumerate} - \item Digits in the \textbf{dp} array at and above the \textbf{used} location must be zero. - \end{enumerate} -\item The value of \textbf{sign} must be \textbf{MP\_ZPOS} if \textbf{used} is zero; -this represents the mp\_int value of zero. -\end{enumerate} - -\section{Argument Passing} -A convention of argument passing must be adopted early on in the development of any library. Making the function -prototypes consistent will help eliminate many headaches in the future as the library grows to significant complexity. -In LibTomMath the multiple precision integer functions accept parameters from left to right as pointers to mp\_int -structures. That means that the source (input) operands are placed on the left and the destination (output) on the right. -Consider the following examples. - -\begin{verbatim} - mp_mul(&a, &b, &c); /* c = a * b */ - mp_add(&a, &b, &a); /* a = a + b */ - mp_sqr(&a, &b); /* b = a * a */ -\end{verbatim} - -The left to right order is a fairly natural way to implement the functions since it lets the developer read aloud the -functions and make sense of them. For example, the first function would read ``multiply a and b and store in c''. - -Certain libraries (\textit{LIP by Lenstra for instance}) accept parameters the other way around, to mimic the order -of assignment expressions. That is, the destination (output) is on the left and arguments (inputs) are on the right. In -truth, it is entirely a matter of preference. In the case of LibTomMath the convention from the MPI library has been -adopted. - -Another very useful design consideration, provided for in LibTomMath, is whether to allow argument sources to also be a -destination. For example, the second example (\textit{mp\_add}) adds $a$ to $b$ and stores in $a$. This is an important -feature to implement since it allows the calling functions to cut down on the number of variables it must maintain. -However, to implement this feature specific care has to be given to ensure the destination is not modified before the -source is fully read. - -\section{Return Values} -A well implemented application, no matter what its purpose, should trap as many runtime errors as possible and return them -to the caller. By catching runtime errors a library can be guaranteed to prevent undefined behaviour. However, the end -developer can still manage to cause a library to crash. For example, by passing an invalid pointer an application may -fault by dereferencing memory not owned by the application. - -In the case of LibTomMath the only errors that are checked for are related to inappropriate inputs (division by zero for -instance) and memory allocation errors. It will not check that the mp\_int passed to any function is valid nor -will it check pointers for validity. Any function that can cause a runtime error will return an error code as an -\textbf{int} data type with one of the following values (fig \ref{fig:errcodes}). - -\index{MP\_OKAY} \index{MP\_VAL} \index{MP\_MEM} -\begin{figure}[here] -\begin{center} -\begin{tabular}{|l|l|} -\hline \textbf{Value} & \textbf{Meaning} \\ -\hline \textbf{MP\_OKAY} & The function was successful \\ -\hline \textbf{MP\_VAL} & One of the input value(s) was invalid \\ -\hline \textbf{MP\_MEM} & The function ran out of heap memory \\ -\hline -\end{tabular} -\end{center} -\caption{LibTomMath Error Codes} -\label{fig:errcodes} -\end{figure} - -When an error is detected within a function it should free any memory it allocated, often during the initialization of -temporary mp\_ints, and return as soon as possible. The goal is to leave the system in the same state it was when the -function was called. Error checking with this style of API is fairly simple. - -\begin{verbatim} - int err; - if ((err = mp_add(&a, &b, &c)) != MP_OKAY) { - printf("Error: %s\n", mp_error_to_string(err)); - exit(EXIT_FAILURE); - } -\end{verbatim} - -The GMP \cite{GMP} library uses C style \textit{signals} to flag errors which is of questionable use. Not all errors are fatal -and it was not deemed ideal by the author of LibTomMath to force developers to have signal handlers for such cases. - -\section{Initialization and Clearing} -The logical starting point when actually writing multiple precision integer functions is the initialization and -clearing of the mp\_int structures. These two algorithms will be used by the majority of the higher level algorithms. - -Given the basic mp\_int structure an initialization routine must first allocate memory to hold the digits of -the integer. Often it is optimal to allocate a sufficiently large pre-set number of digits even though -the initial integer will represent zero. If only a single digit were allocated quite a few subsequent re-allocations -would occur when operations are performed on the integers. There is a tradeoff between how many default digits to allocate -and how many re-allocations are tolerable. Obviously allocating an excessive amount of digits initially will waste -memory and become unmanageable. - -If the memory for the digits has been successfully allocated then the rest of the members of the structure must -be initialized. Since the initial state of an mp\_int is to represent the zero integer, the allocated digits must be set -to zero. The \textbf{used} count set to zero and \textbf{sign} set to \textbf{MP\_ZPOS}. - -\subsection{Initializing an mp\_int} -An mp\_int is said to be initialized if it is set to a valid, preferably default, state such that all of the members of the -structure are set to valid values. The mp\_init algorithm will perform such an action. - -\index{mp\_init} -\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_init}. \\ -\textbf{Input}. An mp\_int $a$ \\ -\textbf{Output}. Allocate memory and initialize $a$ to a known valid mp\_int state. \\ -\hline \\ -1. Allocate memory for \textbf{MP\_PREC} digits. \\ -2. If the allocation failed return(\textit{MP\_MEM}) \\ -3. for $n$ from $0$ to $MP\_PREC - 1$ do \\ -\hspace{3mm}3.1 $a_n \leftarrow 0$\\ -4. $a.sign \leftarrow MP\_ZPOS$\\ -5. $a.used \leftarrow 0$\\ -6. $a.alloc \leftarrow MP\_PREC$\\ -7. Return(\textit{MP\_OKAY})\\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_init} -\end{figure} - -\textbf{Algorithm mp\_init.} -The purpose of this function is to initialize an mp\_int structure so that the rest of the library can properly -manipulte it. It is assumed that the input may not have had any of its members previously initialized which is certainly -a valid assumption if the input resides on the stack. - -Before any of the members such as \textbf{sign}, \textbf{used} or \textbf{alloc} are initialized the memory for -the digits is allocated. If this fails the function returns before setting any of the other members. The \textbf{MP\_PREC} -name represents a constant\footnote{Defined in the ``tommath.h'' header file within LibTomMath.} -used to dictate the minimum precision of newly initialized mp\_int integers. Ideally, it is at least equal to the smallest -precision number you'll be working with. - -Allocating a block of digits at first instead of a single digit has the benefit of lowering the number of usually slow -heap operations later functions will have to perform in the future. If \textbf{MP\_PREC} is set correctly the slack -memory and the number of heap operations will be trivial. - -Once the allocation has been made the digits have to be set to zero as well as the \textbf{used}, \textbf{sign} and -\textbf{alloc} members initialized. This ensures that the mp\_int will always represent the default state of zero regardless -of the original condition of the input. - -\textbf{Remark.} -This function introduces the idiosyncrasy that all iterative loops, commonly initiated with the ``for'' keyword, iterate incrementally -when the ``to'' keyword is placed between two expressions. For example, ``for $a$ from $b$ to $c$ do'' means that -a subsequent expression (or body of expressions) are to be evaluated upto $c - b$ times so long as $b \le c$. In each -iteration the variable $a$ is substituted for a new integer that lies inclusively between $b$ and $c$. If $b > c$ occured -the loop would not iterate. By contrast if the ``downto'' keyword were used in place of ``to'' the loop would iterate -decrementally. - -EXAM,bn_mp_init.c - -One immediate observation of this initializtion function is that it does not return a pointer to a mp\_int structure. It -is assumed that the caller has already allocated memory for the mp\_int structure, typically on the application stack. The -call to mp\_init() is used only to initialize the members of the structure to a known default state. - -Here we see (line @23,XMALLOC@) the memory allocation is performed first. This allows us to exit cleanly and quickly -if there is an error. If the allocation fails the routine will return \textbf{MP\_MEM} to the caller to indicate there -was a memory error. The function XMALLOC is what actually allocates the memory. Technically XMALLOC is not a function -but a macro defined in ``tommath.h``. By default, XMALLOC will evaluate to malloc() which is the C library's built--in -memory allocation routine. - -In order to assure the mp\_int is in a known state the digits must be set to zero. On most platforms this could have been -accomplished by using calloc() instead of malloc(). However, to correctly initialize a integer type to a given value in a -portable fashion you have to actually assign the value. The for loop (line @28,for@) performs this required -operation. - -After the memory has been successfully initialized the remainder of the members are initialized -(lines @29,used@ through @31,sign@) to their respective default states. At this point the algorithm has succeeded and -a success code is returned to the calling function. If this function returns \textbf{MP\_OKAY} it is safe to assume the -mp\_int structure has been properly initialized and is safe to use with other functions within the library. - -\subsection{Clearing an mp\_int} -When an mp\_int is no longer required by the application, the memory that has been allocated for its digits must be -returned to the application's memory pool with the mp\_clear algorithm. - -\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_clear}. \\ -\textbf{Input}. An mp\_int $a$ \\ -\textbf{Output}. The memory for $a$ shall be deallocated. \\ -\hline \\ -1. If $a$ has been previously freed then return(\textit{MP\_OKAY}). \\ -2. for $n$ from 0 to $a.used - 1$ do \\ -\hspace{3mm}2.1 $a_n \leftarrow 0$ \\ -3. Free the memory allocated for the digits of $a$. \\ -4. $a.used \leftarrow 0$ \\ -5. $a.alloc \leftarrow 0$ \\ -6. $a.sign \leftarrow MP\_ZPOS$ \\ -7. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_clear} -\end{figure} - -\textbf{Algorithm mp\_clear.} -This algorithm accomplishes two goals. First, it clears the digits and the other mp\_int members. This ensures that -if a developer accidentally re-uses a cleared structure it is less likely to cause problems. The second goal -is to free the allocated memory. - -The logic behind the algorithm is extended by marking cleared mp\_int structures so that subsequent calls to this -algorithm will not try to free the memory multiple times. Cleared mp\_ints are detectable by having a pre-defined invalid -digit pointer \textbf{dp} setting. - -Once an mp\_int has been cleared the mp\_int structure is no longer in a valid state for any other algorithm -with the exception of algorithms mp\_init, mp\_init\_copy, mp\_init\_size and mp\_clear. - -EXAM,bn_mp_clear.c - -The algorithm only operates on the mp\_int if it hasn't been previously cleared. The if statement (line @23,a->dp != NULL@) -checks to see if the \textbf{dp} member is not \textbf{NULL}. If the mp\_int is a valid mp\_int then \textbf{dp} cannot be -\textbf{NULL} in which case the if statement will evaluate to true. - -The digits of the mp\_int are cleared by the for loop (line @25,for@) which assigns a zero to every digit. Similar to mp\_init() -the digits are assigned zero instead of using block memory operations (such as memset()) since this is more portable. - -The digits are deallocated off the heap via the XFREE macro. Similar to XMALLOC the XFREE macro actually evaluates to -a standard C library function. In this case the free() function. Since free() only deallocates the memory the pointer -still has to be reset to \textbf{NULL} manually (line @33,NULL@). - -Now that the digits have been cleared and deallocated the other members are set to their final values (lines @34,= 0@ and @35,ZPOS@). - -\section{Maintenance Algorithms} - -The previous sections describes how to initialize and clear an mp\_int structure. To further support operations -that are to be performed on mp\_int structures (such as addition and multiplication) the dependent algorithms must be -able to augment the precision of an mp\_int and -initialize mp\_ints with differing initial conditions. - -These algorithms complete the set of low level algorithms required to work with mp\_int structures in the higher level -algorithms such as addition, multiplication and modular exponentiation. - -\subsection{Augmenting an mp\_int's Precision} -When storing a value in an mp\_int structure, a sufficient number of digits must be available to accomodate the entire -result of an operation without loss of precision. Quite often the size of the array given by the \textbf{alloc} member -is large enough to simply increase the \textbf{used} digit count. However, when the size of the array is too small it -must be re-sized appropriately to accomodate the result. The mp\_grow algorithm will provide this functionality. - -\newpage\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_grow}. \\ -\textbf{Input}. An mp\_int $a$ and an integer $b$. \\ -\textbf{Output}. $a$ is expanded to accomodate $b$ digits. \\ -\hline \\ -1. if $a.alloc \ge b$ then return(\textit{MP\_OKAY}) \\ -2. $u \leftarrow b\mbox{ (mod }MP\_PREC\mbox{)}$ \\ -3. $v \leftarrow b + 2 \cdot MP\_PREC - u$ \\ -4. Re-allocate the array of digits $a$ to size $v$ \\ -5. If the allocation failed then return(\textit{MP\_MEM}). \\ -6. for n from a.alloc to $v - 1$ do \\ -\hspace{+3mm}6.1 $a_n \leftarrow 0$ \\ -7. $a.alloc \leftarrow v$ \\ -8. Return(\textit{MP\_OKAY}) \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_grow} -\end{figure} - -\textbf{Algorithm mp\_grow.} -It is ideal to prevent re-allocations from being performed if they are not required (step one). This is useful to -prevent mp\_ints from growing excessively in code that erroneously calls mp\_grow. - -The requested digit count is padded up to next multiple of \textbf{MP\_PREC} plus an additional \textbf{MP\_PREC} (steps two and three). -This helps prevent many trivial reallocations that would grow an mp\_int by trivially small values. - -It is assumed that the reallocation (step four) leaves the lower $a.alloc$ digits of the mp\_int intact. This is much -akin to how the \textit{realloc} function from the standard C library works. Since the newly allocated digits are -assumed to contain undefined values they are initially set to zero. - -EXAM,bn_mp_grow.c - -A quick optimization is to first determine if a memory re-allocation is required at all. The if statement (line @24,alloc@) checks -if the \textbf{alloc} member of the mp\_int is smaller than the requested digit count. If the count is not larger than \textbf{alloc} -the function skips the re-allocation part thus saving time. - -When a re-allocation is performed it is turned into an optimal request to save time in the future. The requested digit count is -padded upwards to 2nd multiple of \textbf{MP\_PREC} larger than \textbf{alloc} (line @25, size@). The XREALLOC function is used -to re-allocate the memory. As per the other functions XREALLOC is actually a macro which evaluates to realloc by default. The realloc -function leaves the base of the allocation intact which means the first \textbf{alloc} digits of the mp\_int are the same as before -the re-allocation. All that is left is to clear the newly allocated digits and return. - -Note that the re-allocation result is actually stored in a temporary pointer $tmp$. This is to allow this function to return -an error with a valid pointer. Earlier releases of the library stored the result of XREALLOC into the mp\_int $a$. That would -result in a memory leak if XREALLOC ever failed. - -\subsection{Initializing Variable Precision mp\_ints} -Occasionally the number of digits required will be known in advance of an initialization, based on, for example, the size -of input mp\_ints to a given algorithm. The purpose of algorithm mp\_init\_size is similar to mp\_init except that it -will allocate \textit{at least} a specified number of digits. - -\begin{figure}[here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_init\_size}. \\ -\textbf{Input}. An mp\_int $a$ and the requested number of digits $b$. \\ -\textbf{Output}. $a$ is initialized to hold at least $b$ digits. \\ -\hline \\ -1. $u \leftarrow b \mbox{ (mod }MP\_PREC\mbox{)}$ \\ -2. $v \leftarrow b + 2 \cdot MP\_PREC - u$ \\ -3. Allocate $v$ digits. \\ -4. for $n$ from $0$ to $v - 1$ do \\ -\hspace{3mm}4.1 $a_n \leftarrow 0$ \\ -5. $a.sign \leftarrow MP\_ZPOS$\\ -6. $a.used \leftarrow 0$\\ -7. $a.alloc \leftarrow v$\\ -8. Return(\textit{MP\_OKAY})\\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_init\_size} -\end{figure} - -\textbf{Algorithm mp\_init\_size.} -This algorithm will initialize an mp\_int structure $a$ like algorithm mp\_init with the exception that the number of -digits allocated can be controlled by the second input argument $b$. The input size is padded upwards so it is a -multiple of \textbf{MP\_PREC} plus an additional \textbf{MP\_PREC} digits. This padding is used to prevent trivial -allocations from becoming a bottleneck in the rest of the algorithms. - -Like algorithm mp\_init, the mp\_int structure is initialized to a default state representing the integer zero. This -particular algorithm is useful if it is known ahead of time the approximate size of the input. If the approximation is -correct no further memory re-allocations are required to work with the mp\_int. - -EXAM,bn_mp_init_size.c - -The number of digits $b$ requested is padded (line @22,MP_PREC@) by first augmenting it to the next multiple of -\textbf{MP\_PREC} and then adding \textbf{MP\_PREC} to the result. If the memory can be successfully allocated the -mp\_int is placed in a default state representing the integer zero. Otherwise, the error code \textbf{MP\_MEM} will be -returned (line @27,return@). - -The digits are allocated with the malloc() function (line @27,XMALLOC@) and set to zero afterwards (line @38,for@). The -\textbf{used} count is set to zero, the \textbf{alloc} count set to the padded digit count and the \textbf{sign} flag set -to \textbf{MP\_ZPOS} to achieve a default valid mp\_int state (lines @29,used@, @30,alloc@ and @31,sign@). If the function -returns succesfully then it is correct to assume that the mp\_int structure is in a valid state for the remainder of the -functions to work with. - -\subsection{Multiple Integer Initializations and Clearings} -Occasionally a function will require a series of mp\_int data types to be made available simultaneously. -The purpose of algorithm mp\_init\_multi is to initialize a variable length array of mp\_int structures in a single -statement. It is essentially a shortcut to multiple initializations. - -\newpage\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_init\_multi}. \\ -\textbf{Input}. Variable length array $V_k$ of mp\_int variables of length $k$. \\ -\textbf{Output}. The array is initialized such that each mp\_int of $V_k$ is ready to use. \\ -\hline \\ -1. for $n$ from 0 to $k - 1$ do \\ -\hspace{+3mm}1.1. Initialize the mp\_int $V_n$ (\textit{mp\_init}) \\ -\hspace{+3mm}1.2. If initialization failed then do \\ -\hspace{+6mm}1.2.1. for $j$ from $0$ to $n$ do \\ -\hspace{+9mm}1.2.1.1. Free the mp\_int $V_j$ (\textit{mp\_clear}) \\ -\hspace{+6mm}1.2.2. Return(\textit{MP\_MEM}) \\ -2. Return(\textit{MP\_OKAY}) \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_init\_multi} -\end{figure} - -\textbf{Algorithm mp\_init\_multi.} -The algorithm will initialize the array of mp\_int variables one at a time. If a runtime error has been detected -(\textit{step 1.2}) all of the previously initialized variables are cleared. The goal is an ``all or nothing'' -initialization which allows for quick recovery from runtime errors. - -EXAM,bn_mp_init_multi.c - -This function intializes a variable length list of mp\_int structure pointers. However, instead of having the mp\_int -structures in an actual C array they are simply passed as arguments to the function. This function makes use of the -``...'' argument syntax of the C programming language. The list is terminated with a final \textbf{NULL} argument -appended on the right. - -The function uses the ``stdarg.h'' \textit{va} functions to step portably through the arguments to the function. A count -$n$ of succesfully initialized mp\_int structures is maintained (line @47,n++@) such that if a failure does occur, -the algorithm can backtrack and free the previously initialized structures (lines @27,if@ to @46,}@). - - -\subsection{Clamping Excess Digits} -When a function anticipates a result will be $n$ digits it is simpler to assume this is true within the body of -the function instead of checking during the computation. For example, a multiplication of a $i$ digit number by a -$j$ digit produces a result of at most $i + j$ digits. It is entirely possible that the result is $i + j - 1$ -though, with no final carry into the last position. However, suppose the destination had to be first expanded -(\textit{via mp\_grow}) to accomodate $i + j - 1$ digits than further expanded to accomodate the final carry. -That would be a considerable waste of time since heap operations are relatively slow. - -The ideal solution is to always assume the result is $i + j$ and fix up the \textbf{used} count after the function -terminates. This way a single heap operation (\textit{at most}) is required. However, if the result was not checked -there would be an excess high order zero digit. - -For example, suppose the product of two integers was $x_n = (0x_{n-1}x_{n-2}...x_0)_{\beta}$. The leading zero digit -will not contribute to the precision of the result. In fact, through subsequent operations more leading zero digits would -accumulate to the point the size of the integer would be prohibitive. As a result even though the precision is very -low the representation is excessively large. - -The mp\_clamp algorithm is designed to solve this very problem. It will trim high-order zeros by decrementing the -\textbf{used} count until a non-zero most significant digit is found. Also in this system, zero is considered to be a -positive number which means that if the \textbf{used} count is decremented to zero, the sign must be set to -\textbf{MP\_ZPOS}. - -\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_clamp}. \\ -\textbf{Input}. An mp\_int $a$ \\ -\textbf{Output}. Any excess leading zero digits of $a$ are removed \\ -\hline \\ -1. while $a.used > 0$ and $a_{a.used - 1} = 0$ do \\ -\hspace{+3mm}1.1 $a.used \leftarrow a.used - 1$ \\ -2. if $a.used = 0$ then do \\ -\hspace{+3mm}2.1 $a.sign \leftarrow MP\_ZPOS$ \\ -\hline \\ -\end{tabular} -\end{center} -\caption{Algorithm mp\_clamp} -\end{figure} - -\textbf{Algorithm mp\_clamp.} -As can be expected this algorithm is very simple. The loop on step one is expected to iterate only once or twice at -the most. For example, this will happen in cases where there is not a carry to fill the last position. Step two fixes the sign for -when all of the digits are zero to ensure that the mp\_int is valid at all times. - -EXAM,bn_mp_clamp.c - -Note on line @27,while@ how to test for the \textbf{used} count is made on the left of the \&\& operator. In the C programming -language the terms to \&\& are evaluated left to right with a boolean short-circuit if any condition fails. This is -important since if the \textbf{used} is zero the test on the right would fetch below the array. That is obviously -undesirable. The parenthesis on line @28,a->used@ is used to make sure the \textbf{used} count is decremented and not -the pointer ``a''. - -\section*{Exercises} -\begin{tabular}{cl} -$\left [ 1 \right ]$ & Discuss the relevance of the \textbf{used} member of the mp\_int structure. \\ - & \\ -$\left [ 1 \right ]$ & Discuss the consequences of not using padding when performing allocations. \\ - & \\ -$\left [ 2 \right ]$ & Estimate an ideal value for \textbf{MP\_PREC} when performing 1024-bit RSA \\ - & encryption when $\beta = 2^{28}$. \\ - & \\ -$\left [ 1 \right ]$ & Discuss the relevance of the algorithm mp\_clamp. What does it prevent? \\ - & \\ -$\left [ 1 \right ]$ & Give an example of when the algorithm mp\_init\_copy might be useful. \\ - & \\ -\end{tabular} - - -%%% -% CHAPTER FOUR -%%% - -\chapter{Basic Operations} - -\section{Introduction} -In the previous chapter a series of low level algorithms were established that dealt with initializing and maintaining -mp\_int structures. This chapter will discuss another set of seemingly non-algebraic algorithms which will form the low -level basis of the entire library. While these algorithm are relatively trivial it is important to understand how they -work before proceeding since these algorithms will be used almost intrinsically in the following chapters. - -The algorithms in this chapter deal primarily with more ``programmer'' related tasks such as creating copies of -mp\_int structures, assigning small values to mp\_int structures and comparisons of the values mp\_int structures -represent. - -\section{Assigning Values to mp\_int Structures} -\subsection{Copying an mp\_int} -Assigning the value that a given mp\_int structure represents to another mp\_int structure shall be known as making -a copy for the purposes of this text. The copy of the mp\_int will be a separate entity that represents the same -value as the mp\_int it was copied from. The mp\_copy algorithm provides this functionality. - -\newpage\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_copy}. \\ -\textbf{Input}. An mp\_int $a$ and $b$. \\ -\textbf{Output}. Store a copy of $a$ in $b$. \\ -\hline \\ -1. If $b.alloc < a.used$ then grow $b$ to $a.used$ digits. (\textit{mp\_grow}) \\ -2. for $n$ from 0 to $a.used - 1$ do \\ -\hspace{3mm}2.1 $b_{n} \leftarrow a_{n}$ \\ -3. for $n$ from $a.used$ to $b.used - 1$ do \\ -\hspace{3mm}3.1 $b_{n} \leftarrow 0$ \\ -4. $b.used \leftarrow a.used$ \\ -5. $b.sign \leftarrow a.sign$ \\ -6. return(\textit{MP\_OKAY}) \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_copy} -\end{figure} - -\textbf{Algorithm mp\_copy.} -This algorithm copies the mp\_int $a$ such that upon succesful termination of the algorithm the mp\_int $b$ will -represent the same integer as the mp\_int $a$. The mp\_int $b$ shall be a complete and distinct copy of the -mp\_int $a$ meaing that the mp\_int $a$ can be modified and it shall not affect the value of the mp\_int $b$. - -If $b$ does not have enough room for the digits of $a$ it must first have its precision augmented via the mp\_grow -algorithm. The digits of $a$ are copied over the digits of $b$ and any excess digits of $b$ are set to zero (step two -and three). The \textbf{used} and \textbf{sign} members of $a$ are finally copied over the respective members of -$b$. - -\textbf{Remark.} This algorithm also introduces a new idiosyncrasy that will be used throughout the rest of the -text. The error return codes of other algorithms are not explicitly checked in the pseudo-code presented. For example, in -step one of the mp\_copy algorithm the return of mp\_grow is not explicitly checked to ensure it succeeded. Text space is -limited so it is assumed that if a algorithm fails it will clear all temporarily allocated mp\_ints and return -the error code itself. However, the C code presented will demonstrate all of the error handling logic required to -implement the pseudo-code. - -EXAM,bn_mp_copy.c - -Occasionally a dependent algorithm may copy an mp\_int effectively into itself such as when the input and output -mp\_int structures passed to a function are one and the same. For this case it is optimal to return immediately without -copying digits (line @24,a == b@). - -The mp\_int $b$ must have enough digits to accomodate the used digits of the mp\_int $a$. If $b.alloc$ is less than -$a.used$ the algorithm mp\_grow is used to augment the precision of $b$ (lines @29,alloc@ to @33,}@). In order to -simplify the inner loop that copies the digits from $a$ to $b$, two aliases $tmpa$ and $tmpb$ point directly at the digits -of the mp\_ints $a$ and $b$ respectively. These aliases (lines @42,tmpa@ and @45,tmpb@) allow the compiler to access the digits without first dereferencing the -mp\_int pointers and then subsequently the pointer to the digits. - -After the aliases are established the digits from $a$ are copied into $b$ (lines @48,for@ to @50,}@) and then the excess -digits of $b$ are set to zero (lines @53,for@ to @55,}@). Both ``for'' loops make use of the pointer aliases and in -fact the alias for $b$ is carried through into the second ``for'' loop to clear the excess digits. This optimization -allows the alias to stay in a machine register fairly easy between the two loops. - -\textbf{Remarks.} The use of pointer aliases is an implementation methodology first introduced in this function that will -be used considerably in other functions. Technically, a pointer alias is simply a short hand alias used to lower the -number of pointer dereferencing operations required to access data. For example, a for loop may resemble - -\begin{alltt} -for (x = 0; x < 100; x++) \{ - a->num[4]->dp[x] = 0; -\} -\end{alltt} - -This could be re-written using aliases as - -\begin{alltt} -mp_digit *tmpa; -a = a->num[4]->dp; -for (x = 0; x < 100; x++) \{ - *a++ = 0; -\} -\end{alltt} - -In this case an alias is used to access the -array of digits within an mp\_int structure directly. It may seem that a pointer alias is strictly not required -as a compiler may optimize out the redundant pointer operations. However, there are two dominant reasons to use aliases. - -The first reason is that most compilers will not effectively optimize pointer arithmetic. For example, some optimizations -may work for the Microsoft Visual C++ compiler (MSVC) and not for the GNU C Compiler (GCC). Also some optimizations may -work for GCC and not MSVC. As such it is ideal to find a common ground for as many compilers as possible. Pointer -aliases optimize the code considerably before the compiler even reads the source code which means the end compiled code -stands a better chance of being faster. - -The second reason is that pointer aliases often can make an algorithm simpler to read. Consider the first ``for'' -loop of the function mp\_copy() re-written to not use pointer aliases. - -\begin{alltt} - /* copy all the digits */ - for (n = 0; n < a->used; n++) \{ - b->dp[n] = a->dp[n]; - \} -\end{alltt} - -Whether this code is harder to read depends strongly on the individual. However, it is quantifiably slightly more -complicated as there are four variables within the statement instead of just two. - -\subsubsection{Nested Statements} -Another commonly used technique in the source routines is that certain sections of code are nested. This is used in -particular with the pointer aliases to highlight code phases. For example, a Comba multiplier (discussed in chapter six) -will typically have three different phases. First the temporaries are initialized, then the columns calculated and -finally the carries are propagated. In this example the middle column production phase will typically be nested as it -uses temporary variables and aliases the most. - -The nesting also simplies the source code as variables that are nested are only valid for their scope. As a result -the various temporary variables required do not propagate into other sections of code. - - -\subsection{Creating a Clone} -Another common operation is to make a local temporary copy of an mp\_int argument. To initialize an mp\_int -and then copy another existing mp\_int into the newly intialized mp\_int will be known as creating a clone. This is -useful within functions that need to modify an argument but do not wish to actually modify the original copy. The -mp\_init\_copy algorithm has been designed to help perform this task. - -\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_init\_copy}. \\ -\textbf{Input}. An mp\_int $a$ and $b$\\ -\textbf{Output}. $a$ is initialized to be a copy of $b$. \\ -\hline \\ -1. Init $a$. (\textit{mp\_init}) \\ -2. Copy $b$ to $a$. (\textit{mp\_copy}) \\ -3. Return the status of the copy operation. \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_init\_copy} -\end{figure} - -\textbf{Algorithm mp\_init\_copy.} -This algorithm will initialize an mp\_int variable and copy another previously initialized mp\_int variable into it. As -such this algorithm will perform two operations in one step. - -EXAM,bn_mp_init_copy.c - -This will initialize \textbf{a} and make it a verbatim copy of the contents of \textbf{b}. Note that -\textbf{a} will have its own memory allocated which means that \textbf{b} may be cleared after the call -and \textbf{a} will be left intact. - -\section{Zeroing an Integer} -Reseting an mp\_int to the default state is a common step in many algorithms. The mp\_zero algorithm will be the algorithm used to -perform this task. - -\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_zero}. \\ -\textbf{Input}. An mp\_int $a$ \\ -\textbf{Output}. Zero the contents of $a$ \\ -\hline \\ -1. $a.used \leftarrow 0$ \\ -2. $a.sign \leftarrow$ MP\_ZPOS \\ -3. for $n$ from 0 to $a.alloc - 1$ do \\ -\hspace{3mm}3.1 $a_n \leftarrow 0$ \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_zero} -\end{figure} - -\textbf{Algorithm mp\_zero.} -This algorithm simply resets a mp\_int to the default state. - -EXAM,bn_mp_zero.c - -After the function is completed, all of the digits are zeroed, the \textbf{used} count is zeroed and the -\textbf{sign} variable is set to \textbf{MP\_ZPOS}. - -\section{Sign Manipulation} -\subsection{Absolute Value} -With the mp\_int representation of an integer, calculating the absolute value is trivial. The mp\_abs algorithm will compute -the absolute value of an mp\_int. - -\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_abs}. \\ -\textbf{Input}. An mp\_int $a$ \\ -\textbf{Output}. Computes $b = \vert a \vert$ \\ -\hline \\ -1. Copy $a$ to $b$. (\textit{mp\_copy}) \\ -2. If the copy failed return(\textit{MP\_MEM}). \\ -3. $b.sign \leftarrow MP\_ZPOS$ \\ -4. Return(\textit{MP\_OKAY}) \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_abs} -\end{figure} - -\textbf{Algorithm mp\_abs.} -This algorithm computes the absolute of an mp\_int input. First it copies $a$ over $b$. This is an example of an -algorithm where the check in mp\_copy that determines if the source and destination are equal proves useful. This allows, -for instance, the developer to pass the same mp\_int as the source and destination to this function without addition -logic to handle it. - -EXAM,bn_mp_abs.c - -This fairly trivial algorithm first eliminates non--required duplications (line @27,a != b@) and then sets the -\textbf{sign} flag to \textbf{MP\_ZPOS}. - -\subsection{Integer Negation} -With the mp\_int representation of an integer, calculating the negation is also trivial. The mp\_neg algorithm will compute -the negative of an mp\_int input. - -\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_neg}. \\ -\textbf{Input}. An mp\_int $a$ \\ -\textbf{Output}. Computes $b = -a$ \\ -\hline \\ -1. Copy $a$ to $b$. (\textit{mp\_copy}) \\ -2. If the copy failed return(\textit{MP\_MEM}). \\ -3. If $a.used = 0$ then return(\textit{MP\_OKAY}). \\ -4. If $a.sign = MP\_ZPOS$ then do \\ -\hspace{3mm}4.1 $b.sign = MP\_NEG$. \\ -5. else do \\ -\hspace{3mm}5.1 $b.sign = MP\_ZPOS$. \\ -6. Return(\textit{MP\_OKAY}) \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_neg} -\end{figure} - -\textbf{Algorithm mp\_neg.} -This algorithm computes the negation of an input. First it copies $a$ over $b$. If $a$ has no used digits then -the algorithm returns immediately. Otherwise it flips the sign flag and stores the result in $b$. Note that if -$a$ had no digits then it must be positive by definition. Had step three been omitted then the algorithm would return -zero as negative. - -EXAM,bn_mp_neg.c - -Like mp\_abs() this function avoids non--required duplications (line @21,a != b@) and then sets the sign. We -have to make sure that only non--zero values get a \textbf{sign} of \textbf{MP\_NEG}. If the mp\_int is zero -than the \textbf{sign} is hard--coded to \textbf{MP\_ZPOS}. - -\section{Small Constants} -\subsection{Setting Small Constants} -Often a mp\_int must be set to a relatively small value such as $1$ or $2$. For these cases the mp\_set algorithm is useful. - -\newpage\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_set}. \\ -\textbf{Input}. An mp\_int $a$ and a digit $b$ \\ -\textbf{Output}. Make $a$ equivalent to $b$ \\ -\hline \\ -1. Zero $a$ (\textit{mp\_zero}). \\ -2. $a_0 \leftarrow b \mbox{ (mod }\beta\mbox{)}$ \\ -3. $a.used \leftarrow \left \lbrace \begin{array}{ll} - 1 & \mbox{if }a_0 > 0 \\ - 0 & \mbox{if }a_0 = 0 - \end{array} \right .$ \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_set} -\end{figure} - -\textbf{Algorithm mp\_set.} -This algorithm sets a mp\_int to a small single digit value. Step number 1 ensures that the integer is reset to the default state. The -single digit is set (\textit{modulo $\beta$}) and the \textbf{used} count is adjusted accordingly. - -EXAM,bn_mp_set.c - -First we zero (line @21,mp_zero@) the mp\_int to make sure that the other members are initialized for a -small positive constant. mp\_zero() ensures that the \textbf{sign} is positive and the \textbf{used} count -is zero. Next we set the digit and reduce it modulo $\beta$ (line @22,MP_MASK@). After this step we have to -check if the resulting digit is zero or not. If it is not then we set the \textbf{used} count to one, otherwise -to zero. - -We can quickly reduce modulo $\beta$ since it is of the form $2^k$ and a quick binary AND operation with -$2^k - 1$ will perform the same operation. - -One important limitation of this function is that it will only set one digit. The size of a digit is not fixed, meaning source that uses -this function should take that into account. Only trivially small constants can be set using this function. - -\subsection{Setting Large Constants} -To overcome the limitations of the mp\_set algorithm the mp\_set\_int algorithm is ideal. It accepts a ``long'' -data type as input and will always treat it as a 32-bit integer. - -\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_set\_int}. \\ -\textbf{Input}. An mp\_int $a$ and a ``long'' integer $b$ \\ -\textbf{Output}. Make $a$ equivalent to $b$ \\ -\hline \\ -1. Zero $a$ (\textit{mp\_zero}) \\ -2. for $n$ from 0 to 7 do \\ -\hspace{3mm}2.1 $a \leftarrow a \cdot 16$ (\textit{mp\_mul2d}) \\ -\hspace{3mm}2.2 $u \leftarrow \lfloor b / 2^{4(7 - n)} \rfloor \mbox{ (mod }16\mbox{)}$\\ -\hspace{3mm}2.3 $a_0 \leftarrow a_0 + u$ \\ -\hspace{3mm}2.4 $a.used \leftarrow a.used + 1$ \\ -3. Clamp excess used digits (\textit{mp\_clamp}) \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_set\_int} -\end{figure} - -\textbf{Algorithm mp\_set\_int.} -The algorithm performs eight iterations of a simple loop where in each iteration four bits from the source are added to the -mp\_int. Step 2.1 will multiply the current result by sixteen making room for four more bits in the less significant positions. In step 2.2 the -next four bits from the source are extracted and are added to the mp\_int. The \textbf{used} digit count is -incremented to reflect the addition. The \textbf{used} digit counter is incremented since if any of the leading digits were zero the mp\_int would have -zero digits used and the newly added four bits would be ignored. - -Excess zero digits are trimmed in steps 2.1 and 3 by using higher level algorithms mp\_mul2d and mp\_clamp. - -EXAM,bn_mp_set_int.c - -This function sets four bits of the number at a time to handle all practical \textbf{DIGIT\_BIT} sizes. The weird -addition on line @38,a->used@ ensures that the newly added in bits are added to the number of digits. While it may not -seem obvious as to why the digit counter does not grow exceedingly large it is because of the shift on line @27,mp_mul_2d@ -as well as the call to mp\_clamp() on line @40,mp_clamp@. Both functions will clamp excess leading digits which keeps -the number of used digits low. - -\section{Comparisons} -\subsection{Unsigned Comparisions} -Comparing a multiple precision integer is performed with the exact same algorithm used to compare two decimal numbers. For example, -to compare $1,234$ to $1,264$ the digits are extracted by their positions. That is we compare $1 \cdot 10^3 + 2 \cdot 10^2 + 3 \cdot 10^1 + 4 \cdot 10^0$ -to $1 \cdot 10^3 + 2 \cdot 10^2 + 6 \cdot 10^1 + 4 \cdot 10^0$ by comparing single digits at a time starting with the highest magnitude -positions. If any leading digit of one integer is greater than a digit in the same position of another integer then obviously it must be greater. - -The first comparision routine that will be developed is the unsigned magnitude compare which will perform a comparison based on the digits of two -mp\_int variables alone. It will ignore the sign of the two inputs. Such a function is useful when an absolute comparison is required or if the -signs are known to agree in advance. - -To facilitate working with the results of the comparison functions three constants are required. - -\begin{figure}[here] -\begin{center} -\begin{tabular}{|r|l|} -\hline \textbf{Constant} & \textbf{Meaning} \\ -\hline \textbf{MP\_GT} & Greater Than \\ -\hline \textbf{MP\_EQ} & Equal To \\ -\hline \textbf{MP\_LT} & Less Than \\ -\hline -\end{tabular} -\end{center} -\caption{Comparison Return Codes} -\end{figure} - -\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_cmp\_mag}. \\ -\textbf{Input}. Two mp\_ints $a$ and $b$. \\ -\textbf{Output}. Unsigned comparison results ($a$ to the left of $b$). \\ -\hline \\ -1. If $a.used > b.used$ then return(\textit{MP\_GT}) \\ -2. If $a.used < b.used$ then return(\textit{MP\_LT}) \\ -3. for n from $a.used - 1$ to 0 do \\ -\hspace{+3mm}3.1 if $a_n > b_n$ then return(\textit{MP\_GT}) \\ -\hspace{+3mm}3.2 if $a_n < b_n$ then return(\textit{MP\_LT}) \\ -4. Return(\textit{MP\_EQ}) \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_cmp\_mag} -\end{figure} - -\textbf{Algorithm mp\_cmp\_mag.} -By saying ``$a$ to the left of $b$'' it is meant that the comparison is with respect to $a$, that is if $a$ is greater than $b$ it will return -\textbf{MP\_GT} and similar with respect to when $a = b$ and $a < b$. The first two steps compare the number of digits used in both $a$ and $b$. -Obviously if the digit counts differ there would be an imaginary zero digit in the smaller number where the leading digit of the larger number is. -If both have the same number of digits than the actual digits themselves must be compared starting at the leading digit. - -By step three both inputs must have the same number of digits so its safe to start from either $a.used - 1$ or $b.used - 1$ and count down to -the zero'th digit. If after all of the digits have been compared, no difference is found, the algorithm returns \textbf{MP\_EQ}. - -EXAM,bn_mp_cmp_mag.c - -The two if statements (lines @24,if@ and @28,if@) compare the number of digits in the two inputs. These two are -performed before all of the digits are compared since it is a very cheap test to perform and can potentially save -considerable time. The implementation given is also not valid without those two statements. $b.alloc$ may be -smaller than $a.used$, meaning that undefined values will be read from $b$ past the end of the array of digits. - - - -\subsection{Signed Comparisons} -Comparing with sign considerations is also fairly critical in several routines (\textit{division for example}). Based on an unsigned magnitude -comparison a trivial signed comparison algorithm can be written. - -\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_cmp}. \\ -\textbf{Input}. Two mp\_ints $a$ and $b$ \\ -\textbf{Output}. Signed Comparison Results ($a$ to the left of $b$) \\ -\hline \\ -1. if $a.sign = MP\_NEG$ and $b.sign = MP\_ZPOS$ then return(\textit{MP\_LT}) \\ -2. if $a.sign = MP\_ZPOS$ and $b.sign = MP\_NEG$ then return(\textit{MP\_GT}) \\ -3. if $a.sign = MP\_NEG$ then \\ -\hspace{+3mm}3.1 Return the unsigned comparison of $b$ and $a$ (\textit{mp\_cmp\_mag}) \\ -4 Otherwise \\ -\hspace{+3mm}4.1 Return the unsigned comparison of $a$ and $b$ \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_cmp} -\end{figure} - -\textbf{Algorithm mp\_cmp.} -The first two steps compare the signs of the two inputs. If the signs do not agree then it can return right away with the appropriate -comparison code. When the signs are equal the digits of the inputs must be compared to determine the correct result. In step -three the unsigned comparision flips the order of the arguments since they are both negative. For instance, if $-a > -b$ then -$\vert a \vert < \vert b \vert$. Step number four will compare the two when they are both positive. - -EXAM,bn_mp_cmp.c - -The two if statements (lines @22,if@ and @26,if@) perform the initial sign comparison. If the signs are not the equal then which ever -has the positive sign is larger. The inputs are compared (line @30,if@) based on magnitudes. If the signs were both -negative then the unsigned comparison is performed in the opposite direction (line @31,mp_cmp_mag@). Otherwise, the signs are assumed to -be both positive and a forward direction unsigned comparison is performed. - -\section*{Exercises} -\begin{tabular}{cl} -$\left [ 2 \right ]$ & Modify algorithm mp\_set\_int to accept as input a variable length array of bits. \\ - & \\ -$\left [ 3 \right ]$ & Give the probability that algorithm mp\_cmp\_mag will have to compare $k$ digits \\ - & of two random digits (of equal magnitude) before a difference is found. \\ - & \\ -$\left [ 1 \right ]$ & Suggest a simple method to speed up the implementation of mp\_cmp\_mag based \\ - & on the observations made in the previous problem. \\ - & -\end{tabular} - -\chapter{Basic Arithmetic} -\section{Introduction} -At this point algorithms for initialization, clearing, zeroing, copying, comparing and setting small constants have been -established. The next logical set of algorithms to develop are addition, subtraction and digit shifting algorithms. These -algorithms make use of the lower level algorithms and are the cruicial building block for the multiplication algorithms. It is very important -that these algorithms are highly optimized. On their own they are simple $O(n)$ algorithms but they can be called from higher level algorithms -which easily places them at $O(n^2)$ or even $O(n^3)$ work levels. - -MARK,SHIFTS -All of the algorithms within this chapter make use of the logical bit shift operations denoted by $<<$ and $>>$ for left and right -logical shifts respectively. A logical shift is analogous to sliding the decimal point of radix-10 representations. For example, the real -number $0.9345$ is equivalent to $93.45\%$ which is found by sliding the the decimal two places to the right (\textit{multiplying by $\beta^2 = 10^2$}). -Algebraically a binary logical shift is equivalent to a division or multiplication by a power of two. -For example, $a << k = a \cdot 2^k$ while $a >> k = \lfloor a/2^k \rfloor$. - -One significant difference between a logical shift and the way decimals are shifted is that digits below the zero'th position are removed -from the number. For example, consider $1101_2 >> 1$ using decimal notation this would produce $110.1_2$. However, with a logical shift the -result is $110_2$. - -\section{Addition and Subtraction} -In common twos complement fixed precision arithmetic negative numbers are easily represented by subtraction from the modulus. For example, with 32-bit integers -$a - b\mbox{ (mod }2^{32}\mbox{)}$ is the same as $a + (2^{32} - b) \mbox{ (mod }2^{32}\mbox{)}$ since $2^{32} \equiv 0 \mbox{ (mod }2^{32}\mbox{)}$. -As a result subtraction can be performed with a trivial series of logical operations and an addition. - -However, in multiple precision arithmetic negative numbers are not represented in the same way. Instead a sign flag is used to keep track of the -sign of the integer. As a result signed addition and subtraction are actually implemented as conditional usage of lower level addition or -subtraction algorithms with the sign fixed up appropriately. - -The lower level algorithms will add or subtract integers without regard to the sign flag. That is they will add or subtract the magnitude of -the integers respectively. - -\subsection{Low Level Addition} -An unsigned addition of multiple precision integers is performed with the same long-hand algorithm used to add decimal numbers. That is to add the -trailing digits first and propagate the resulting carry upwards. Since this is a lower level algorithm the name will have a ``s\_'' prefix. -Historically that convention stems from the MPI library where ``s\_'' stood for static functions that were hidden from the developer entirely. - -\newpage -\begin{figure}[!here] -\begin{center} -\begin{small} -\begin{tabular}{l} -\hline Algorithm \textbf{s\_mp\_add}. \\ -\textbf{Input}. Two mp\_ints $a$ and $b$ \\ -\textbf{Output}. The unsigned addition $c = \vert a \vert + \vert b \vert$. \\ -\hline \\ -1. if $a.used > b.used$ then \\ -\hspace{+3mm}1.1 $min \leftarrow b.used$ \\ -\hspace{+3mm}1.2 $max \leftarrow a.used$ \\ -\hspace{+3mm}1.3 $x \leftarrow a$ \\ -2. else \\ -\hspace{+3mm}2.1 $min \leftarrow a.used$ \\ -\hspace{+3mm}2.2 $max \leftarrow b.used$ \\ -\hspace{+3mm}2.3 $x \leftarrow b$ \\ -3. If $c.alloc < max + 1$ then grow $c$ to hold at least $max + 1$ digits (\textit{mp\_grow}) \\ -4. $oldused \leftarrow c.used$ \\ -5. $c.used \leftarrow max + 1$ \\ -6. $u \leftarrow 0$ \\ -7. for $n$ from $0$ to $min - 1$ do \\ -\hspace{+3mm}7.1 $c_n \leftarrow a_n + b_n + u$ \\ -\hspace{+3mm}7.2 $u \leftarrow c_n >> lg(\beta)$ \\ -\hspace{+3mm}7.3 $c_n \leftarrow c_n \mbox{ (mod }\beta\mbox{)}$ \\ -8. if $min \ne max$ then do \\ -\hspace{+3mm}8.1 for $n$ from $min$ to $max - 1$ do \\ -\hspace{+6mm}8.1.1 $c_n \leftarrow x_n + u$ \\ -\hspace{+6mm}8.1.2 $u \leftarrow c_n >> lg(\beta)$ \\ -\hspace{+6mm}8.1.3 $c_n \leftarrow c_n \mbox{ (mod }\beta\mbox{)}$ \\ -9. $c_{max} \leftarrow u$ \\ -10. if $olduse > max$ then \\ -\hspace{+3mm}10.1 for $n$ from $max + 1$ to $oldused - 1$ do \\ -\hspace{+6mm}10.1.1 $c_n \leftarrow 0$ \\ -11. Clamp excess digits in $c$. (\textit{mp\_clamp}) \\ -12. Return(\textit{MP\_OKAY}) \\ -\hline -\end{tabular} -\end{small} -\end{center} -\caption{Algorithm s\_mp\_add} -\end{figure} - -\textbf{Algorithm s\_mp\_add.} -This algorithm is loosely based on algorithm 14.7 of HAC \cite[pp. 594]{HAC} but has been extended to allow the inputs to have different magnitudes. -Coincidentally the description of algorithm A in Knuth \cite[pp. 266]{TAOCPV2} shares the same deficiency as the algorithm from \cite{HAC}. Even the -MIX pseudo machine code presented by Knuth \cite[pp. 266-267]{TAOCPV2} is incapable of handling inputs which are of different magnitudes. - -The first thing that has to be accomplished is to sort out which of the two inputs is the largest. The addition logic -will simply add all of the smallest input to the largest input and store that first part of the result in the -destination. Then it will apply a simpler addition loop to excess digits of the larger input. - -The first two steps will handle sorting the inputs such that $min$ and $max$ hold the digit counts of the two -inputs. The variable $x$ will be an mp\_int alias for the largest input or the second input $b$ if they have the -same number of digits. After the inputs are sorted the destination $c$ is grown as required to accomodate the sum -of the two inputs. The original \textbf{used} count of $c$ is copied and set to the new used count. - -At this point the first addition loop will go through as many digit positions that both inputs have. The carry -variable $\mu$ is set to zero outside the loop. Inside the loop an ``addition'' step requires three statements to produce -one digit of the summand. First -two digits from $a$ and $b$ are added together along with the carry $\mu$. The carry of this step is extracted and stored -in $\mu$ and finally the digit of the result $c_n$ is truncated within the range $0 \le c_n < \beta$. - -Now all of the digit positions that both inputs have in common have been exhausted. If $min \ne max$ then $x$ is an alias -for one of the inputs that has more digits. A simplified addition loop is then used to essentially copy the remaining digits -and the carry to the destination. - -The final carry is stored in $c_{max}$ and digits above $max$ upto $oldused$ are zeroed which completes the addition. - - -EXAM,bn_s_mp_add.c - -We first sort (lines @27,if@ to @35,}@) the inputs based on magnitude and determine the $min$ and $max$ variables. -Note that $x$ is a pointer to an mp\_int assigned to the largest input, in effect it is a local alias. Next we -grow the destination (@37,init@ to @42,}@) ensure that it can accomodate the result of the addition. - -Similar to the implementation of mp\_copy this function uses the braced code and local aliases coding style. The three aliases that are on -lines @56,tmpa@, @59,tmpb@ and @62,tmpc@ represent the two inputs and destination variables respectively. These aliases are used to ensure the -compiler does not have to dereference $a$, $b$ or $c$ (respectively) to access the digits of the respective mp\_int. - -The initial carry $u$ will be cleared (line @65,u = 0@), note that $u$ is of type mp\_digit which ensures type -compatibility within the implementation. The initial addition (line @66,for@ to @75,}@) adds digits from -both inputs until the smallest input runs out of digits. Similarly the conditional addition loop -(line @81,for@ to @90,}@) adds the remaining digits from the larger of the two inputs. The addition is finished -with the final carry being stored in $tmpc$ (line @94,tmpc++@). Note the ``++'' operator within the same expression. -After line @94,tmpc++@, $tmpc$ will point to the $c.used$'th digit of the mp\_int $c$. This is useful -for the next loop (line @97,for@ to @99,}@) which set any old upper digits to zero. - -\subsection{Low Level Subtraction} -The low level unsigned subtraction algorithm is very similar to the low level unsigned addition algorithm. The principle difference is that the -unsigned subtraction algorithm requires the result to be positive. That is when computing $a - b$ the condition $\vert a \vert \ge \vert b\vert$ must -be met for this algorithm to function properly. Keep in mind this low level algorithm is not meant to be used in higher level algorithms directly. -This algorithm as will be shown can be used to create functional signed addition and subtraction algorithms. - -MARK,GAMMA - -For this algorithm a new variable is required to make the description simpler. Recall from section 1.3.1 that a mp\_digit must be able to represent -the range $0 \le x < 2\beta$ for the algorithms to work correctly. However, it is allowable that a mp\_digit represent a larger range of values. For -this algorithm we will assume that the variable $\gamma$ represents the number of bits available in a -mp\_digit (\textit{this implies $2^{\gamma} > \beta$}). - -For example, the default for LibTomMath is to use a ``unsigned long'' for the mp\_digit ``type'' while $\beta = 2^{28}$. In ISO C an ``unsigned long'' -data type must be able to represent $0 \le x < 2^{32}$ meaning that in this case $\gamma \ge 32$. - -\newpage\begin{figure}[!here] -\begin{center} -\begin{small} -\begin{tabular}{l} -\hline Algorithm \textbf{s\_mp\_sub}. \\ -\textbf{Input}. Two mp\_ints $a$ and $b$ ($\vert a \vert \ge \vert b \vert$) \\ -\textbf{Output}. The unsigned subtraction $c = \vert a \vert - \vert b \vert$. \\ -\hline \\ -1. $min \leftarrow b.used$ \\ -2. $max \leftarrow a.used$ \\ -3. If $c.alloc < max$ then grow $c$ to hold at least $max$ digits. (\textit{mp\_grow}) \\ -4. $oldused \leftarrow c.used$ \\ -5. $c.used \leftarrow max$ \\ -6. $u \leftarrow 0$ \\ -7. for $n$ from $0$ to $min - 1$ do \\ -\hspace{3mm}7.1 $c_n \leftarrow a_n - b_n - u$ \\ -\hspace{3mm}7.2 $u \leftarrow c_n >> (\gamma - 1)$ \\ -\hspace{3mm}7.3 $c_n \leftarrow c_n \mbox{ (mod }\beta\mbox{)}$ \\ -8. if $min < max$ then do \\ -\hspace{3mm}8.1 for $n$ from $min$ to $max - 1$ do \\ -\hspace{6mm}8.1.1 $c_n \leftarrow a_n - u$ \\ -\hspace{6mm}8.1.2 $u \leftarrow c_n >> (\gamma - 1)$ \\ -\hspace{6mm}8.1.3 $c_n \leftarrow c_n \mbox{ (mod }\beta\mbox{)}$ \\ -9. if $oldused > max$ then do \\ -\hspace{3mm}9.1 for $n$ from $max$ to $oldused - 1$ do \\ -\hspace{6mm}9.1.1 $c_n \leftarrow 0$ \\ -10. Clamp excess digits of $c$. (\textit{mp\_clamp}). \\ -11. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{small} -\end{center} -\caption{Algorithm s\_mp\_sub} -\end{figure} - -\textbf{Algorithm s\_mp\_sub.} -This algorithm performs the unsigned subtraction of two mp\_int variables under the restriction that the result must be positive. That is when -passing variables $a$ and $b$ the condition that $\vert a \vert \ge \vert b \vert$ must be met for the algorithm to function correctly. This -algorithm is loosely based on algorithm 14.9 \cite[pp. 595]{HAC} and is similar to algorithm S in \cite[pp. 267]{TAOCPV2} as well. As was the case -of the algorithm s\_mp\_add both other references lack discussion concerning various practical details such as when the inputs differ in magnitude. - -The initial sorting of the inputs is trivial in this algorithm since $a$ is guaranteed to have at least the same magnitude of $b$. Steps 1 and 2 -set the $min$ and $max$ variables. Unlike the addition routine there is guaranteed to be no carry which means that the final result can be at -most $max$ digits in length as opposed to $max + 1$. Similar to the addition algorithm the \textbf{used} count of $c$ is copied locally and -set to the maximal count for the operation. - -The subtraction loop that begins on step seven is essentially the same as the addition loop of algorithm s\_mp\_add except single precision -subtraction is used instead. Note the use of the $\gamma$ variable to extract the carry (\textit{also known as the borrow}) within the subtraction -loops. Under the assumption that two's complement single precision arithmetic is used this will successfully extract the desired carry. - -For example, consider subtracting $0101_2$ from $0100_2$ where $\gamma = 4$ and $\beta = 2$. The least significant bit will force a carry upwards to -the third bit which will be set to zero after the borrow. After the very first bit has been subtracted $4 - 1 \equiv 0011_2$ will remain, When the -third bit of $0101_2$ is subtracted from the result it will cause another carry. In this case though the carry will be forced to propagate all the -way to the most significant bit. - -Recall that $\beta < 2^{\gamma}$. This means that if a carry does occur just before the $lg(\beta)$'th bit it will propagate all the way to the most -significant bit. Thus, the high order bits of the mp\_digit that are not part of the actual digit will either be all zero, or all one. All that -is needed is a single zero or one bit for the carry. Therefore a single logical shift right by $\gamma - 1$ positions is sufficient to extract the -carry. This method of carry extraction may seem awkward but the reason for it becomes apparent when the implementation is discussed. - -If $b$ has a smaller magnitude than $a$ then step 9 will force the carry and copy operation to propagate through the larger input $a$ into $c$. Step -10 will ensure that any leading digits of $c$ above the $max$'th position are zeroed. - -EXAM,bn_s_mp_sub.c - -Like low level addition we ``sort'' the inputs. Except in this case the sorting is hardcoded -(lines @24,min@ and @25,max@). In reality the $min$ and $max$ variables are only aliases and are only -used to make the source code easier to read. Again the pointer alias optimization is used -within this algorithm. The aliases $tmpa$, $tmpb$ and $tmpc$ are initialized -(lines @42,tmpa@, @43,tmpb@ and @44,tmpc@) for $a$, $b$ and $c$ respectively. - -The first subtraction loop (lines @47,u = 0@ through @61,}@) subtract digits from both inputs until the smaller of -the two inputs has been exhausted. As remarked earlier there is an implementation reason for using the ``awkward'' -method of extracting the carry (line @57, >>@). The traditional method for extracting the carry would be to shift -by $lg(\beta)$ positions and logically AND the least significant bit. The AND operation is required because all of -the bits above the $\lg(\beta)$'th bit will be set to one after a carry occurs from subtraction. This carry -extraction requires two relatively cheap operations to extract the carry. The other method is to simply shift the -most significant bit to the least significant bit thus extracting the carry with a single cheap operation. This -optimization only works on twos compliment machines which is a safe assumption to make. - -If $a$ has a larger magnitude than $b$ an additional loop (lines @64,for@ through @73,}@) is required to propagate -the carry through $a$ and copy the result to $c$. - -\subsection{High Level Addition} -Now that both lower level addition and subtraction algorithms have been established an effective high level signed addition algorithm can be -established. This high level addition algorithm will be what other algorithms and developers will use to perform addition of mp\_int data -types. - -Recall from section 5.2 that an mp\_int represents an integer with an unsigned mantissa (\textit{the array of digits}) and a \textbf{sign} -flag. A high level addition is actually performed as a series of eight separate cases which can be optimized down to three unique cases. - -\begin{figure}[!here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_add}. \\ -\textbf{Input}. Two mp\_ints $a$ and $b$ \\ -\textbf{Output}. The signed addition $c = a + b$. \\ -\hline \\ -1. if $a.sign = b.sign$ then do \\ -\hspace{3mm}1.1 $c.sign \leftarrow a.sign$ \\ -\hspace{3mm}1.2 $c \leftarrow \vert a \vert + \vert b \vert$ (\textit{s\_mp\_add})\\ -2. else do \\ -\hspace{3mm}2.1 if $\vert a \vert < \vert b \vert$ then do (\textit{mp\_cmp\_mag}) \\ -\hspace{6mm}2.1.1 $c.sign \leftarrow b.sign$ \\ -\hspace{6mm}2.1.2 $c \leftarrow \vert b \vert - \vert a \vert$ (\textit{s\_mp\_sub}) \\ -\hspace{3mm}2.2 else do \\ -\hspace{6mm}2.2.1 $c.sign \leftarrow a.sign$ \\ -\hspace{6mm}2.2.2 $c \leftarrow \vert a \vert - \vert b \vert$ \\ -3. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_add} -\end{figure} - -\textbf{Algorithm mp\_add.} -This algorithm performs the signed addition of two mp\_int variables. There is no reference algorithm to draw upon from -either \cite{TAOCPV2} or \cite{HAC} since they both only provide unsigned operations. The algorithm is fairly -straightforward but restricted since subtraction can only produce positive results. - -\begin{figure}[here] -\begin{small} -\begin{center} -\begin{tabular}{|c|c|c|c|c|} -\hline \textbf{Sign of $a$} & \textbf{Sign of $b$} & \textbf{$\vert a \vert > \vert b \vert $} & \textbf{Unsigned Operation} & \textbf{Result Sign Flag} \\ -\hline $+$ & $+$ & Yes & $c = a + b$ & $a.sign$ \\ -\hline $+$ & $+$ & No & $c = a + b$ & $a.sign$ \\ -\hline $-$ & $-$ & Yes & $c = a + b$ & $a.sign$ \\ -\hline $-$ & $-$ & No & $c = a + b$ & $a.sign$ \\ -\hline &&&&\\ - -\hline $+$ & $-$ & No & $c = b - a$ & $b.sign$ \\ -\hline $-$ & $+$ & No & $c = b - a$ & $b.sign$ \\ - -\hline &&&&\\ - -\hline $+$ & $-$ & Yes & $c = a - b$ & $a.sign$ \\ -\hline $-$ & $+$ & Yes & $c = a - b$ & $a.sign$ \\ - -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Addition Guide Chart} -\label{fig:AddChart} -\end{figure} - -Figure~\ref{fig:AddChart} lists all of the eight possible input combinations and is sorted to show that only three -specific cases need to be handled. The return code of the unsigned operations at step 1.2, 2.1.2 and 2.2.2 are -forwarded to step three to check for errors. This simplifies the description of the algorithm considerably and best -follows how the implementation actually was achieved. - -Also note how the \textbf{sign} is set before the unsigned addition or subtraction is performed. Recall from the descriptions of algorithms -s\_mp\_add and s\_mp\_sub that the mp\_clamp function is used at the end to trim excess digits. The mp\_clamp algorithm will set the \textbf{sign} -to \textbf{MP\_ZPOS} when the \textbf{used} digit count reaches zero. - -For example, consider performing $-a + a$ with algorithm mp\_add. By the description of the algorithm the sign is set to \textbf{MP\_NEG} which would -produce a result of $-0$. However, since the sign is set first then the unsigned addition is performed the subsequent usage of algorithm mp\_clamp -within algorithm s\_mp\_add will force $-0$ to become $0$. - -EXAM,bn_mp_add.c - -The source code follows the algorithm fairly closely. The most notable new source code addition is the usage of the $res$ integer variable which -is used to pass result of the unsigned operations forward. Unlike in the algorithm, the variable $res$ is merely returned as is without -explicitly checking it and returning the constant \textbf{MP\_OKAY}. The observation is this algorithm will succeed or fail only if the lower -level functions do so. Returning their return code is sufficient. - -\subsection{High Level Subtraction} -The high level signed subtraction algorithm is essentially the same as the high level signed addition algorithm. - -\newpage\begin{figure}[!here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_sub}. \\ -\textbf{Input}. Two mp\_ints $a$ and $b$ \\ -\textbf{Output}. The signed subtraction $c = a - b$. \\ -\hline \\ -1. if $a.sign \ne b.sign$ then do \\ -\hspace{3mm}1.1 $c.sign \leftarrow a.sign$ \\ -\hspace{3mm}1.2 $c \leftarrow \vert a \vert + \vert b \vert$ (\textit{s\_mp\_add}) \\ -2. else do \\ -\hspace{3mm}2.1 if $\vert a \vert \ge \vert b \vert$ then do (\textit{mp\_cmp\_mag}) \\ -\hspace{6mm}2.1.1 $c.sign \leftarrow a.sign$ \\ -\hspace{6mm}2.1.2 $c \leftarrow \vert a \vert - \vert b \vert$ (\textit{s\_mp\_sub}) \\ -\hspace{3mm}2.2 else do \\ -\hspace{6mm}2.2.1 $c.sign \leftarrow \left \lbrace \begin{array}{ll} - MP\_ZPOS & \mbox{if }a.sign = MP\_NEG \\ - MP\_NEG & \mbox{otherwise} \\ - \end{array} \right .$ \\ -\hspace{6mm}2.2.2 $c \leftarrow \vert b \vert - \vert a \vert$ \\ -3. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_sub} -\end{figure} - -\textbf{Algorithm mp\_sub.} -This algorithm performs the signed subtraction of two inputs. Similar to algorithm mp\_add there is no reference in either \cite{TAOCPV2} or -\cite{HAC}. Also this algorithm is restricted by algorithm s\_mp\_sub. Chart \ref{fig:SubChart} lists the eight possible inputs and -the operations required. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{|c|c|c|c|c|} -\hline \textbf{Sign of $a$} & \textbf{Sign of $b$} & \textbf{$\vert a \vert \ge \vert b \vert $} & \textbf{Unsigned Operation} & \textbf{Result Sign Flag} \\ -\hline $+$ & $-$ & Yes & $c = a + b$ & $a.sign$ \\ -\hline $+$ & $-$ & No & $c = a + b$ & $a.sign$ \\ -\hline $-$ & $+$ & Yes & $c = a + b$ & $a.sign$ \\ -\hline $-$ & $+$ & No & $c = a + b$ & $a.sign$ \\ -\hline &&&& \\ -\hline $+$ & $+$ & Yes & $c = a - b$ & $a.sign$ \\ -\hline $-$ & $-$ & Yes & $c = a - b$ & $a.sign$ \\ -\hline &&&& \\ -\hline $+$ & $+$ & No & $c = b - a$ & $\mbox{opposite of }a.sign$ \\ -\hline $-$ & $-$ & No & $c = b - a$ & $\mbox{opposite of }a.sign$ \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Subtraction Guide Chart} -\label{fig:SubChart} -\end{figure} - -Similar to the case of algorithm mp\_add the \textbf{sign} is set first before the unsigned addition or subtraction. That is to prevent the -algorithm from producing $-a - -a = -0$ as a result. - -EXAM,bn_mp_sub.c - -Much like the implementation of algorithm mp\_add the variable $res$ is used to catch the return code of the unsigned addition or subtraction operations -and forward it to the end of the function. On line @38, != MP_LT@ the ``not equal to'' \textbf{MP\_LT} expression is used to emulate a -``greater than or equal to'' comparison. - -\section{Bit and Digit Shifting} -MARK,POLY -It is quite common to think of a multiple precision integer as a polynomial in $x$, that is $y = f(\beta)$ where $f(x) = \sum_{i=0}^{n-1} a_i x^i$. -This notation arises within discussion of Montgomery and Diminished Radix Reduction as well as Karatsuba multiplication and squaring. - -In order to facilitate operations on polynomials in $x$ as above a series of simple ``digit'' algorithms have to be established. That is to shift -the digits left or right as well to shift individual bits of the digits left and right. It is important to note that not all ``shift'' operations -are on radix-$\beta$ digits. - -\subsection{Multiplication by Two} - -In a binary system where the radix is a power of two multiplication by two not only arises often in other algorithms it is a fairly efficient -operation to perform. A single precision logical shift left is sufficient to multiply a single digit by two. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_mul\_2}. \\ -\textbf{Input}. One mp\_int $a$ \\ -\textbf{Output}. $b = 2a$. \\ -\hline \\ -1. If $b.alloc < a.used + 1$ then grow $b$ to hold $a.used + 1$ digits. (\textit{mp\_grow}) \\ -2. $oldused \leftarrow b.used$ \\ -3. $b.used \leftarrow a.used$ \\ -4. $r \leftarrow 0$ \\ -5. for $n$ from 0 to $a.used - 1$ do \\ -\hspace{3mm}5.1 $rr \leftarrow a_n >> (lg(\beta) - 1)$ \\ -\hspace{3mm}5.2 $b_n \leftarrow (a_n << 1) + r \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{3mm}5.3 $r \leftarrow rr$ \\ -6. If $r \ne 0$ then do \\ -\hspace{3mm}6.1 $b_{n + 1} \leftarrow r$ \\ -\hspace{3mm}6.2 $b.used \leftarrow b.used + 1$ \\ -7. If $b.used < oldused - 1$ then do \\ -\hspace{3mm}7.1 for $n$ from $b.used$ to $oldused - 1$ do \\ -\hspace{6mm}7.1.1 $b_n \leftarrow 0$ \\ -8. $b.sign \leftarrow a.sign$ \\ -9. Return(\textit{MP\_OKAY}).\\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_mul\_2} -\end{figure} - -\textbf{Algorithm mp\_mul\_2.} -This algorithm will quickly multiply a mp\_int by two provided $\beta$ is a power of two. Neither \cite{TAOCPV2} nor \cite{HAC} describe such -an algorithm despite the fact it arises often in other algorithms. The algorithm is setup much like the lower level algorithm s\_mp\_add since -it is for all intents and purposes equivalent to the operation $b = \vert a \vert + \vert a \vert$. - -Step 1 and 2 grow the input as required to accomodate the maximum number of \textbf{used} digits in the result. The initial \textbf{used} count -is set to $a.used$ at step 4. Only if there is a final carry will the \textbf{used} count require adjustment. - -Step 6 is an optimization implementation of the addition loop for this specific case. That is since the two values being added together -are the same there is no need to perform two reads from the digits of $a$. Step 6.1 performs a single precision shift on the current digit $a_n$ to -obtain what will be the carry for the next iteration. Step 6.2 calculates the $n$'th digit of the result as single precision shift of $a_n$ plus -the previous carry. Recall from ~SHIFTS~ that $a_n << 1$ is equivalent to $a_n \cdot 2$. An iteration of the addition loop is finished with -forwarding the carry to the next iteration. - -Step 7 takes care of any final carry by setting the $a.used$'th digit of the result to the carry and augmenting the \textbf{used} count of $b$. -Step 8 clears any leading digits of $b$ in case it originally had a larger magnitude than $a$. - -EXAM,bn_mp_mul_2.c - -This implementation is essentially an optimized implementation of s\_mp\_add for the case of doubling an input. The only noteworthy difference -is the use of the logical shift operator on line @52,<<@ to perform a single precision doubling. - -\subsection{Division by Two} -A division by two can just as easily be accomplished with a logical shift right as multiplication by two can be with a logical shift left. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_div\_2}. \\ -\textbf{Input}. One mp\_int $a$ \\ -\textbf{Output}. $b = a/2$. \\ -\hline \\ -1. If $b.alloc < a.used$ then grow $b$ to hold $a.used$ digits. (\textit{mp\_grow}) \\ -2. If the reallocation failed return(\textit{MP\_MEM}). \\ -3. $oldused \leftarrow b.used$ \\ -4. $b.used \leftarrow a.used$ \\ -5. $r \leftarrow 0$ \\ -6. for $n$ from $b.used - 1$ to $0$ do \\ -\hspace{3mm}6.1 $rr \leftarrow a_n \mbox{ (mod }2\mbox{)}$\\ -\hspace{3mm}6.2 $b_n \leftarrow (a_n >> 1) + (r << (lg(\beta) - 1)) \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{3mm}6.3 $r \leftarrow rr$ \\ -7. If $b.used < oldused - 1$ then do \\ -\hspace{3mm}7.1 for $n$ from $b.used$ to $oldused - 1$ do \\ -\hspace{6mm}7.1.1 $b_n \leftarrow 0$ \\ -8. $b.sign \leftarrow a.sign$ \\ -9. Clamp excess digits of $b$. (\textit{mp\_clamp}) \\ -10. Return(\textit{MP\_OKAY}).\\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_div\_2} -\end{figure} - -\textbf{Algorithm mp\_div\_2.} -This algorithm will divide an mp\_int by two using logical shifts to the right. Like mp\_mul\_2 it uses a modified low level addition -core as the basis of the algorithm. Unlike mp\_mul\_2 the shift operations work from the leading digit to the trailing digit. The algorithm -could be written to work from the trailing digit to the leading digit however, it would have to stop one short of $a.used - 1$ digits to prevent -reading past the end of the array of digits. - -Essentially the loop at step 6 is similar to that of mp\_mul\_2 except the logical shifts go in the opposite direction and the carry is at the -least significant bit not the most significant bit. - -EXAM,bn_mp_div_2.c - -\section{Polynomial Basis Operations} -Recall from ~POLY~ that any integer can be represented as a polynomial in $x$ as $y = f(\beta)$. Such a representation is also known as -the polynomial basis \cite[pp. 48]{ROSE}. Given such a notation a multiplication or division by $x$ amounts to shifting whole digits a single -place. The need for such operations arises in several other higher level algorithms such as Barrett and Montgomery reduction, integer -division and Karatsuba multiplication. - -Converting from an array of digits to polynomial basis is very simple. Consider the integer $y \equiv (a_2, a_1, a_0)_{\beta}$ and recall that -$y = \sum_{i=0}^{2} a_i \beta^i$. Simply replace $\beta$ with $x$ and the expression is in polynomial basis. For example, $f(x) = 8x + 9$ is the -polynomial basis representation for $89$ using radix ten. That is, $f(10) = 8(10) + 9 = 89$. - -\subsection{Multiplication by $x$} - -Given a polynomial in $x$ such as $f(x) = a_n x^n + a_{n-1} x^{n-1} + ... + a_0$ multiplying by $x$ amounts to shifting the coefficients up one -degree. In this case $f(x) \cdot x = a_n x^{n+1} + a_{n-1} x^n + ... + a_0 x$. From a scalar basis point of view multiplying by $x$ is equivalent to -multiplying by the integer $\beta$. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_lshd}. \\ -\textbf{Input}. One mp\_int $a$ and an integer $b$ \\ -\textbf{Output}. $a \leftarrow a \cdot \beta^b$ (equivalent to multiplication by $x^b$). \\ -\hline \\ -1. If $b \le 0$ then return(\textit{MP\_OKAY}). \\ -2. If $a.alloc < a.used + b$ then grow $a$ to at least $a.used + b$ digits. (\textit{mp\_grow}). \\ -3. If the reallocation failed return(\textit{MP\_MEM}). \\ -4. $a.used \leftarrow a.used + b$ \\ -5. $i \leftarrow a.used - 1$ \\ -6. $j \leftarrow a.used - 1 - b$ \\ -7. for $n$ from $a.used - 1$ to $b$ do \\ -\hspace{3mm}7.1 $a_{i} \leftarrow a_{j}$ \\ -\hspace{3mm}7.2 $i \leftarrow i - 1$ \\ -\hspace{3mm}7.3 $j \leftarrow j - 1$ \\ -8. for $n$ from 0 to $b - 1$ do \\ -\hspace{3mm}8.1 $a_n \leftarrow 0$ \\ -9. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_lshd} -\end{figure} - -\textbf{Algorithm mp\_lshd.} -This algorithm multiplies an mp\_int by the $b$'th power of $x$. This is equivalent to multiplying by $\beta^b$. The algorithm differs -from the other algorithms presented so far as it performs the operation in place instead storing the result in a separate location. The -motivation behind this change is due to the way this function is typically used. Algorithms such as mp\_add store the result in an optionally -different third mp\_int because the original inputs are often still required. Algorithm mp\_lshd (\textit{and similarly algorithm mp\_rshd}) is -typically used on values where the original value is no longer required. The algorithm will return success immediately if -$b \le 0$ since the rest of algorithm is only valid when $b > 0$. - -First the destination $a$ is grown as required to accomodate the result. The counters $i$ and $j$ are used to form a \textit{sliding window} over -the digits of $a$ of length $b$. The head of the sliding window is at $i$ (\textit{the leading digit}) and the tail at $j$ (\textit{the trailing digit}). -The loop on step 7 copies the digit from the tail to the head. In each iteration the window is moved down one digit. The last loop on -step 8 sets the lower $b$ digits to zero. - -\newpage -FIGU,sliding_window,Sliding Window Movement - -EXAM,bn_mp_lshd.c - -The if statement (line @24,if@) ensures that the $b$ variable is greater than zero since we do not interpret negative -shift counts properly. The \textbf{used} count is incremented by $b$ before the copy loop begins. This elminates -the need for an additional variable in the for loop. The variable $top$ (line @42,top@) is an alias -for the leading digit while $bottom$ (line @45,bottom@) is an alias for the trailing edge. The aliases form a -window of exactly $b$ digits over the input. - -\subsection{Division by $x$} - -Division by powers of $x$ is easily achieved by shifting the digits right and removing any that will end up to the right of the zero'th digit. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_rshd}. \\ -\textbf{Input}. One mp\_int $a$ and an integer $b$ \\ -\textbf{Output}. $a \leftarrow a / \beta^b$ (Divide by $x^b$). \\ -\hline \\ -1. If $b \le 0$ then return. \\ -2. If $a.used \le b$ then do \\ -\hspace{3mm}2.1 Zero $a$. (\textit{mp\_zero}). \\ -\hspace{3mm}2.2 Return. \\ -3. $i \leftarrow 0$ \\ -4. $j \leftarrow b$ \\ -5. for $n$ from 0 to $a.used - b - 1$ do \\ -\hspace{3mm}5.1 $a_i \leftarrow a_j$ \\ -\hspace{3mm}5.2 $i \leftarrow i + 1$ \\ -\hspace{3mm}5.3 $j \leftarrow j + 1$ \\ -6. for $n$ from $a.used - b$ to $a.used - 1$ do \\ -\hspace{3mm}6.1 $a_n \leftarrow 0$ \\ -7. $a.used \leftarrow a.used - b$ \\ -8. Return. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_rshd} -\end{figure} - -\textbf{Algorithm mp\_rshd.} -This algorithm divides the input in place by the $b$'th power of $x$. It is analogous to dividing by a $\beta^b$ but much quicker since -it does not require single precision division. This algorithm does not actually return an error code as it cannot fail. - -If the input $b$ is less than one the algorithm quickly returns without performing any work. If the \textbf{used} count is less than or equal -to the shift count $b$ then it will simply zero the input and return. - -After the trivial cases of inputs have been handled the sliding window is setup. Much like the case of algorithm mp\_lshd a sliding window that -is $b$ digits wide is used to copy the digits. Unlike mp\_lshd the window slides in the opposite direction from the trailing to the leading digit. -Also the digits are copied from the leading to the trailing edge. - -Once the window copy is complete the upper digits must be zeroed and the \textbf{used} count decremented. - -EXAM,bn_mp_rshd.c - -The only noteworthy element of this routine is the lack of a return type since it cannot fail. Like mp\_lshd() we -form a sliding window except we copy in the other direction. After the window (line @59,for (;@) we then zero -the upper digits of the input to make sure the result is correct. - -\section{Powers of Two} - -Now that algorithms for moving single bits as well as whole digits exist algorithms for moving the ``in between'' distances are required. For -example, to quickly multiply by $2^k$ for any $k$ without using a full multiplier algorithm would prove useful. Instead of performing single -shifts $k$ times to achieve a multiplication by $2^{\pm k}$ a mixture of whole digit shifting and partial digit shifting is employed. - -\subsection{Multiplication by Power of Two} - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_mul\_2d}. \\ -\textbf{Input}. One mp\_int $a$ and an integer $b$ \\ -\textbf{Output}. $c \leftarrow a \cdot 2^b$. \\ -\hline \\ -1. $c \leftarrow a$. (\textit{mp\_copy}) \\ -2. If $c.alloc < c.used + \lfloor b / lg(\beta) \rfloor + 2$ then grow $c$ accordingly. \\ -3. If the reallocation failed return(\textit{MP\_MEM}). \\ -4. If $b \ge lg(\beta)$ then \\ -\hspace{3mm}4.1 $c \leftarrow c \cdot \beta^{\lfloor b / lg(\beta) \rfloor}$ (\textit{mp\_lshd}). \\ -\hspace{3mm}4.2 If step 4.1 failed return(\textit{MP\_MEM}). \\ -5. $d \leftarrow b \mbox{ (mod }lg(\beta)\mbox{)}$ \\ -6. If $d \ne 0$ then do \\ -\hspace{3mm}6.1 $mask \leftarrow 2^d$ \\ -\hspace{3mm}6.2 $r \leftarrow 0$ \\ -\hspace{3mm}6.3 for $n$ from $0$ to $c.used - 1$ do \\ -\hspace{6mm}6.3.1 $rr \leftarrow c_n >> (lg(\beta) - d) \mbox{ (mod }mask\mbox{)}$ \\ -\hspace{6mm}6.3.2 $c_n \leftarrow (c_n << d) + r \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{6mm}6.3.3 $r \leftarrow rr$ \\ -\hspace{3mm}6.4 If $r > 0$ then do \\ -\hspace{6mm}6.4.1 $c_{c.used} \leftarrow r$ \\ -\hspace{6mm}6.4.2 $c.used \leftarrow c.used + 1$ \\ -7. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_mul\_2d} -\end{figure} - -\textbf{Algorithm mp\_mul\_2d.} -This algorithm multiplies $a$ by $2^b$ and stores the result in $c$. The algorithm uses algorithm mp\_lshd and a derivative of algorithm mp\_mul\_2 to -quickly compute the product. - -First the algorithm will multiply $a$ by $x^{\lfloor b / lg(\beta) \rfloor}$ which will ensure that the remainder multiplicand is less than -$\beta$. For example, if $b = 37$ and $\beta = 2^{28}$ then this step will multiply by $x$ leaving a multiplication by $2^{37 - 28} = 2^{9}$ -left. - -After the digits have been shifted appropriately at most $lg(\beta) - 1$ shifts are left to perform. Step 5 calculates the number of remaining shifts -required. If it is non-zero a modified shift loop is used to calculate the remaining product. -Essentially the loop is a generic version of algorithm mp\_mul\_2 designed to handle any shift count in the range $1 \le x < lg(\beta)$. The $mask$ -variable is used to extract the upper $d$ bits to form the carry for the next iteration. - -This algorithm is loosely measured as a $O(2n)$ algorithm which means that if the input is $n$-digits that it takes $2n$ ``time'' to -complete. It is possible to optimize this algorithm down to a $O(n)$ algorithm at a cost of making the algorithm slightly harder to follow. - -EXAM,bn_mp_mul_2d.c - -The shifting is performed in--place which means the first step (line @24,a != c@) is to copy the input to the -destination. We avoid calling mp\_copy() by making sure the mp\_ints are different. The destination then -has to be grown (line @31,grow@) to accomodate the result. - -If the shift count $b$ is larger than $lg(\beta)$ then a call to mp\_lshd() is used to handle all of the multiples -of $lg(\beta)$. Leaving only a remaining shift of $lg(\beta) - 1$ or fewer bits left. Inside the actual shift -loop (lines @45,if@ to @76,}@) we make use of pre--computed values $shift$ and $mask$. These are used to -extract the carry bit(s) to pass into the next iteration of the loop. The $r$ and $rr$ variables form a -chain between consecutive iterations to propagate the carry. - -\subsection{Division by Power of Two} - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_div\_2d}. \\ -\textbf{Input}. One mp\_int $a$ and an integer $b$ \\ -\textbf{Output}. $c \leftarrow \lfloor a / 2^b \rfloor, d \leftarrow a \mbox{ (mod }2^b\mbox{)}$. \\ -\hline \\ -1. If $b \le 0$ then do \\ -\hspace{3mm}1.1 $c \leftarrow a$ (\textit{mp\_copy}) \\ -\hspace{3mm}1.2 $d \leftarrow 0$ (\textit{mp\_zero}) \\ -\hspace{3mm}1.3 Return(\textit{MP\_OKAY}). \\ -2. $c \leftarrow a$ \\ -3. $d \leftarrow a \mbox{ (mod }2^b\mbox{)}$ (\textit{mp\_mod\_2d}) \\ -4. If $b \ge lg(\beta)$ then do \\ -\hspace{3mm}4.1 $c \leftarrow \lfloor c/\beta^{\lfloor b/lg(\beta) \rfloor} \rfloor$ (\textit{mp\_rshd}). \\ -5. $k \leftarrow b \mbox{ (mod }lg(\beta)\mbox{)}$ \\ -6. If $k \ne 0$ then do \\ -\hspace{3mm}6.1 $mask \leftarrow 2^k$ \\ -\hspace{3mm}6.2 $r \leftarrow 0$ \\ -\hspace{3mm}6.3 for $n$ from $c.used - 1$ to $0$ do \\ -\hspace{6mm}6.3.1 $rr \leftarrow c_n \mbox{ (mod }mask\mbox{)}$ \\ -\hspace{6mm}6.3.2 $c_n \leftarrow (c_n >> k) + (r << (lg(\beta) - k))$ \\ -\hspace{6mm}6.3.3 $r \leftarrow rr$ \\ -7. Clamp excess digits of $c$. (\textit{mp\_clamp}) \\ -8. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_div\_2d} -\end{figure} - -\textbf{Algorithm mp\_div\_2d.} -This algorithm will divide an input $a$ by $2^b$ and produce the quotient and remainder. The algorithm is designed much like algorithm -mp\_mul\_2d by first using whole digit shifts then single precision shifts. This algorithm will also produce the remainder of the division -by using algorithm mp\_mod\_2d. - -EXAM,bn_mp_div_2d.c - -The implementation of algorithm mp\_div\_2d is slightly different than the algorithm specifies. The remainder $d$ may be optionally -ignored by passing \textbf{NULL} as the pointer to the mp\_int variable. The temporary mp\_int variable $t$ is used to hold the -result of the remainder operation until the end. This allows $d$ and $a$ to represent the same mp\_int without modifying $a$ before -the quotient is obtained. - -The remainder of the source code is essentially the same as the source code for mp\_mul\_2d. The only significant difference is -the direction of the shifts. - -\subsection{Remainder of Division by Power of Two} - -The last algorithm in the series of polynomial basis power of two algorithms is calculating the remainder of division by $2^b$. This -algorithm benefits from the fact that in twos complement arithmetic $a \mbox{ (mod }2^b\mbox{)}$ is the same as $a$ AND $2^b - 1$. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_mod\_2d}. \\ -\textbf{Input}. One mp\_int $a$ and an integer $b$ \\ -\textbf{Output}. $c \leftarrow a \mbox{ (mod }2^b\mbox{)}$. \\ -\hline \\ -1. If $b \le 0$ then do \\ -\hspace{3mm}1.1 $c \leftarrow 0$ (\textit{mp\_zero}) \\ -\hspace{3mm}1.2 Return(\textit{MP\_OKAY}). \\ -2. If $b > a.used \cdot lg(\beta)$ then do \\ -\hspace{3mm}2.1 $c \leftarrow a$ (\textit{mp\_copy}) \\ -\hspace{3mm}2.2 Return the result of step 2.1. \\ -3. $c \leftarrow a$ \\ -4. If step 3 failed return(\textit{MP\_MEM}). \\ -5. for $n$ from $\lceil b / lg(\beta) \rceil$ to $c.used$ do \\ -\hspace{3mm}5.1 $c_n \leftarrow 0$ \\ -6. $k \leftarrow b \mbox{ (mod }lg(\beta)\mbox{)}$ \\ -7. $c_{\lfloor b / lg(\beta) \rfloor} \leftarrow c_{\lfloor b / lg(\beta) \rfloor} \mbox{ (mod }2^{k}\mbox{)}$. \\ -8. Clamp excess digits of $c$. (\textit{mp\_clamp}) \\ -9. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_mod\_2d} -\end{figure} - -\textbf{Algorithm mp\_mod\_2d.} -This algorithm will quickly calculate the value of $a \mbox{ (mod }2^b\mbox{)}$. First if $b$ is less than or equal to zero the -result is set to zero. If $b$ is greater than the number of bits in $a$ then it simply copies $a$ to $c$ and returns. Otherwise, $a$ -is copied to $b$, leading digits are removed and the remaining leading digit is trimed to the exact bit count. - -EXAM,bn_mp_mod_2d.c - -We first avoid cases of $b \le 0$ by simply mp\_zero()'ing the destination in such cases. Next if $2^b$ is larger -than the input we just mp\_copy() the input and return right away. After this point we know we must actually -perform some work to produce the remainder. - -Recalling that reducing modulo $2^k$ and a binary ``and'' with $2^k - 1$ are numerically equivalent we can quickly reduce -the number. First we zero any digits above the last digit in $2^b$ (line @41,for@). Next we reduce the -leading digit of both (line @45,&=@) and then mp\_clamp(). - -\section*{Exercises} -\begin{tabular}{cl} -$\left [ 3 \right ] $ & Devise an algorithm that performs $a \cdot 2^b$ for generic values of $b$ \\ - & in $O(n)$ time. \\ - &\\ -$\left [ 3 \right ] $ & Devise an efficient algorithm to multiply by small low hamming \\ - & weight values such as $3$, $5$ and $9$. Extend it to handle all values \\ - & upto $64$ with a hamming weight less than three. \\ - &\\ -$\left [ 2 \right ] $ & Modify the preceding algorithm to handle values of the form \\ - & $2^k - 1$ as well. \\ - &\\ -$\left [ 3 \right ] $ & Using only algorithms mp\_mul\_2, mp\_div\_2 and mp\_add create an \\ - & algorithm to multiply two integers in roughly $O(2n^2)$ time for \\ - & any $n$-bit input. Note that the time of addition is ignored in the \\ - & calculation. \\ - & \\ -$\left [ 5 \right ] $ & Improve the previous algorithm to have a working time of at most \\ - & $O \left (2^{(k-1)}n + \left ({2n^2 \over k} \right ) \right )$ for an appropriate choice of $k$. Again ignore \\ - & the cost of addition. \\ - & \\ -$\left [ 2 \right ] $ & Devise a chart to find optimal values of $k$ for the previous problem \\ - & for $n = 64 \ldots 1024$ in steps of $64$. \\ - & \\ -$\left [ 2 \right ] $ & Using only algorithms mp\_abs and mp\_sub devise another method for \\ - & calculating the result of a signed comparison. \\ - & -\end{tabular} - -\chapter{Multiplication and Squaring} -\section{The Multipliers} -For most number theoretic problems including certain public key cryptographic algorithms, the ``multipliers'' form the most important subset of -algorithms of any multiple precision integer package. The set of multiplier algorithms include integer multiplication, squaring and modular reduction -where in each of the algorithms single precision multiplication is the dominant operation performed. This chapter will discuss integer multiplication -and squaring, leaving modular reductions for the subsequent chapter. - -The importance of the multiplier algorithms is for the most part driven by the fact that certain popular public key algorithms are based on modular -exponentiation, that is computing $d \equiv a^b \mbox{ (mod }c\mbox{)}$ for some arbitrary choice of $a$, $b$, $c$ and $d$. During a modular -exponentiation the majority\footnote{Roughly speaking a modular exponentiation will spend about 40\% of the time performing modular reductions, -35\% of the time performing squaring and 25\% of the time performing multiplications.} of the processor time is spent performing single precision -multiplications. - -For centuries general purpose multiplication has required a lengthly $O(n^2)$ process, whereby each digit of one multiplicand has to be multiplied -against every digit of the other multiplicand. Traditional long-hand multiplication is based on this process; while the techniques can differ the -overall algorithm used is essentially the same. Only ``recently'' have faster algorithms been studied. First Karatsuba multiplication was discovered in -1962. This algorithm can multiply two numbers with considerably fewer single precision multiplications when compared to the long-hand approach. -This technique led to the discovery of polynomial basis algorithms (\textit{good reference?}) and subquently Fourier Transform based solutions. - -\section{Multiplication} -\subsection{The Baseline Multiplication} -\label{sec:basemult} -\index{baseline multiplication} -Computing the product of two integers in software can be achieved using a trivial adaptation of the standard $O(n^2)$ long-hand multiplication -algorithm that school children are taught. The algorithm is considered an $O(n^2)$ algorithm since for two $n$-digit inputs $n^2$ single precision -multiplications are required. More specifically for a $m$ and $n$ digit input $m \cdot n$ single precision multiplications are required. To -simplify most discussions, it will be assumed that the inputs have comparable number of digits. - -The ``baseline multiplication'' algorithm is designed to act as the ``catch-all'' algorithm, only to be used when the faster algorithms cannot be -used. This algorithm does not use any particularly interesting optimizations and should ideally be avoided if possible. One important -facet of this algorithm, is that it has been modified to only produce a certain amount of output digits as resolution. The importance of this -modification will become evident during the discussion of Barrett modular reduction. Recall that for a $n$ and $m$ digit input the product -will be at most $n + m$ digits. Therefore, this algorithm can be reduced to a full multiplier by having it produce $n + m$ digits of the product. - -Recall from ~GAMMA~ the definition of $\gamma$ as the number of bits in the type \textbf{mp\_digit}. We shall now extend the variable set to -include $\alpha$ which shall represent the number of bits in the type \textbf{mp\_word}. This implies that $2^{\alpha} > 2 \cdot \beta^2$. The -constant $\delta = 2^{\alpha - 2lg(\beta)}$ will represent the maximal weight of any column in a product (\textit{see ~COMBA~ for more information}). - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{s\_mp\_mul\_digs}. \\ -\textbf{Input}. mp\_int $a$, mp\_int $b$ and an integer $digs$ \\ -\textbf{Output}. $c \leftarrow \vert a \vert \cdot \vert b \vert \mbox{ (mod }\beta^{digs}\mbox{)}$. \\ -\hline \\ -1. If min$(a.used, b.used) < \delta$ then do \\ -\hspace{3mm}1.1 Calculate $c = \vert a \vert \cdot \vert b \vert$ by the Comba method (\textit{see algorithm~\ref{fig:COMBAMULT}}). \\ -\hspace{3mm}1.2 Return the result of step 1.1 \\ -\\ -Allocate and initialize a temporary mp\_int. \\ -2. Init $t$ to be of size $digs$ \\ -3. If step 2 failed return(\textit{MP\_MEM}). \\ -4. $t.used \leftarrow digs$ \\ -\\ -Compute the product. \\ -5. for $ix$ from $0$ to $a.used - 1$ do \\ -\hspace{3mm}5.1 $u \leftarrow 0$ \\ -\hspace{3mm}5.2 $pb \leftarrow \mbox{min}(b.used, digs - ix)$ \\ -\hspace{3mm}5.3 If $pb < 1$ then goto step 6. \\ -\hspace{3mm}5.4 for $iy$ from $0$ to $pb - 1$ do \\ -\hspace{6mm}5.4.1 $\hat r \leftarrow t_{iy + ix} + a_{ix} \cdot b_{iy} + u$ \\ -\hspace{6mm}5.4.2 $t_{iy + ix} \leftarrow \hat r \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{6mm}5.4.3 $u \leftarrow \lfloor \hat r / \beta \rfloor$ \\ -\hspace{3mm}5.5 if $ix + pb < digs$ then do \\ -\hspace{6mm}5.5.1 $t_{ix + pb} \leftarrow u$ \\ -6. Clamp excess digits of $t$. \\ -7. Swap $c$ with $t$ \\ -8. Clear $t$ \\ -9. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm s\_mp\_mul\_digs} -\end{figure} - -\textbf{Algorithm s\_mp\_mul\_digs.} -This algorithm computes the unsigned product of two inputs $a$ and $b$, limited to an output precision of $digs$ digits. While it may seem -a bit awkward to modify the function from its simple $O(n^2)$ description, the usefulness of partial multipliers will arise in a subsequent -algorithm. The algorithm is loosely based on algorithm 14.12 from \cite[pp. 595]{HAC} and is similar to Algorithm M of Knuth \cite[pp. 268]{TAOCPV2}. -Algorithm s\_mp\_mul\_digs differs from these cited references since it can produce a variable output precision regardless of the precision of the -inputs. - -The first thing this algorithm checks for is whether a Comba multiplier can be used instead. If the minimum digit count of either -input is less than $\delta$, then the Comba method may be used instead. After the Comba method is ruled out, the baseline algorithm begins. A -temporary mp\_int variable $t$ is used to hold the intermediate result of the product. This allows the algorithm to be used to -compute products when either $a = c$ or $b = c$ without overwriting the inputs. - -All of step 5 is the infamous $O(n^2)$ multiplication loop slightly modified to only produce upto $digs$ digits of output. The $pb$ variable -is given the count of digits to read from $b$ inside the nested loop. If $pb \le 1$ then no more output digits can be produced and the algorithm -will exit the loop. The best way to think of the loops are as a series of $pb \times 1$ multiplications. That is, in each pass of the -innermost loop $a_{ix}$ is multiplied against $b$ and the result is added (\textit{with an appropriate shift}) to $t$. - -For example, consider multiplying $576$ by $241$. That is equivalent to computing $10^0(1)(576) + 10^1(4)(576) + 10^2(2)(576)$ which is best -visualized in the following table. - -\begin{figure}[here] -\begin{center} -\begin{tabular}{|c|c|c|c|c|c|l|} -\hline && & 5 & 7 & 6 & \\ -\hline $\times$&& & 2 & 4 & 1 & \\ -\hline &&&&&&\\ - && & 5 & 7 & 6 & $10^0(1)(576)$ \\ - &2 & 3 & 6 & 1 & 6 & $10^1(4)(576) + 10^0(1)(576)$ \\ - 1 & 3 & 8 & 8 & 1 & 6 & $10^2(2)(576) + 10^1(4)(576) + 10^0(1)(576)$ \\ -\hline -\end{tabular} -\end{center} -\caption{Long-Hand Multiplication Diagram} -\end{figure} - -Each row of the product is added to the result after being shifted to the left (\textit{multiplied by a power of the radix}) by the appropriate -count. That is in pass $ix$ of the inner loop the product is added starting at the $ix$'th digit of the reult. - -Step 5.4.1 introduces the hat symbol (\textit{e.g. $\hat r$}) which represents a double precision variable. The multiplication on that step -is assumed to be a double wide output single precision multiplication. That is, two single precision variables are multiplied to produce a -double precision result. The step is somewhat optimized from a long-hand multiplication algorithm because the carry from the addition in step -5.4.1 is propagated through the nested loop. If the carry was not propagated immediately it would overflow the single precision digit -$t_{ix+iy}$ and the result would be lost. - -At step 5.5 the nested loop is finished and any carry that was left over should be forwarded. The carry does not have to be added to the $ix+pb$'th -digit since that digit is assumed to be zero at this point. However, if $ix + pb \ge digs$ the carry is not set as it would make the result -exceed the precision requested. - -EXAM,bn_s_mp_mul_digs.c - -First we determine (line @30,if@) if the Comba method can be used first since it's faster. The conditions for -sing the Comba routine are that min$(a.used, b.used) < \delta$ and the number of digits of output is less than -\textbf{MP\_WARRAY}. This new constant is used to control the stack usage in the Comba routines. By default it is -set to $\delta$ but can be reduced when memory is at a premium. - -If we cannot use the Comba method we proceed to setup the baseline routine. We allocate the the destination mp\_int -$t$ (line @36,init@) to the exact size of the output to avoid further re--allocations. At this point we now -begin the $O(n^2)$ loop. - -This implementation of multiplication has the caveat that it can be trimmed to only produce a variable number of -digits as output. In each iteration of the outer loop the $pb$ variable is set (line @48,MIN@) to the maximum -number of inner loop iterations. - -Inside the inner loop we calculate $\hat r$ as the mp\_word product of the two mp\_digits and the addition of the -carry from the previous iteration. A particularly important observation is that most modern optimizing -C compilers (GCC for instance) can recognize that a $N \times N \rightarrow 2N$ multiplication is all that -is required for the product. In x86 terms for example, this means using the MUL instruction. - -Each digit of the product is stored in turn (line @68,tmpt@) and the carry propagated (line @71,>>@) to the -next iteration. - -\subsection{Faster Multiplication by the ``Comba'' Method} -MARK,COMBA - -One of the huge drawbacks of the ``baseline'' algorithms is that at the $O(n^2)$ level the carry must be -computed and propagated upwards. This makes the nested loop very sequential and hard to unroll and implement -in parallel. The ``Comba'' \cite{COMBA} method is named after little known (\textit{in cryptographic venues}) Paul G. -Comba who described a method of implementing fast multipliers that do not require nested carry fixup operations. As an -interesting aside it seems that Paul Barrett describes a similar technique in his 1986 paper \cite{BARRETT} written -five years before. - -At the heart of the Comba technique is once again the long-hand algorithm. Except in this case a slight -twist is placed on how the columns of the result are produced. In the standard long-hand algorithm rows of products -are produced then added together to form the final result. In the baseline algorithm the columns are added together -after each iteration to get the result instantaneously. - -In the Comba algorithm the columns of the result are produced entirely independently of each other. That is at -the $O(n^2)$ level a simple multiplication and addition step is performed. The carries of the columns are propagated -after the nested loop to reduce the amount of work requiored. Succintly the first step of the algorithm is to compute -the product vector $\vec x$ as follows. - -\begin{equation} -\vec x_n = \sum_{i+j = n} a_ib_j, \forall n \in \lbrace 0, 1, 2, \ldots, i + j \rbrace -\end{equation} - -Where $\vec x_n$ is the $n'th$ column of the output vector. Consider the following example which computes the vector $\vec x$ for the multiplication -of $576$ and $241$. - -\newpage\begin{figure}[here] -\begin{small} -\begin{center} -\begin{tabular}{|c|c|c|c|c|c|} - \hline & & 5 & 7 & 6 & First Input\\ - \hline $\times$ & & 2 & 4 & 1 & Second Input\\ -\hline & & $1 \cdot 5 = 5$ & $1 \cdot 7 = 7$ & $1 \cdot 6 = 6$ & First pass \\ - & $4 \cdot 5 = 20$ & $4 \cdot 7+5=33$ & $4 \cdot 6+7=31$ & 6 & Second pass \\ - $2 \cdot 5 = 10$ & $2 \cdot 7 + 20 = 34$ & $2 \cdot 6+33=45$ & 31 & 6 & Third pass \\ -\hline 10 & 34 & 45 & 31 & 6 & Final Result \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Comba Multiplication Diagram} -\end{figure} - -At this point the vector $x = \left < 10, 34, 45, 31, 6 \right >$ is the result of the first step of the Comba multipler. -Now the columns must be fixed by propagating the carry upwards. The resultant vector will have one extra dimension over the input vector which is -congruent to adding a leading zero digit. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{Comba Fixup}. \\ -\textbf{Input}. Vector $\vec x$ of dimension $k$ \\ -\textbf{Output}. Vector $\vec x$ such that the carries have been propagated. \\ -\hline \\ -1. for $n$ from $0$ to $k - 1$ do \\ -\hspace{3mm}1.1 $\vec x_{n+1} \leftarrow \vec x_{n+1} + \lfloor \vec x_{n}/\beta \rfloor$ \\ -\hspace{3mm}1.2 $\vec x_{n} \leftarrow \vec x_{n} \mbox{ (mod }\beta\mbox{)}$ \\ -2. Return($\vec x$). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm Comba Fixup} -\end{figure} - -With that algorithm and $k = 5$ and $\beta = 10$ the following vector is produced $\vec x= \left < 1, 3, 8, 8, 1, 6 \right >$. In this case -$241 \cdot 576$ is in fact $138816$ and the procedure succeeded. If the algorithm is correct and as will be demonstrated shortly more -efficient than the baseline algorithm why not simply always use this algorithm? - -\subsubsection{Column Weight.} -At the nested $O(n^2)$ level the Comba method adds the product of two single precision variables to each column of the output -independently. A serious obstacle is if the carry is lost, due to lack of precision before the algorithm has a chance to fix -the carries. For example, in the multiplication of two three-digit numbers the third column of output will be the sum of -three single precision multiplications. If the precision of the accumulator for the output digits is less then $3 \cdot (\beta - 1)^2$ then -an overflow can occur and the carry information will be lost. For any $m$ and $n$ digit inputs the maximum weight of any column is -min$(m, n)$ which is fairly obvious. - -The maximum number of terms in any column of a product is known as the ``column weight'' and strictly governs when the algorithm can be used. Recall -from earlier that a double precision type has $\alpha$ bits of resolution and a single precision digit has $lg(\beta)$ bits of precision. Given these -two quantities we must not violate the following - -\begin{equation} -k \cdot \left (\beta - 1 \right )^2 < 2^{\alpha} -\end{equation} - -Which reduces to - -\begin{equation} -k \cdot \left ( \beta^2 - 2\beta + 1 \right ) < 2^{\alpha} -\end{equation} - -Let $\rho = lg(\beta)$ represent the number of bits in a single precision digit. By further re-arrangement of the equation the final solution is -found. - -\begin{equation} -k < {{2^{\alpha}} \over {\left (2^{2\rho} - 2^{\rho + 1} + 1 \right )}} -\end{equation} - -The defaults for LibTomMath are $\beta = 2^{28}$ and $\alpha = 2^{64}$ which means that $k$ is bounded by $k < 257$. In this configuration -the smaller input may not have more than $256$ digits if the Comba method is to be used. This is quite satisfactory for most applications since -$256$ digits would allow for numbers in the range of $0 \le x < 2^{7168}$ which, is much larger than most public key cryptographic algorithms require. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{fast\_s\_mp\_mul\_digs}. \\ -\textbf{Input}. mp\_int $a$, mp\_int $b$ and an integer $digs$ \\ -\textbf{Output}. $c \leftarrow \vert a \vert \cdot \vert b \vert \mbox{ (mod }\beta^{digs}\mbox{)}$. \\ -\hline \\ -Place an array of \textbf{MP\_WARRAY} single precision digits named $W$ on the stack. \\ -1. If $c.alloc < digs$ then grow $c$ to $digs$ digits. (\textit{mp\_grow}) \\ -2. If step 1 failed return(\textit{MP\_MEM}).\\ -\\ -3. $pa \leftarrow \mbox{MIN}(digs, a.used + b.used)$ \\ -\\ -4. $\_ \hat W \leftarrow 0$ \\ -5. for $ix$ from 0 to $pa - 1$ do \\ -\hspace{3mm}5.1 $ty \leftarrow \mbox{MIN}(b.used - 1, ix)$ \\ -\hspace{3mm}5.2 $tx \leftarrow ix - ty$ \\ -\hspace{3mm}5.3 $iy \leftarrow \mbox{MIN}(a.used - tx, ty + 1)$ \\ -\hspace{3mm}5.4 for $iz$ from 0 to $iy - 1$ do \\ -\hspace{6mm}5.4.1 $\_ \hat W \leftarrow \_ \hat W + a_{tx+iy}b_{ty-iy}$ \\ -\hspace{3mm}5.5 $W_{ix} \leftarrow \_ \hat W (\mbox{mod }\beta)$\\ -\hspace{3mm}5.6 $\_ \hat W \leftarrow \lfloor \_ \hat W / \beta \rfloor$ \\ -\\ -6. $oldused \leftarrow c.used$ \\ -7. $c.used \leftarrow digs$ \\ -8. for $ix$ from $0$ to $pa$ do \\ -\hspace{3mm}8.1 $c_{ix} \leftarrow W_{ix}$ \\ -9. for $ix$ from $pa + 1$ to $oldused - 1$ do \\ -\hspace{3mm}9.1 $c_{ix} \leftarrow 0$ \\ -\\ -10. Clamp $c$. \\ -11. Return MP\_OKAY. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm fast\_s\_mp\_mul\_digs} -\label{fig:COMBAMULT} -\end{figure} - -\textbf{Algorithm fast\_s\_mp\_mul\_digs.} -This algorithm performs the unsigned multiplication of $a$ and $b$ using the Comba method limited to $digs$ digits of precision. - -The outer loop of this algorithm is more complicated than that of the baseline multiplier. This is because on the inside of the -loop we want to produce one column per pass. This allows the accumulator $\_ \hat W$ to be placed in CPU registers and -reduce the memory bandwidth to two \textbf{mp\_digit} reads per iteration. - -The $ty$ variable is set to the minimum count of $ix$ or the number of digits in $b$. That way if $a$ has more digits than -$b$ this will be limited to $b.used - 1$. The $tx$ variable is set to the to the distance past $b.used$ the variable -$ix$ is. This is used for the immediately subsequent statement where we find $iy$. - -The variable $iy$ is the minimum digits we can read from either $a$ or $b$ before running out. Computing one column at a time -means we have to scan one integer upwards and the other downwards. $a$ starts at $tx$ and $b$ starts at $ty$. In each -pass we are producing the $ix$'th output column and we note that $tx + ty = ix$. As we move $tx$ upwards we have to -move $ty$ downards so the equality remains valid. The $iy$ variable is the number of iterations until -$tx \ge a.used$ or $ty < 0$ occurs. - -After every inner pass we store the lower half of the accumulator into $W_{ix}$ and then propagate the carry of the accumulator -into the next round by dividing $\_ \hat W$ by $\beta$. - -To measure the benefits of the Comba method over the baseline method consider the number of operations that are required. If the -cost in terms of time of a multiply and addition is $p$ and the cost of a carry propagation is $q$ then a baseline multiplication would require -$O \left ((p + q)n^2 \right )$ time to multiply two $n$-digit numbers. The Comba method requires only $O(pn^2 + qn)$ time, however in practice, -the speed increase is actually much more. With $O(n)$ space the algorithm can be reduced to $O(pn + qn)$ time by implementing the $n$ multiply -and addition operations in the nested loop in parallel. - -EXAM,bn_fast_s_mp_mul_digs.c - -As per the pseudo--code we first calculate $pa$ (line @47,MIN@) as the number of digits to output. Next we begin the outer loop -to produce the individual columns of the product. We use the two aliases $tmpx$ and $tmpy$ (lines @61,tmpx@, @62,tmpy@) to point -inside the two multiplicands quickly. - -The inner loop (lines @70,for@ to @72,}@) of this implementation is where the tradeoff come into play. Originally this comba -implementation was ``row--major'' which means it adds to each of the columns in each pass. After the outer loop it would then fix -the carries. This was very fast except it had an annoying drawback. You had to read a mp\_word and two mp\_digits and write -one mp\_word per iteration. On processors such as the Athlon XP and P4 this did not matter much since the cache bandwidth -is very high and it can keep the ALU fed with data. It did, however, matter on older and embedded cpus where cache is often -slower and also often doesn't exist. This new algorithm only performs two reads per iteration under the assumption that the -compiler has aliased $\_ \hat W$ to a CPU register. - -After the inner loop we store the current accumulator in $W$ and shift $\_ \hat W$ (lines @75,W[ix]@, @78,>>@) to forward it as -a carry for the next pass. After the outer loop we use the final carry (line @82,W[ix]@) as the last digit of the product. - -\subsection{Polynomial Basis Multiplication} -To break the $O(n^2)$ barrier in multiplication requires a completely different look at integer multiplication. In the following algorithms -the use of polynomial basis representation for two integers $a$ and $b$ as $f(x) = \sum_{i=0}^{n} a_i x^i$ and -$g(x) = \sum_{i=0}^{n} b_i x^i$ respectively, is required. In this system both $f(x)$ and $g(x)$ have $n + 1$ terms and are of the $n$'th degree. - -The product $a \cdot b \equiv f(x)g(x)$ is the polynomial $W(x) = \sum_{i=0}^{2n} w_i x^i$. The coefficients $w_i$ will -directly yield the desired product when $\beta$ is substituted for $x$. The direct solution to solve for the $2n + 1$ coefficients -requires $O(n^2)$ time and would in practice be slower than the Comba technique. - -However, numerical analysis theory indicates that only $2n + 1$ distinct points in $W(x)$ are required to determine the values of the $2n + 1$ unknown -coefficients. This means by finding $\zeta_y = W(y)$ for $2n + 1$ small values of $y$ the coefficients of $W(x)$ can be found with -Gaussian elimination. This technique is also occasionally refered to as the \textit{interpolation technique} (\textit{references please...}) since in -effect an interpolation based on $2n + 1$ points will yield a polynomial equivalent to $W(x)$. - -The coefficients of the polynomial $W(x)$ are unknown which makes finding $W(y)$ for any value of $y$ impossible. However, since -$W(x) = f(x)g(x)$ the equivalent $\zeta_y = f(y) g(y)$ can be used in its place. The benefit of this technique stems from the -fact that $f(y)$ and $g(y)$ are much smaller than either $a$ or $b$ respectively. As a result finding the $2n + 1$ relations required -by multiplying $f(y)g(y)$ involves multiplying integers that are much smaller than either of the inputs. - -When picking points to gather relations there are always three obvious points to choose, $y = 0, 1$ and $ \infty$. The $\zeta_0$ term -is simply the product $W(0) = w_0 = a_0 \cdot b_0$. The $\zeta_1$ term is the product -$W(1) = \left (\sum_{i = 0}^{n} a_i \right ) \left (\sum_{i = 0}^{n} b_i \right )$. The third point $\zeta_{\infty}$ is less obvious but rather -simple to explain. The $2n + 1$'th coefficient of $W(x)$ is numerically equivalent to the most significant column in an integer multiplication. -The point at $\infty$ is used symbolically to represent the most significant column, that is $W(\infty) = w_{2n} = a_nb_n$. Note that the -points at $y = 0$ and $\infty$ yield the coefficients $w_0$ and $w_{2n}$ directly. - -If more points are required they should be of small values and powers of two such as $2^q$ and the related \textit{mirror points} -$\left (2^q \right )^{2n} \cdot \zeta_{2^{-q}}$ for small values of $q$. The term ``mirror point'' stems from the fact that -$\left (2^q \right )^{2n} \cdot \zeta_{2^{-q}}$ can be calculated in the exact opposite fashion as $\zeta_{2^q}$. For -example, when $n = 2$ and $q = 1$ then following two equations are equivalent to the point $\zeta_{2}$ and its mirror. - -\begin{eqnarray} -\zeta_{2} = f(2)g(2) = (4a_2 + 2a_1 + a_0)(4b_2 + 2b_1 + b_0) \nonumber \\ -16 \cdot \zeta_{1 \over 2} = 4f({1\over 2}) \cdot 4g({1 \over 2}) = (a_2 + 2a_1 + 4a_0)(b_2 + 2b_1 + 4b_0) -\end{eqnarray} - -Using such points will allow the values of $f(y)$ and $g(y)$ to be independently calculated using only left shifts. For example, when $n = 2$ the -polynomial $f(2^q)$ is equal to $2^q((2^qa_2) + a_1) + a_0$. This technique of polynomial representation is known as Horner's method. - -As a general rule of the algorithm when the inputs are split into $n$ parts each there are $2n - 1$ multiplications. Each multiplication is of -multiplicands that have $n$ times fewer digits than the inputs. The asymptotic running time of this algorithm is -$O \left ( k^{lg_n(2n - 1)} \right )$ for $k$ digit inputs (\textit{assuming they have the same number of digits}). Figure~\ref{fig:exponent} -summarizes the exponents for various values of $n$. - -\begin{figure} -\begin{center} -\begin{tabular}{|c|c|c|} -\hline \textbf{Split into $n$ Parts} & \textbf{Exponent} & \textbf{Notes}\\ -\hline $2$ & $1.584962501$ & This is Karatsuba Multiplication. \\ -\hline $3$ & $1.464973520$ & This is Toom-Cook Multiplication. \\ -\hline $4$ & $1.403677461$ &\\ -\hline $5$ & $1.365212389$ &\\ -\hline $10$ & $1.278753601$ &\\ -\hline $100$ & $1.149426538$ &\\ -\hline $1000$ & $1.100270931$ &\\ -\hline $10000$ & $1.075252070$ &\\ -\hline -\end{tabular} -\end{center} -\caption{Asymptotic Running Time of Polynomial Basis Multiplication} -\label{fig:exponent} -\end{figure} - -At first it may seem like a good idea to choose $n = 1000$ since the exponent is approximately $1.1$. However, the overhead -of solving for the 2001 terms of $W(x)$ will certainly consume any savings the algorithm could offer for all but exceedingly large -numbers. - -\subsubsection{Cutoff Point} -The polynomial basis multiplication algorithms all require fewer single precision multiplications than a straight Comba approach. However, -the algorithms incur an overhead (\textit{at the $O(n)$ work level}) since they require a system of equations to be solved. This makes the -polynomial basis approach more costly to use with small inputs. - -Let $m$ represent the number of digits in the multiplicands (\textit{assume both multiplicands have the same number of digits}). There exists a -point $y$ such that when $m < y$ the polynomial basis algorithms are more costly than Comba, when $m = y$ they are roughly the same cost and -when $m > y$ the Comba methods are slower than the polynomial basis algorithms. - -The exact location of $y$ depends on several key architectural elements of the computer platform in question. - -\begin{enumerate} -\item The ratio of clock cycles for single precision multiplication versus other simpler operations such as addition, shifting, etc. For example -on the AMD Athlon the ratio is roughly $17 : 1$ while on the Intel P4 it is $29 : 1$. The higher the ratio in favour of multiplication the lower -the cutoff point $y$ will be. - -\item The complexity of the linear system of equations (\textit{for the coefficients of $W(x)$}) is. Generally speaking as the number of splits -grows the complexity grows substantially. Ideally solving the system will only involve addition, subtraction and shifting of integers. This -directly reflects on the ratio previous mentioned. - -\item To a lesser extent memory bandwidth and function call overheads. Provided the values are in the processor cache this is less of an -influence over the cutoff point. - -\end{enumerate} - -A clean cutoff point separation occurs when a point $y$ is found such that all of the cutoff point conditions are met. For example, if the point -is too low then there will be values of $m$ such that $m > y$ and the Comba method is still faster. Finding the cutoff points is fairly simple when -a high resolution timer is available. - -\subsection{Karatsuba Multiplication} -Karatsuba \cite{KARA} multiplication when originally proposed in 1962 was among the first set of algorithms to break the $O(n^2)$ barrier for -general purpose multiplication. Given two polynomial basis representations $f(x) = ax + b$ and $g(x) = cx + d$, Karatsuba proved with -light algebra \cite{KARAP} that the following polynomial is equivalent to multiplication of the two integers the polynomials represent. - -\begin{equation} -f(x) \cdot g(x) = acx^2 + ((a + b)(c + d) - (ac + bd))x + bd -\end{equation} - -Using the observation that $ac$ and $bd$ could be re-used only three half sized multiplications would be required to produce the product. Applying -this algorithm recursively, the work factor becomes $O(n^{lg(3)})$ which is substantially better than the work factor $O(n^2)$ of the Comba technique. It turns -out what Karatsuba did not know or at least did not publish was that this is simply polynomial basis multiplication with the points -$\zeta_0$, $\zeta_{\infty}$ and $\zeta_{1}$. Consider the resultant system of equations. - -\begin{center} -\begin{tabular}{rcrcrcrc} -$\zeta_{0}$ & $=$ & & & & & $w_0$ \\ -$\zeta_{1}$ & $=$ & $w_2$ & $+$ & $w_1$ & $+$ & $w_0$ \\ -$\zeta_{\infty}$ & $=$ & $w_2$ & & & & \\ -\end{tabular} -\end{center} - -By adding the first and last equation to the equation in the middle the term $w_1$ can be isolated and all three coefficients solved for. The simplicity -of this system of equations has made Karatsuba fairly popular. In fact the cutoff point is often fairly low\footnote{With LibTomMath 0.18 it is 70 and 109 digits for the Intel P4 and AMD Athlon respectively.} -making it an ideal algorithm to speed up certain public key cryptosystems such as RSA and Diffie-Hellman. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_karatsuba\_mul}. \\ -\textbf{Input}. mp\_int $a$ and mp\_int $b$ \\ -\textbf{Output}. $c \leftarrow \vert a \vert \cdot \vert b \vert$ \\ -\hline \\ -1. Init the following mp\_int variables: $x0$, $x1$, $y0$, $y1$, $t1$, $x0y0$, $x1y1$.\\ -2. If step 2 failed then return(\textit{MP\_MEM}). \\ -\\ -Split the input. e.g. $a = x1 \cdot \beta^B + x0$ \\ -3. $B \leftarrow \mbox{min}(a.used, b.used)/2$ \\ -4. $x0 \leftarrow a \mbox{ (mod }\beta^B\mbox{)}$ (\textit{mp\_mod\_2d}) \\ -5. $y0 \leftarrow b \mbox{ (mod }\beta^B\mbox{)}$ \\ -6. $x1 \leftarrow \lfloor a / \beta^B \rfloor$ (\textit{mp\_rshd}) \\ -7. $y1 \leftarrow \lfloor b / \beta^B \rfloor$ \\ -\\ -Calculate the three products. \\ -8. $x0y0 \leftarrow x0 \cdot y0$ (\textit{mp\_mul}) \\ -9. $x1y1 \leftarrow x1 \cdot y1$ \\ -10. $t1 \leftarrow x1 + x0$ (\textit{mp\_add}) \\ -11. $x0 \leftarrow y1 + y0$ \\ -12. $t1 \leftarrow t1 \cdot x0$ \\ -\\ -Calculate the middle term. \\ -13. $x0 \leftarrow x0y0 + x1y1$ \\ -14. $t1 \leftarrow t1 - x0$ (\textit{s\_mp\_sub}) \\ -\\ -Calculate the final product. \\ -15. $t1 \leftarrow t1 \cdot \beta^B$ (\textit{mp\_lshd}) \\ -16. $x1y1 \leftarrow x1y1 \cdot \beta^{2B}$ \\ -17. $t1 \leftarrow x0y0 + t1$ \\ -18. $c \leftarrow t1 + x1y1$ \\ -19. Clear all of the temporary variables. \\ -20. Return(\textit{MP\_OKAY}).\\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_karatsuba\_mul} -\end{figure} - -\textbf{Algorithm mp\_karatsuba\_mul.} -This algorithm computes the unsigned product of two inputs using the Karatsuba multiplication algorithm. It is loosely based on the description -from Knuth \cite[pp. 294-295]{TAOCPV2}. - -\index{radix point} -In order to split the two inputs into their respective halves, a suitable \textit{radix point} must be chosen. The radix point chosen must -be used for both of the inputs meaning that it must be smaller than the smallest input. Step 3 chooses the radix point $B$ as half of the -smallest input \textbf{used} count. After the radix point is chosen the inputs are split into lower and upper halves. Step 4 and 5 -compute the lower halves. Step 6 and 7 computer the upper halves. - -After the halves have been computed the three intermediate half-size products must be computed. Step 8 and 9 compute the trivial products -$x0 \cdot y0$ and $x1 \cdot y1$. The mp\_int $x0$ is used as a temporary variable after $x1 + x0$ has been computed. By using $x0$ instead -of an additional temporary variable, the algorithm can avoid an addition memory allocation operation. - -The remaining steps 13 through 18 compute the Karatsuba polynomial through a variety of digit shifting and addition operations. - -EXAM,bn_mp_karatsuba_mul.c - -The new coding element in this routine, not seen in previous routines, is the usage of goto statements. The conventional -wisdom is that goto statements should be avoided. This is generally true, however when every single function call can fail, it makes sense -to handle error recovery with a single piece of code. Lines @61,if@ to @75,if@ handle initializing all of the temporary variables -required. Note how each of the if statements goes to a different label in case of failure. This allows the routine to correctly free only -the temporaries that have been successfully allocated so far. - -The temporary variables are all initialized using the mp\_init\_size routine since they are expected to be large. This saves the -additional reallocation that would have been necessary. Also $x0$, $x1$, $y0$ and $y1$ have to be able to hold at least their respective -number of digits for the next section of code. - -The first algebraic portion of the algorithm is to split the two inputs into their halves. However, instead of using mp\_mod\_2d and mp\_rshd -to extract the halves, the respective code has been placed inline within the body of the function. To initialize the halves, the \textbf{used} and -\textbf{sign} members are copied first. The first for loop on line @98,for@ copies the lower halves. Since they are both the same magnitude it -is simpler to calculate both lower halves in a single loop. The for loop on lines @104,for@ and @109,for@ calculate the upper halves $x1$ and -$y1$ respectively. - -By inlining the calculation of the halves, the Karatsuba multiplier has a slightly lower overhead and can be used for smaller magnitude inputs. - -When line @152,err@ is reached, the algorithm has completed succesfully. The ``error status'' variable $err$ is set to \textbf{MP\_OKAY} so that -the same code that handles errors can be used to clear the temporary variables and return. - -\subsection{Toom-Cook $3$-Way Multiplication} -Toom-Cook $3$-Way \cite{TOOM} multiplication is essentially the polynomial basis algorithm for $n = 2$ except that the points are -chosen such that $\zeta$ is easy to compute and the resulting system of equations easy to reduce. Here, the points $\zeta_{0}$, -$16 \cdot \zeta_{1 \over 2}$, $\zeta_1$, $\zeta_2$ and $\zeta_{\infty}$ make up the five required points to solve for the coefficients -of the $W(x)$. - -With the five relations that Toom-Cook specifies, the following system of equations is formed. - -\begin{center} -\begin{tabular}{rcrcrcrcrcr} -$\zeta_0$ & $=$ & $0w_4$ & $+$ & $0w_3$ & $+$ & $0w_2$ & $+$ & $0w_1$ & $+$ & $1w_0$ \\ -$16 \cdot \zeta_{1 \over 2}$ & $=$ & $1w_4$ & $+$ & $2w_3$ & $+$ & $4w_2$ & $+$ & $8w_1$ & $+$ & $16w_0$ \\ -$\zeta_1$ & $=$ & $1w_4$ & $+$ & $1w_3$ & $+$ & $1w_2$ & $+$ & $1w_1$ & $+$ & $1w_0$ \\ -$\zeta_2$ & $=$ & $16w_4$ & $+$ & $8w_3$ & $+$ & $4w_2$ & $+$ & $2w_1$ & $+$ & $1w_0$ \\ -$\zeta_{\infty}$ & $=$ & $1w_4$ & $+$ & $0w_3$ & $+$ & $0w_2$ & $+$ & $0w_1$ & $+$ & $0w_0$ \\ -\end{tabular} -\end{center} - -A trivial solution to this matrix requires $12$ subtractions, two multiplications by a small power of two, two divisions by a small power -of two, two divisions by three and one multiplication by three. All of these $19$ sub-operations require less than quadratic time, meaning that -the algorithm can be faster than a baseline multiplication. However, the greater complexity of this algorithm places the cutoff point -(\textbf{TOOM\_MUL\_CUTOFF}) where Toom-Cook becomes more efficient much higher than the Karatsuba cutoff point. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_toom\_mul}. \\ -\textbf{Input}. mp\_int $a$ and mp\_int $b$ \\ -\textbf{Output}. $c \leftarrow a \cdot b $ \\ -\hline \\ -Split $a$ and $b$ into three pieces. E.g. $a = a_2 \beta^{2k} + a_1 \beta^{k} + a_0$ \\ -1. $k \leftarrow \lfloor \mbox{min}(a.used, b.used) / 3 \rfloor$ \\ -2. $a_0 \leftarrow a \mbox{ (mod }\beta^{k}\mbox{)}$ \\ -3. $a_1 \leftarrow \lfloor a / \beta^k \rfloor$, $a_1 \leftarrow a_1 \mbox{ (mod }\beta^{k}\mbox{)}$ \\ -4. $a_2 \leftarrow \lfloor a / \beta^{2k} \rfloor$, $a_2 \leftarrow a_2 \mbox{ (mod }\beta^{k}\mbox{)}$ \\ -5. $b_0 \leftarrow a \mbox{ (mod }\beta^{k}\mbox{)}$ \\ -6. $b_1 \leftarrow \lfloor a / \beta^k \rfloor$, $b_1 \leftarrow b_1 \mbox{ (mod }\beta^{k}\mbox{)}$ \\ -7. $b_2 \leftarrow \lfloor a / \beta^{2k} \rfloor$, $b_2 \leftarrow b_2 \mbox{ (mod }\beta^{k}\mbox{)}$ \\ -\\ -Find the five equations for $w_0, w_1, ..., w_4$. \\ -8. $w_0 \leftarrow a_0 \cdot b_0$ \\ -9. $w_4 \leftarrow a_2 \cdot b_2$ \\ -10. $tmp_1 \leftarrow 2 \cdot a_0$, $tmp_1 \leftarrow a_1 + tmp_1$, $tmp_1 \leftarrow 2 \cdot tmp_1$, $tmp_1 \leftarrow tmp_1 + a_2$ \\ -11. $tmp_2 \leftarrow 2 \cdot b_0$, $tmp_2 \leftarrow b_1 + tmp_2$, $tmp_2 \leftarrow 2 \cdot tmp_2$, $tmp_2 \leftarrow tmp_2 + b_2$ \\ -12. $w_1 \leftarrow tmp_1 \cdot tmp_2$ \\ -13. $tmp_1 \leftarrow 2 \cdot a_2$, $tmp_1 \leftarrow a_1 + tmp_1$, $tmp_1 \leftarrow 2 \cdot tmp_1$, $tmp_1 \leftarrow tmp_1 + a_0$ \\ -14. $tmp_2 \leftarrow 2 \cdot b_2$, $tmp_2 \leftarrow b_1 + tmp_2$, $tmp_2 \leftarrow 2 \cdot tmp_2$, $tmp_2 \leftarrow tmp_2 + b_0$ \\ -15. $w_3 \leftarrow tmp_1 \cdot tmp_2$ \\ -16. $tmp_1 \leftarrow a_0 + a_1$, $tmp_1 \leftarrow tmp_1 + a_2$, $tmp_2 \leftarrow b_0 + b_1$, $tmp_2 \leftarrow tmp_2 + b_2$ \\ -17. $w_2 \leftarrow tmp_1 \cdot tmp_2$ \\ -\\ -Continued on the next page.\\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_toom\_mul} -\end{figure} - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_toom\_mul} (continued). \\ -\textbf{Input}. mp\_int $a$ and mp\_int $b$ \\ -\textbf{Output}. $c \leftarrow a \cdot b $ \\ -\hline \\ -Now solve the system of equations. \\ -18. $w_1 \leftarrow w_4 - w_1$, $w_3 \leftarrow w_3 - w_0$ \\ -19. $w_1 \leftarrow \lfloor w_1 / 2 \rfloor$, $w_3 \leftarrow \lfloor w_3 / 2 \rfloor$ \\ -20. $w_2 \leftarrow w_2 - w_0$, $w_2 \leftarrow w_2 - w_4$ \\ -21. $w_1 \leftarrow w_1 - w_2$, $w_3 \leftarrow w_3 - w_2$ \\ -22. $tmp_1 \leftarrow 8 \cdot w_0$, $w_1 \leftarrow w_1 - tmp_1$, $tmp_1 \leftarrow 8 \cdot w_4$, $w_3 \leftarrow w_3 - tmp_1$ \\ -23. $w_2 \leftarrow 3 \cdot w_2$, $w_2 \leftarrow w_2 - w_1$, $w_2 \leftarrow w_2 - w_3$ \\ -24. $w_1 \leftarrow w_1 - w_2$, $w_3 \leftarrow w_3 - w_2$ \\ -25. $w_1 \leftarrow \lfloor w_1 / 3 \rfloor, w_3 \leftarrow \lfloor w_3 / 3 \rfloor$ \\ -\\ -Now substitute $\beta^k$ for $x$ by shifting $w_0, w_1, ..., w_4$. \\ -26. for $n$ from $1$ to $4$ do \\ -\hspace{3mm}26.1 $w_n \leftarrow w_n \cdot \beta^{nk}$ \\ -27. $c \leftarrow w_0 + w_1$, $c \leftarrow c + w_2$, $c \leftarrow c + w_3$, $c \leftarrow c + w_4$ \\ -28. Return(\textit{MP\_OKAY}) \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_toom\_mul (continued)} -\end{figure} - -\textbf{Algorithm mp\_toom\_mul.} -This algorithm computes the product of two mp\_int variables $a$ and $b$ using the Toom-Cook approach. Compared to the Karatsuba multiplication, this -algorithm has a lower asymptotic running time of approximately $O(n^{1.464})$ but at an obvious cost in overhead. In this -description, several statements have been compounded to save space. The intention is that the statements are executed from left to right across -any given step. - -The two inputs $a$ and $b$ are first split into three $k$-digit integers $a_0, a_1, a_2$ and $b_0, b_1, b_2$ respectively. From these smaller -integers the coefficients of the polynomial basis representations $f(x)$ and $g(x)$ are known and can be used to find the relations required. - -The first two relations $w_0$ and $w_4$ are the points $\zeta_{0}$ and $\zeta_{\infty}$ respectively. The relation $w_1, w_2$ and $w_3$ correspond -to the points $16 \cdot \zeta_{1 \over 2}, \zeta_{2}$ and $\zeta_{1}$ respectively. These are found using logical shifts to independently find -$f(y)$ and $g(y)$ which significantly speeds up the algorithm. - -After the five relations $w_0, w_1, \ldots, w_4$ have been computed, the system they represent must be solved in order for the unknown coefficients -$w_1, w_2$ and $w_3$ to be isolated. The steps 18 through 25 perform the system reduction required as previously described. Each step of -the reduction represents the comparable matrix operation that would be performed had this been performed by pencil. For example, step 18 indicates -that row $1$ must be subtracted from row $4$ and simultaneously row $0$ subtracted from row $3$. - -Once the coeffients have been isolated, the polynomial $W(x) = \sum_{i=0}^{2n} w_i x^i$ is known. By substituting $\beta^{k}$ for $x$, the integer -result $a \cdot b$ is produced. - -EXAM,bn_mp_toom_mul.c - -The first obvious thing to note is that this algorithm is complicated. The complexity is worth it if you are multiplying very -large numbers. For example, a 10,000 digit multiplication takes approximaly 99,282,205 fewer single precision multiplications with -Toom--Cook than a Comba or baseline approach (this is a savings of more than 99$\%$). For most ``crypto'' sized numbers this -algorithm is not practical as Karatsuba has a much lower cutoff point. - -First we split $a$ and $b$ into three roughly equal portions. This has been accomplished (lines @40,mod@ to @69,rshd@) with -combinations of mp\_rshd() and mp\_mod\_2d() function calls. At this point $a = a2 \cdot \beta^2 + a1 \cdot \beta + a0$ and similiarly -for $b$. - -Next we compute the five points $w0, w1, w2, w3$ and $w4$. Recall that $w0$ and $w4$ can be computed directly from the portions so -we get those out of the way first (lines @72,mul@ and @77,mul@). Next we compute $w1, w2$ and $w3$ using Horners method. - -After this point we solve for the actual values of $w1, w2$ and $w3$ by reducing the $5 \times 5$ system which is relatively -straight forward. - -\subsection{Signed Multiplication} -Now that algorithms to handle multiplications of every useful dimensions have been developed, a rather simple finishing touch is required. So far all -of the multiplication algorithms have been unsigned multiplications which leaves only a signed multiplication algorithm to be established. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_mul}. \\ -\textbf{Input}. mp\_int $a$ and mp\_int $b$ \\ -\textbf{Output}. $c \leftarrow a \cdot b$ \\ -\hline \\ -1. If $a.sign = b.sign$ then \\ -\hspace{3mm}1.1 $sign = MP\_ZPOS$ \\ -2. else \\ -\hspace{3mm}2.1 $sign = MP\_ZNEG$ \\ -3. If min$(a.used, b.used) \ge TOOM\_MUL\_CUTOFF$ then \\ -\hspace{3mm}3.1 $c \leftarrow a \cdot b$ using algorithm mp\_toom\_mul \\ -4. else if min$(a.used, b.used) \ge KARATSUBA\_MUL\_CUTOFF$ then \\ -\hspace{3mm}4.1 $c \leftarrow a \cdot b$ using algorithm mp\_karatsuba\_mul \\ -5. else \\ -\hspace{3mm}5.1 $digs \leftarrow a.used + b.used + 1$ \\ -\hspace{3mm}5.2 If $digs < MP\_ARRAY$ and min$(a.used, b.used) \le \delta$ then \\ -\hspace{6mm}5.2.1 $c \leftarrow a \cdot b \mbox{ (mod }\beta^{digs}\mbox{)}$ using algorithm fast\_s\_mp\_mul\_digs. \\ -\hspace{3mm}5.3 else \\ -\hspace{6mm}5.3.1 $c \leftarrow a \cdot b \mbox{ (mod }\beta^{digs}\mbox{)}$ using algorithm s\_mp\_mul\_digs. \\ -6. $c.sign \leftarrow sign$ \\ -7. Return the result of the unsigned multiplication performed. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_mul} -\end{figure} - -\textbf{Algorithm mp\_mul.} -This algorithm performs the signed multiplication of two inputs. It will make use of any of the three unsigned multiplication algorithms -available when the input is of appropriate size. The \textbf{sign} of the result is not set until the end of the algorithm since algorithm -s\_mp\_mul\_digs will clear it. - -EXAM,bn_mp_mul.c - -The implementation is rather simplistic and is not particularly noteworthy. Line @22,?@ computes the sign of the result using the ``?'' -operator from the C programming language. Line @37,<<@ computes $\delta$ using the fact that $1 << k$ is equal to $2^k$. - -\section{Squaring} -\label{sec:basesquare} - -Squaring is a special case of multiplication where both multiplicands are equal. At first it may seem like there is no significant optimization -available but in fact there is. Consider the multiplication of $576$ against $241$. In total there will be nine single precision multiplications -performed which are $1\cdot 6$, $1 \cdot 7$, $1 \cdot 5$, $4 \cdot 6$, $4 \cdot 7$, $4 \cdot 5$, $2 \cdot 6$, $2 \cdot 7$ and $2 \cdot 5$. Now consider -the multiplication of $123$ against $123$. The nine products are $3 \cdot 3$, $3 \cdot 2$, $3 \cdot 1$, $2 \cdot 3$, $2 \cdot 2$, $2 \cdot 1$, -$1 \cdot 3$, $1 \cdot 2$ and $1 \cdot 1$. On closer inspection some of the products are equivalent. For example, $3 \cdot 2 = 2 \cdot 3$ -and $3 \cdot 1 = 1 \cdot 3$. - -For any $n$-digit input, there are ${{\left (n^2 + n \right)}\over 2}$ possible unique single precision multiplications required compared to the $n^2$ -required for multiplication. The following diagram gives an example of the operations required. - -\begin{figure}[here] -\begin{center} -\begin{tabular}{ccccc|c} -&&1&2&3&\\ -$\times$ &&1&2&3&\\ -\hline && $3 \cdot 1$ & $3 \cdot 2$ & $3 \cdot 3$ & Row 0\\ - & $2 \cdot 1$ & $2 \cdot 2$ & $2 \cdot 3$ && Row 1 \\ - $1 \cdot 1$ & $1 \cdot 2$ & $1 \cdot 3$ &&& Row 2 \\ -\end{tabular} -\end{center} -\caption{Squaring Optimization Diagram} -\end{figure} - -MARK,SQUARE -Starting from zero and numbering the columns from right to left a very simple pattern becomes obvious. For the purposes of this discussion let $x$ -represent the number being squared. The first observation is that in row $k$ the $2k$'th column of the product has a $\left (x_k \right)^2$ term in it. - -The second observation is that every column $j$ in row $k$ where $j \ne 2k$ is part of a double product. Every non-square term of a column will -appear twice hence the name ``double product''. Every odd column is made up entirely of double products. In fact every column is made up of double -products and at most one square (\textit{see the exercise section}). - -The third and final observation is that for row $k$ the first unique non-square term, that is, one that hasn't already appeared in an earlier row, -occurs at column $2k + 1$. For example, on row $1$ of the previous squaring, column one is part of the double product with column one from row zero. -Column two of row one is a square and column three is the first unique column. - -\subsection{The Baseline Squaring Algorithm} -The baseline squaring algorithm is meant to be a catch-all squaring algorithm. It will handle any of the input sizes that the faster routines -will not handle. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{s\_mp\_sqr}. \\ -\textbf{Input}. mp\_int $a$ \\ -\textbf{Output}. $b \leftarrow a^2$ \\ -\hline \\ -1. Init a temporary mp\_int of at least $2 \cdot a.used +1$ digits. (\textit{mp\_init\_size}) \\ -2. If step 1 failed return(\textit{MP\_MEM}) \\ -3. $t.used \leftarrow 2 \cdot a.used + 1$ \\ -4. For $ix$ from 0 to $a.used - 1$ do \\ -\hspace{3mm}Calculate the square. \\ -\hspace{3mm}4.1 $\hat r \leftarrow t_{2ix} + \left (a_{ix} \right )^2$ \\ -\hspace{3mm}4.2 $t_{2ix} \leftarrow \hat r \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{3mm}Calculate the double products after the square. \\ -\hspace{3mm}4.3 $u \leftarrow \lfloor \hat r / \beta \rfloor$ \\ -\hspace{3mm}4.4 For $iy$ from $ix + 1$ to $a.used - 1$ do \\ -\hspace{6mm}4.4.1 $\hat r \leftarrow 2 \cdot a_{ix}a_{iy} + t_{ix + iy} + u$ \\ -\hspace{6mm}4.4.2 $t_{ix + iy} \leftarrow \hat r \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{6mm}4.4.3 $u \leftarrow \lfloor \hat r / \beta \rfloor$ \\ -\hspace{3mm}Set the last carry. \\ -\hspace{3mm}4.5 While $u > 0$ do \\ -\hspace{6mm}4.5.1 $iy \leftarrow iy + 1$ \\ -\hspace{6mm}4.5.2 $\hat r \leftarrow t_{ix + iy} + u$ \\ -\hspace{6mm}4.5.3 $t_{ix + iy} \leftarrow \hat r \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{6mm}4.5.4 $u \leftarrow \lfloor \hat r / \beta \rfloor$ \\ -5. Clamp excess digits of $t$. (\textit{mp\_clamp}) \\ -6. Exchange $b$ and $t$. \\ -7. Clear $t$ (\textit{mp\_clear}) \\ -8. Return(\textit{MP\_OKAY}) \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm s\_mp\_sqr} -\end{figure} - -\textbf{Algorithm s\_mp\_sqr.} -This algorithm computes the square of an input using the three observations on squaring. It is based fairly faithfully on algorithm 14.16 of HAC -\cite[pp.596-597]{HAC}. Similar to algorithm s\_mp\_mul\_digs, a temporary mp\_int is allocated to hold the result of the squaring. This allows the -destination mp\_int to be the same as the source mp\_int. - -The outer loop of this algorithm begins on step 4. It is best to think of the outer loop as walking down the rows of the partial results, while -the inner loop computes the columns of the partial result. Step 4.1 and 4.2 compute the square term for each row, and step 4.3 and 4.4 propagate -the carry and compute the double products. - -The requirement that a mp\_word be able to represent the range $0 \le x < 2 \beta^2$ arises from this -very algorithm. The product $a_{ix}a_{iy}$ will lie in the range $0 \le x \le \beta^2 - 2\beta + 1$ which is obviously less than $\beta^2$ meaning that -when it is multiplied by two, it can be properly represented by a mp\_word. - -Similar to algorithm s\_mp\_mul\_digs, after every pass of the inner loop, the destination is correctly set to the sum of all of the partial -results calculated so far. This involves expensive carry propagation which will be eliminated in the next algorithm. - -EXAM,bn_s_mp_sqr.c - -Inside the outer loop (line @32,for@) the square term is calculated on line @35,r =@. The carry (line @42,>>@) has been -extracted from the mp\_word accumulator using a right shift. Aliases for $a_{ix}$ and $t_{ix+iy}$ are initialized -(lines @45,tmpx@ and @48,tmpt@) to simplify the inner loop. The doubling is performed using two -additions (line @57,r + r@) since it is usually faster than shifting, if not at least as fast. - -The important observation is that the inner loop does not begin at $iy = 0$ like for multiplication. As such the inner loops -get progressively shorter as the algorithm proceeds. This is what leads to the savings compared to using a multiplication to -square a number. - -\subsection{Faster Squaring by the ``Comba'' Method} -A major drawback to the baseline method is the requirement for single precision shifting inside the $O(n^2)$ nested loop. Squaring has an additional -drawback that it must double the product inside the inner loop as well. As for multiplication, the Comba technique can be used to eliminate these -performance hazards. - -The first obvious solution is to make an array of mp\_words which will hold all of the columns. This will indeed eliminate all of the carry -propagation operations from the inner loop. However, the inner product must still be doubled $O(n^2)$ times. The solution stems from the simple fact -that $2a + 2b + 2c = 2(a + b + c)$. That is the sum of all of the double products is equal to double the sum of all the products. For example, -$ab + ba + ac + ca = 2ab + 2ac = 2(ab + ac)$. - -However, we cannot simply double all of the columns, since the squares appear only once per row. The most practical solution is to have two -mp\_word arrays. One array will hold the squares and the other array will hold the double products. With both arrays the doubling and -carry propagation can be moved to a $O(n)$ work level outside the $O(n^2)$ level. In this case, we have an even simpler solution in mind. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{fast\_s\_mp\_sqr}. \\ -\textbf{Input}. mp\_int $a$ \\ -\textbf{Output}. $b \leftarrow a^2$ \\ -\hline \\ -Place an array of \textbf{MP\_WARRAY} mp\_digits named $W$ on the stack. \\ -1. If $b.alloc < 2a.used + 1$ then grow $b$ to $2a.used + 1$ digits. (\textit{mp\_grow}). \\ -2. If step 1 failed return(\textit{MP\_MEM}). \\ -\\ -3. $pa \leftarrow 2 \cdot a.used$ \\ -4. $\hat W1 \leftarrow 0$ \\ -5. for $ix$ from $0$ to $pa - 1$ do \\ -\hspace{3mm}5.1 $\_ \hat W \leftarrow 0$ \\ -\hspace{3mm}5.2 $ty \leftarrow \mbox{MIN}(a.used - 1, ix)$ \\ -\hspace{3mm}5.3 $tx \leftarrow ix - ty$ \\ -\hspace{3mm}5.4 $iy \leftarrow \mbox{MIN}(a.used - tx, ty + 1)$ \\ -\hspace{3mm}5.5 $iy \leftarrow \mbox{MIN}(iy, \lfloor \left (ty - tx + 1 \right )/2 \rfloor)$ \\ -\hspace{3mm}5.6 for $iz$ from $0$ to $iz - 1$ do \\ -\hspace{6mm}5.6.1 $\_ \hat W \leftarrow \_ \hat W + a_{tx + iz}a_{ty - iz}$ \\ -\hspace{3mm}5.7 $\_ \hat W \leftarrow 2 \cdot \_ \hat W + \hat W1$ \\ -\hspace{3mm}5.8 if $ix$ is even then \\ -\hspace{6mm}5.8.1 $\_ \hat W \leftarrow \_ \hat W + \left ( a_{\lfloor ix/2 \rfloor}\right )^2$ \\ -\hspace{3mm}5.9 $W_{ix} \leftarrow \_ \hat W (\mbox{mod }\beta)$ \\ -\hspace{3mm}5.10 $\hat W1 \leftarrow \lfloor \_ \hat W / \beta \rfloor$ \\ -\\ -6. $oldused \leftarrow b.used$ \\ -7. $b.used \leftarrow 2 \cdot a.used$ \\ -8. for $ix$ from $0$ to $pa - 1$ do \\ -\hspace{3mm}8.1 $b_{ix} \leftarrow W_{ix}$ \\ -9. for $ix$ from $pa$ to $oldused - 1$ do \\ -\hspace{3mm}9.1 $b_{ix} \leftarrow 0$ \\ -10. Clamp excess digits from $b$. (\textit{mp\_clamp}) \\ -11. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm fast\_s\_mp\_sqr} -\end{figure} - -\textbf{Algorithm fast\_s\_mp\_sqr.} -This algorithm computes the square of an input using the Comba technique. It is designed to be a replacement for algorithm -s\_mp\_sqr when the number of input digits is less than \textbf{MP\_WARRAY} and less than $\delta \over 2$. -This algorithm is very similar to the Comba multiplier except with a few key differences we shall make note of. - -First, we have an accumulator and carry variables $\_ \hat W$ and $\hat W1$ respectively. This is because the inner loop -products are to be doubled. If we had added the previous carry in we would be doubling too much. Next we perform an -addition MIN condition on $iy$ (step 5.5) to prevent overlapping digits. For example, $a_3 \cdot a_5$ is equal -$a_5 \cdot a_3$. Whereas in the multiplication case we would have $5 < a.used$ and $3 \ge 0$ is maintained since we double the sum -of the products just outside the inner loop we have to avoid doing this. This is also a good thing since we perform -fewer multiplications and the routine ends up being faster. - -Finally the last difference is the addition of the ``square'' term outside the inner loop (step 5.8). We add in the square -only to even outputs and it is the square of the term at the $\lfloor ix / 2 \rfloor$ position. - -EXAM,bn_fast_s_mp_sqr.c - -This implementation is essentially a copy of Comba multiplication with the appropriate changes added to make it faster for -the special case of squaring. - -\subsection{Polynomial Basis Squaring} -The same algorithm that performs optimal polynomial basis multiplication can be used to perform polynomial basis squaring. The minor exception -is that $\zeta_y = f(y)g(y)$ is actually equivalent to $\zeta_y = f(y)^2$ since $f(y) = g(y)$. Instead of performing $2n + 1$ -multiplications to find the $\zeta$ relations, squaring operations are performed instead. - -\subsection{Karatsuba Squaring} -Let $f(x) = ax + b$ represent the polynomial basis representation of a number to square. -Let $h(x) = \left ( f(x) \right )^2$ represent the square of the polynomial. The Karatsuba equation can be modified to square a -number with the following equation. - -\begin{equation} -h(x) = a^2x^2 + \left ((a + b)^2 - (a^2 + b^2) \right )x + b^2 -\end{equation} - -Upon closer inspection this equation only requires the calculation of three half-sized squares: $a^2$, $b^2$ and $(a + b)^2$. As in -Karatsuba multiplication, this algorithm can be applied recursively on the input and will achieve an asymptotic running time of -$O \left ( n^{lg(3)} \right )$. - -If the asymptotic times of Karatsuba squaring and multiplication are the same, why not simply use the multiplication algorithm -instead? The answer to this arises from the cutoff point for squaring. As in multiplication there exists a cutoff point, at which the -time required for a Comba based squaring and a Karatsuba based squaring meet. Due to the overhead inherent in the Karatsuba method, the cutoff -point is fairly high. For example, on an AMD Athlon XP processor with $\beta = 2^{28}$, the cutoff point is around 127 digits. - -Consider squaring a 200 digit number with this technique. It will be split into two 100 digit halves which are subsequently squared. -The 100 digit halves will not be squared using Karatsuba, but instead using the faster Comba based squaring algorithm. If Karatsuba multiplication -were used instead, the 100 digit numbers would be squared with a slower Comba based multiplication. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_karatsuba\_sqr}. \\ -\textbf{Input}. mp\_int $a$ \\ -\textbf{Output}. $b \leftarrow a^2$ \\ -\hline \\ -1. Initialize the following temporary mp\_ints: $x0$, $x1$, $t1$, $t2$, $x0x0$ and $x1x1$. \\ -2. If any of the initializations on step 1 failed return(\textit{MP\_MEM}). \\ -\\ -Split the input. e.g. $a = x1\beta^B + x0$ \\ -3. $B \leftarrow \lfloor a.used / 2 \rfloor$ \\ -4. $x0 \leftarrow a \mbox{ (mod }\beta^B\mbox{)}$ (\textit{mp\_mod\_2d}) \\ -5. $x1 \leftarrow \lfloor a / \beta^B \rfloor$ (\textit{mp\_lshd}) \\ -\\ -Calculate the three squares. \\ -6. $x0x0 \leftarrow x0^2$ (\textit{mp\_sqr}) \\ -7. $x1x1 \leftarrow x1^2$ \\ -8. $t1 \leftarrow x1 + x0$ (\textit{s\_mp\_add}) \\ -9. $t1 \leftarrow t1^2$ \\ -\\ -Compute the middle term. \\ -10. $t2 \leftarrow x0x0 + x1x1$ (\textit{s\_mp\_add}) \\ -11. $t1 \leftarrow t1 - t2$ \\ -\\ -Compute final product. \\ -12. $t1 \leftarrow t1\beta^B$ (\textit{mp\_lshd}) \\ -13. $x1x1 \leftarrow x1x1\beta^{2B}$ \\ -14. $t1 \leftarrow t1 + x0x0$ \\ -15. $b \leftarrow t1 + x1x1$ \\ -16. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_karatsuba\_sqr} -\end{figure} - -\textbf{Algorithm mp\_karatsuba\_sqr.} -This algorithm computes the square of an input $a$ using the Karatsuba technique. This algorithm is very similar to the Karatsuba based -multiplication algorithm with the exception that the three half-size multiplications have been replaced with three half-size squarings. - -The radix point for squaring is simply placed exactly in the middle of the digits when the input has an odd number of digits, otherwise it is -placed just below the middle. Step 3, 4 and 5 compute the two halves required using $B$ -as the radix point. The first two squares in steps 6 and 7 are rather straightforward while the last square is of a more compact form. - -By expanding $\left (x1 + x0 \right )^2$, the $x1^2$ and $x0^2$ terms in the middle disappear, that is $(x0 - x1)^2 - (x1^2 + x0^2) = 2 \cdot x0 \cdot x1$. -Now if $5n$ single precision additions and a squaring of $n$-digits is faster than multiplying two $n$-digit numbers and doubling then -this method is faster. Assuming no further recursions occur, the difference can be estimated with the following inequality. - -Let $p$ represent the cost of a single precision addition and $q$ the cost of a single precision multiplication both in terms of time\footnote{Or -machine clock cycles.}. - -\begin{equation} -5pn +{{q(n^2 + n)} \over 2} \le pn + qn^2 -\end{equation} - -For example, on an AMD Athlon XP processor $p = {1 \over 3}$ and $q = 6$. This implies that the following inequality should hold. -\begin{center} -\begin{tabular}{rcl} -${5n \over 3} + 3n^2 + 3n$ & $<$ & ${n \over 3} + 6n^2$ \\ -${5 \over 3} + 3n + 3$ & $<$ & ${1 \over 3} + 6n$ \\ -${13 \over 9}$ & $<$ & $n$ \\ -\end{tabular} -\end{center} - -This results in a cutoff point around $n = 2$. As a consequence it is actually faster to compute the middle term the ``long way'' on processors -where multiplication is substantially slower\footnote{On the Athlon there is a 1:17 ratio between clock cycles for addition and multiplication. On -the Intel P4 processor this ratio is 1:29 making this method even more beneficial. The only common exception is the ARMv4 processor which has a -ratio of 1:7. } than simpler operations such as addition. - -EXAM,bn_mp_karatsuba_sqr.c - -This implementation is largely based on the implementation of algorithm mp\_karatsuba\_mul. It uses the same inline style to copy and -shift the input into the two halves. The loop from line @54,{@ to line @70,}@ has been modified since only one input exists. The \textbf{used} -count of both $x0$ and $x1$ is fixed up and $x0$ is clamped before the calculations begin. At this point $x1$ and $x0$ are valid equivalents -to the respective halves as if mp\_rshd and mp\_mod\_2d had been used. - -By inlining the copy and shift operations the cutoff point for Karatsuba multiplication can be lowered. On the Athlon the cutoff point -is exactly at the point where Comba squaring can no longer be used (\textit{128 digits}). On slower processors such as the Intel P4 -it is actually below the Comba limit (\textit{at 110 digits}). - -This routine uses the same error trap coding style as mp\_karatsuba\_sqr. As the temporary variables are initialized errors are -redirected to the error trap higher up. If the algorithm completes without error the error code is set to \textbf{MP\_OKAY} and -mp\_clears are executed normally. - -\subsection{Toom-Cook Squaring} -The Toom-Cook squaring algorithm mp\_toom\_sqr is heavily based on the algorithm mp\_toom\_mul with the exception that squarings are used -instead of multiplication to find the five relations. The reader is encouraged to read the description of the latter algorithm and try to -derive their own Toom-Cook squaring algorithm. - -\subsection{High Level Squaring} -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_sqr}. \\ -\textbf{Input}. mp\_int $a$ \\ -\textbf{Output}. $b \leftarrow a^2$ \\ -\hline \\ -1. If $a.used \ge TOOM\_SQR\_CUTOFF$ then \\ -\hspace{3mm}1.1 $b \leftarrow a^2$ using algorithm mp\_toom\_sqr \\ -2. else if $a.used \ge KARATSUBA\_SQR\_CUTOFF$ then \\ -\hspace{3mm}2.1 $b \leftarrow a^2$ using algorithm mp\_karatsuba\_sqr \\ -3. else \\ -\hspace{3mm}3.1 $digs \leftarrow a.used + b.used + 1$ \\ -\hspace{3mm}3.2 If $digs < MP\_ARRAY$ and $a.used \le \delta$ then \\ -\hspace{6mm}3.2.1 $b \leftarrow a^2$ using algorithm fast\_s\_mp\_sqr. \\ -\hspace{3mm}3.3 else \\ -\hspace{6mm}3.3.1 $b \leftarrow a^2$ using algorithm s\_mp\_sqr. \\ -4. $b.sign \leftarrow MP\_ZPOS$ \\ -5. Return the result of the unsigned squaring performed. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_sqr} -\end{figure} - -\textbf{Algorithm mp\_sqr.} -This algorithm computes the square of the input using one of four different algorithms. If the input is very large and has at least -\textbf{TOOM\_SQR\_CUTOFF} or \textbf{KARATSUBA\_SQR\_CUTOFF} digits then either the Toom-Cook or the Karatsuba Squaring algorithm is used. If -neither of the polynomial basis algorithms should be used then either the Comba or baseline algorithm is used. - -EXAM,bn_mp_sqr.c - -\section*{Exercises} -\begin{tabular}{cl} -$\left [ 3 \right ] $ & Devise an efficient algorithm for selection of the radix point to handle inputs \\ - & that have different number of digits in Karatsuba multiplication. \\ - & \\ -$\left [ 2 \right ] $ & In ~SQUARE~ the fact that every column of a squaring is made up \\ - & of double products and at most one square is stated. Prove this statement. \\ - & \\ -$\left [ 3 \right ] $ & Prove the equation for Karatsuba squaring. \\ - & \\ -$\left [ 1 \right ] $ & Prove that Karatsuba squaring requires $O \left (n^{lg(3)} \right )$ time. \\ - & \\ -$\left [ 2 \right ] $ & Determine the minimal ratio between addition and multiplication clock cycles \\ - & required for equation $6.7$ to be true. \\ - & \\ -$\left [ 3 \right ] $ & Implement a threaded version of Comba multiplication (and squaring) where you \\ - & compute subsets of the columns in each thread. Determine a cutoff point where \\ - & it is effective and add the logic to mp\_mul() and mp\_sqr(). \\ - &\\ -$\left [ 4 \right ] $ & Same as the previous but also modify the Karatsuba and Toom-Cook. You must \\ - & increase the throughput of mp\_exptmod() for random odd moduli in the range \\ - & $512 \ldots 4096$ bits significantly ($> 2x$) to complete this challenge. \\ - & \\ -\end{tabular} - -\chapter{Modular Reduction} -MARK,REDUCTION -\section{Basics of Modular Reduction} -\index{modular residue} -Modular reduction is an operation that arises quite often within public key cryptography algorithms and various number theoretic algorithms, -such as factoring. Modular reduction algorithms are the third class of algorithms of the ``multipliers'' set. A number $a$ is said to be \textit{reduced} -modulo another number $b$ by finding the remainder of the division $a/b$. Full integer division with remainder is a topic to be covered -in~\ref{sec:division}. - -Modular reduction is equivalent to solving for $r$ in the following equation. $a = bq + r$ where $q = \lfloor a/b \rfloor$. The result -$r$ is said to be ``congruent to $a$ modulo $b$'' which is also written as $r \equiv a \mbox{ (mod }b\mbox{)}$. In other vernacular $r$ is known as the -``modular residue'' which leads to ``quadratic residue''\footnote{That's fancy talk for $b \equiv a^2 \mbox{ (mod }p\mbox{)}$.} and -other forms of residues. - -Modular reductions are normally used to create either finite groups, rings or fields. The most common usage for performance driven modular reductions -is in modular exponentiation algorithms. That is to compute $d = a^b \mbox{ (mod }c\mbox{)}$ as fast as possible. This operation is used in the -RSA and Diffie-Hellman public key algorithms, for example. Modular multiplication and squaring also appears as a fundamental operation in -elliptic curve cryptographic algorithms. As will be discussed in the subsequent chapter there exist fast algorithms for computing modular -exponentiations without having to perform (\textit{in this example}) $b - 1$ multiplications. These algorithms will produce partial results in the -range $0 \le x < c^2$ which can be taken advantage of to create several efficient algorithms. They have also been used to create redundancy check -algorithms known as CRCs, error correction codes such as Reed-Solomon and solve a variety of number theoeretic problems. - -\section{The Barrett Reduction} -The Barrett reduction algorithm \cite{BARRETT} was inspired by fast division algorithms which multiply by the reciprocal to emulate -division. Barretts observation was that the residue $c$ of $a$ modulo $b$ is equal to - -\begin{equation} -c = a - b \cdot \lfloor a/b \rfloor -\end{equation} - -Since algorithms such as modular exponentiation would be using the same modulus extensively, typical DSP\footnote{It is worth noting that Barrett's paper -targeted the DSP56K processor.} intuition would indicate the next step would be to replace $a/b$ by a multiplication by the reciprocal. However, -DSP intuition on its own will not work as these numbers are considerably larger than the precision of common DSP floating point data types. -It would take another common optimization to optimize the algorithm. - -\subsection{Fixed Point Arithmetic} -The trick used to optimize the above equation is based on a technique of emulating floating point data types with fixed precision integers. Fixed -point arithmetic would become very popular as it greatly optimize the ``3d-shooter'' genre of games in the mid 1990s when floating point units were -fairly slow if not unavailable. The idea behind fixed point arithmetic is to take a normal $k$-bit integer data type and break it into $p$-bit -integer and a $q$-bit fraction part (\textit{where $p+q = k$}). - -In this system a $k$-bit integer $n$ would actually represent $n/2^q$. For example, with $q = 4$ the integer $n = 37$ would actually represent the -value $2.3125$. To multiply two fixed point numbers the integers are multiplied using traditional arithmetic and subsequently normalized by -moving the implied decimal point back to where it should be. For example, with $q = 4$ to multiply the integers $9$ and $5$ they must be converted -to fixed point first by multiplying by $2^q$. Let $a = 9(2^q)$ represent the fixed point representation of $9$ and $b = 5(2^q)$ represent the -fixed point representation of $5$. The product $ab$ is equal to $45(2^{2q})$ which when normalized by dividing by $2^q$ produces $45(2^q)$. - -This technique became popular since a normal integer multiplication and logical shift right are the only required operations to perform a multiplication -of two fixed point numbers. Using fixed point arithmetic, division can be easily approximated by multiplying by the reciprocal. If $2^q$ is -equivalent to one than $2^q/b$ is equivalent to the fixed point approximation of $1/b$ using real arithmetic. Using this fact dividing an integer -$a$ by another integer $b$ can be achieved with the following expression. - -\begin{equation} -\lfloor a / b \rfloor \mbox{ }\approx\mbox{ } \lfloor (a \cdot \lfloor 2^q / b \rfloor)/2^q \rfloor -\end{equation} - -The precision of the division is proportional to the value of $q$. If the divisor $b$ is used frequently as is the case with -modular exponentiation pre-computing $2^q/b$ will allow a division to be performed with a multiplication and a right shift. Both operations -are considerably faster than division on most processors. - -Consider dividing $19$ by $5$. The correct result is $\lfloor 19/5 \rfloor = 3$. With $q = 3$ the reciprocal is $\lfloor 2^q/5 \rfloor = 1$ which -leads to a product of $19$ which when divided by $2^q$ produces $2$. However, with $q = 4$ the reciprocal is $\lfloor 2^q/5 \rfloor = 3$ and -the result of the emulated division is $\lfloor 3 \cdot 19 / 2^q \rfloor = 3$ which is correct. The value of $2^q$ must be close to or ideally -larger than the dividend. In effect if $a$ is the dividend then $q$ should allow $0 \le \lfloor a/2^q \rfloor \le 1$ in order for this approach -to work correctly. Plugging this form of divison into the original equation the following modular residue equation arises. - -\begin{equation} -c = a - b \cdot \lfloor (a \cdot \lfloor 2^q / b \rfloor)/2^q \rfloor -\end{equation} - -Using the notation from \cite{BARRETT} the value of $\lfloor 2^q / b \rfloor$ will be represented by the $\mu$ symbol. Using the $\mu$ -variable also helps re-inforce the idea that it is meant to be computed once and re-used. - -\begin{equation} -c = a - b \cdot \lfloor (a \cdot \mu)/2^q \rfloor -\end{equation} - -Provided that $2^q \ge a$ this algorithm will produce a quotient that is either exactly correct or off by a value of one. In the context of Barrett -reduction the value of $a$ is bound by $0 \le a \le (b - 1)^2$ meaning that $2^q \ge b^2$ is sufficient to ensure the reciprocal will have enough -precision. - -Let $n$ represent the number of digits in $b$. This algorithm requires approximately $2n^2$ single precision multiplications to produce the quotient and -another $n^2$ single precision multiplications to find the residue. In total $3n^2$ single precision multiplications are required to -reduce the number. - -For example, if $b = 1179677$ and $q = 41$ ($2^q > b^2$), then the reciprocal $\mu$ is equal to $\lfloor 2^q / b \rfloor = 1864089$. Consider reducing -$a = 180388626447$ modulo $b$ using the above reduction equation. The quotient using the new formula is $\lfloor (a \cdot \mu) / 2^q \rfloor = 152913$. -By subtracting $152913b$ from $a$ the correct residue $a \equiv 677346 \mbox{ (mod }b\mbox{)}$ is found. - -\subsection{Choosing a Radix Point} -Using the fixed point representation a modular reduction can be performed with $3n^2$ single precision multiplications. If that were the best -that could be achieved a full division\footnote{A division requires approximately $O(2cn^2)$ single precision multiplications for a small value of $c$. -See~\ref{sec:division} for further details.} might as well be used in its place. The key to optimizing the reduction is to reduce the precision of -the initial multiplication that finds the quotient. - -Let $a$ represent the number of which the residue is sought. Let $b$ represent the modulus used to find the residue. Let $m$ represent -the number of digits in $b$. For the purposes of this discussion we will assume that the number of digits in $a$ is $2m$, which is generally true if -two $m$-digit numbers have been multiplied. Dividing $a$ by $b$ is the same as dividing a $2m$ digit integer by a $m$ digit integer. Digits below the -$m - 1$'th digit of $a$ will contribute at most a value of $1$ to the quotient because $\beta^k < b$ for any $0 \le k \le m - 1$. Another way to -express this is by re-writing $a$ as two parts. If $a' \equiv a \mbox{ (mod }b^m\mbox{)}$ and $a'' = a - a'$ then -${a \over b} \equiv {{a' + a''} \over b}$ which is equivalent to ${a' \over b} + {a'' \over b}$. Since $a'$ is bound to be less than $b$ the quotient -is bound by $0 \le {a' \over b} < 1$. - -Since the digits of $a'$ do not contribute much to the quotient the observation is that they might as well be zero. However, if the digits -``might as well be zero'' they might as well not be there in the first place. Let $q_0 = \lfloor a/\beta^{m-1} \rfloor$ represent the input -with the irrelevant digits trimmed. Now the modular reduction is trimmed to the almost equivalent equation - -\begin{equation} -c = a - b \cdot \lfloor (q_0 \cdot \mu) / \beta^{m+1} \rfloor -\end{equation} - -Note that the original divisor $2^q$ has been replaced with $\beta^{m+1}$ where in this case $q$ is a multiple of $lg(\beta)$. Also note that the -exponent on the divisor when added to the amount $q_0$ was shifted by equals $2m$. If the optimization had not been performed the divisor -would have the exponent $2m$ so in the end the exponents do ``add up''. Using the above equation the quotient -$\lfloor (q_0 \cdot \mu) / \beta^{m+1} \rfloor$ can be off from the true quotient by at most two. The original fixed point quotient can be off -by as much as one (\textit{provided the radix point is chosen suitably}) and now that the lower irrelevent digits have been trimmed the quotient -can be off by an additional value of one for a total of at most two. This implies that -$0 \le a - b \cdot \lfloor (q_0 \cdot \mu) / \beta^{m+1} \rfloor < 3b$. By first subtracting $b$ times the quotient and then conditionally subtracting -$b$ once or twice the residue is found. - -The quotient is now found using $(m + 1)(m) = m^2 + m$ single precision multiplications and the residue with an additional $m^2$ single -precision multiplications, ignoring the subtractions required. In total $2m^2 + m$ single precision multiplications are required to find the residue. -This is considerably faster than the original attempt. - -For example, let $\beta = 10$ represent the radix of the digits. Let $b = 9999$ represent the modulus which implies $m = 4$. Let $a = 99929878$ -represent the value of which the residue is desired. In this case $q = 8$ since $10^7 < 9999^2$ meaning that $\mu = \lfloor \beta^{q}/b \rfloor = 10001$. -With the new observation the multiplicand for the quotient is equal to $q_0 = \lfloor a / \beta^{m - 1} \rfloor = 99929$. The quotient is then -$\lfloor (q_0 \cdot \mu) / \beta^{m+1} \rfloor = 9993$. Subtracting $9993b$ from $a$ and the correct residue $a \equiv 9871 \mbox{ (mod }b\mbox{)}$ -is found. - -\subsection{Trimming the Quotient} -So far the reduction algorithm has been optimized from $3m^2$ single precision multiplications down to $2m^2 + m$ single precision multiplications. As -it stands now the algorithm is already fairly fast compared to a full integer division algorithm. However, there is still room for -optimization. - -After the first multiplication inside the quotient ($q_0 \cdot \mu$) the value is shifted right by $m + 1$ places effectively nullifying the lower -half of the product. It would be nice to be able to remove those digits from the product to effectively cut down the number of single precision -multiplications. If the number of digits in the modulus $m$ is far less than $\beta$ a full product is not required for the algorithm to work properly. -In fact the lower $m - 2$ digits will not affect the upper half of the product at all and do not need to be computed. - -The value of $\mu$ is a $m$-digit number and $q_0$ is a $m + 1$ digit number. Using a full multiplier $(m + 1)(m) = m^2 + m$ single precision -multiplications would be required. Using a multiplier that will only produce digits at and above the $m - 1$'th digit reduces the number -of single precision multiplications to ${m^2 + m} \over 2$ single precision multiplications. - -\subsection{Trimming the Residue} -After the quotient has been calculated it is used to reduce the input. As previously noted the algorithm is not exact and it can be off by a small -multiple of the modulus, that is $0 \le a - b \cdot \lfloor (q_0 \cdot \mu) / \beta^{m+1} \rfloor < 3b$. If $b$ is $m$ digits than the -result of reduction equation is a value of at most $m + 1$ digits (\textit{provided $3 < \beta$}) implying that the upper $m - 1$ digits are -implicitly zero. - -The next optimization arises from this very fact. Instead of computing $b \cdot \lfloor (q_0 \cdot \mu) / \beta^{m+1} \rfloor$ using a full -$O(m^2)$ multiplication algorithm only the lower $m+1$ digits of the product have to be computed. Similarly the value of $a$ can -be reduced modulo $\beta^{m+1}$ before the multiple of $b$ is subtracted which simplifes the subtraction as well. A multiplication that produces -only the lower $m+1$ digits requires ${m^2 + 3m - 2} \over 2$ single precision multiplications. - -With both optimizations in place the algorithm is the algorithm Barrett proposed. It requires $m^2 + 2m - 1$ single precision multiplications which -is considerably faster than the straightforward $3m^2$ method. - -\subsection{The Barrett Algorithm} -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_reduce}. \\ -\textbf{Input}. mp\_int $a$, mp\_int $b$ and $\mu = \lfloor \beta^{2m}/b \rfloor, m = \lceil lg_{\beta}(b) \rceil, (0 \le a < b^2, b > 1)$ \\ -\textbf{Output}. $a \mbox{ (mod }b\mbox{)}$ \\ -\hline \\ -Let $m$ represent the number of digits in $b$. \\ -1. Make a copy of $a$ and store it in $q$. (\textit{mp\_init\_copy}) \\ -2. $q \leftarrow \lfloor q / \beta^{m - 1} \rfloor$ (\textit{mp\_rshd}) \\ -\\ -Produce the quotient. \\ -3. $q \leftarrow q \cdot \mu$ (\textit{note: only produce digits at or above $m-1$}) \\ -4. $q \leftarrow \lfloor q / \beta^{m + 1} \rfloor$ \\ -\\ -Subtract the multiple of modulus from the input. \\ -5. $a \leftarrow a \mbox{ (mod }\beta^{m+1}\mbox{)}$ (\textit{mp\_mod\_2d}) \\ -6. $q \leftarrow q \cdot b \mbox{ (mod }\beta^{m+1}\mbox{)}$ (\textit{s\_mp\_mul\_digs}) \\ -7. $a \leftarrow a - q$ (\textit{mp\_sub}) \\ -\\ -Add $\beta^{m+1}$ if a carry occured. \\ -8. If $a < 0$ then (\textit{mp\_cmp\_d}) \\ -\hspace{3mm}8.1 $q \leftarrow 1$ (\textit{mp\_set}) \\ -\hspace{3mm}8.2 $q \leftarrow q \cdot \beta^{m+1}$ (\textit{mp\_lshd}) \\ -\hspace{3mm}8.3 $a \leftarrow a + q$ \\ -\\ -Now subtract the modulus if the residue is too large (e.g. quotient too small). \\ -9. While $a \ge b$ do (\textit{mp\_cmp}) \\ -\hspace{3mm}9.1 $c \leftarrow a - b$ \\ -10. Clear $q$. \\ -11. Return(\textit{MP\_OKAY}) \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_reduce} -\end{figure} - -\textbf{Algorithm mp\_reduce.} -This algorithm will reduce the input $a$ modulo $b$ in place using the Barrett algorithm. It is loosely based on algorithm 14.42 of HAC -\cite[pp. 602]{HAC} which is based on the paper from Paul Barrett \cite{BARRETT}. The algorithm has several restrictions and assumptions which must -be adhered to for the algorithm to work. - -First the modulus $b$ is assumed to be positive and greater than one. If the modulus were less than or equal to one than subtracting -a multiple of it would either accomplish nothing or actually enlarge the input. The input $a$ must be in the range $0 \le a < b^2$ in order -for the quotient to have enough precision. If $a$ is the product of two numbers that were already reduced modulo $b$, this will not be a problem. -Technically the algorithm will still work if $a \ge b^2$ but it will take much longer to finish. The value of $\mu$ is passed as an argument to this -algorithm and is assumed to be calculated and stored before the algorithm is used. - -Recall that the multiplication for the quotient on step 3 must only produce digits at or above the $m-1$'th position. An algorithm called -$s\_mp\_mul\_high\_digs$ which has not been presented is used to accomplish this task. The algorithm is based on $s\_mp\_mul\_digs$ except that -instead of stopping at a given level of precision it starts at a given level of precision. This optimal algorithm can only be used if the number -of digits in $b$ is very much smaller than $\beta$. - -While it is known that -$a \ge b \cdot \lfloor (q_0 \cdot \mu) / \beta^{m+1} \rfloor$ only the lower $m+1$ digits are being used to compute the residue, so an implied -``borrow'' from the higher digits might leave a negative result. After the multiple of the modulus has been subtracted from $a$ the residue must be -fixed up in case it is negative. The invariant $\beta^{m+1}$ must be added to the residue to make it positive again. - -The while loop at step 9 will subtract $b$ until the residue is less than $b$. If the algorithm is performed correctly this step is -performed at most twice, and on average once. However, if $a \ge b^2$ than it will iterate substantially more times than it should. - -EXAM,bn_mp_reduce.c - -The first multiplication that determines the quotient can be performed by only producing the digits from $m - 1$ and up. This essentially halves -the number of single precision multiplications required. However, the optimization is only safe if $\beta$ is much larger than the number of digits -in the modulus. In the source code this is evaluated on lines @36,if@ to @44,}@ where algorithm s\_mp\_mul\_high\_digs is used when it is -safe to do so. - -\subsection{The Barrett Setup Algorithm} -In order to use algorithm mp\_reduce the value of $\mu$ must be calculated in advance. Ideally this value should be computed once and stored for -future use so that the Barrett algorithm can be used without delay. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_reduce\_setup}. \\ -\textbf{Input}. mp\_int $a$ ($a > 1$) \\ -\textbf{Output}. $\mu \leftarrow \lfloor \beta^{2m}/a \rfloor$ \\ -\hline \\ -1. $\mu \leftarrow 2^{2 \cdot lg(\beta) \cdot m}$ (\textit{mp\_2expt}) \\ -2. $\mu \leftarrow \lfloor \mu / b \rfloor$ (\textit{mp\_div}) \\ -3. Return(\textit{MP\_OKAY}) \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_reduce\_setup} -\end{figure} - -\textbf{Algorithm mp\_reduce\_setup.} -This algorithm computes the reciprocal $\mu$ required for Barrett reduction. First $\beta^{2m}$ is calculated as $2^{2 \cdot lg(\beta) \cdot m}$ which -is equivalent and much faster. The final value is computed by taking the integer quotient of $\lfloor \mu / b \rfloor$. - -EXAM,bn_mp_reduce_setup.c - -This simple routine calculates the reciprocal $\mu$ required by Barrett reduction. Note the extended usage of algorithm mp\_div where the variable -which would received the remainder is passed as NULL. As will be discussed in~\ref{sec:division} the division routine allows both the quotient and the -remainder to be passed as NULL meaning to ignore the value. - -\section{The Montgomery Reduction} -Montgomery reduction\footnote{Thanks to Niels Ferguson for his insightful explanation of the algorithm.} \cite{MONT} is by far the most interesting -form of reduction in common use. It computes a modular residue which is not actually equal to the residue of the input yet instead equal to a -residue times a constant. However, as perplexing as this may sound the algorithm is relatively simple and very efficient. - -Throughout this entire section the variable $n$ will represent the modulus used to form the residue. As will be discussed shortly the value of -$n$ must be odd. The variable $x$ will represent the quantity of which the residue is sought. Similar to the Barrett algorithm the input -is restricted to $0 \le x < n^2$. To begin the description some simple number theory facts must be established. - -\textbf{Fact 1.} Adding $n$ to $x$ does not change the residue since in effect it adds one to the quotient $\lfloor x / n \rfloor$. Another way -to explain this is that $n$ is (\textit{or multiples of $n$ are}) congruent to zero modulo $n$. Adding zero will not change the value of the residue. - -\textbf{Fact 2.} If $x$ is even then performing a division by two in $\Z$ is congruent to $x \cdot 2^{-1} \mbox{ (mod }n\mbox{)}$. Actually -this is an application of the fact that if $x$ is evenly divisible by any $k \in \Z$ then division in $\Z$ will be congruent to -multiplication by $k^{-1}$ modulo $n$. - -From these two simple facts the following simple algorithm can be derived. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{Montgomery Reduction}. \\ -\textbf{Input}. Integer $x$, $n$ and $k$ \\ -\textbf{Output}. $2^{-k}x \mbox{ (mod }n\mbox{)}$ \\ -\hline \\ -1. for $t$ from $1$ to $k$ do \\ -\hspace{3mm}1.1 If $x$ is odd then \\ -\hspace{6mm}1.1.1 $x \leftarrow x + n$ \\ -\hspace{3mm}1.2 $x \leftarrow x/2$ \\ -2. Return $x$. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm Montgomery Reduction} -\end{figure} - -The algorithm reduces the input one bit at a time using the two congruencies stated previously. Inside the loop $n$, which is odd, is -added to $x$ if $x$ is odd. This forces $x$ to be even which allows the division by two in $\Z$ to be congruent to a modular division by two. Since -$x$ is assumed to be initially much larger than $n$ the addition of $n$ will contribute an insignificant magnitude to $x$. Let $r$ represent the -final result of the Montgomery algorithm. If $k > lg(n)$ and $0 \le x < n^2$ then the final result is limited to -$0 \le r < \lfloor x/2^k \rfloor + n$. As a result at most a single subtraction is required to get the residue desired. - -\begin{figure}[here] -\begin{small} -\begin{center} -\begin{tabular}{|c|l|} -\hline \textbf{Step number ($t$)} & \textbf{Result ($x$)} \\ -\hline $1$ & $x + n = 5812$, $x/2 = 2906$ \\ -\hline $2$ & $x/2 = 1453$ \\ -\hline $3$ & $x + n = 1710$, $x/2 = 855$ \\ -\hline $4$ & $x + n = 1112$, $x/2 = 556$ \\ -\hline $5$ & $x/2 = 278$ \\ -\hline $6$ & $x/2 = 139$ \\ -\hline $7$ & $x + n = 396$, $x/2 = 198$ \\ -\hline $8$ & $x/2 = 99$ \\ -\hline $9$ & $x + n = 356$, $x/2 = 178$ \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Example of Montgomery Reduction (I)} -\label{fig:MONT1} -\end{figure} - -Consider the example in figure~\ref{fig:MONT1} which reduces $x = 5555$ modulo $n = 257$ when $k = 9$ (note $\beta^k = 512$ which is larger than $n$). The result of -the algorithm $r = 178$ is congruent to the value of $2^{-9} \cdot 5555 \mbox{ (mod }257\mbox{)}$. When $r$ is multiplied by $2^9$ modulo $257$ the correct residue -$r \equiv 158$ is produced. - -Let $k = \lfloor lg(n) \rfloor + 1$ represent the number of bits in $n$. The current algorithm requires $2k^2$ single precision shifts -and $k^2$ single precision additions. At this rate the algorithm is most certainly slower than Barrett reduction and not terribly useful. -Fortunately there exists an alternative representation of the algorithm. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{Montgomery Reduction} (modified I). \\ -\textbf{Input}. Integer $x$, $n$ and $k$ ($2^k > n$) \\ -\textbf{Output}. $2^{-k}x \mbox{ (mod }n\mbox{)}$ \\ -\hline \\ -1. for $t$ from $1$ to $k$ do \\ -\hspace{3mm}1.1 If the $t$'th bit of $x$ is one then \\ -\hspace{6mm}1.1.1 $x \leftarrow x + 2^tn$ \\ -2. Return $x/2^k$. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm Montgomery Reduction (modified I)} -\end{figure} - -This algorithm is equivalent since $2^tn$ is a multiple of $n$ and the lower $k$ bits of $x$ are zero by step 2. The number of single -precision shifts has now been reduced from $2k^2$ to $k^2 + k$ which is only a small improvement. - -\begin{figure}[here] -\begin{small} -\begin{center} -\begin{tabular}{|c|l|r|} -\hline \textbf{Step number ($t$)} & \textbf{Result ($x$)} & \textbf{Result ($x$) in Binary} \\ -\hline -- & $5555$ & $1010110110011$ \\ -\hline $1$ & $x + 2^{0}n = 5812$ & $1011010110100$ \\ -\hline $2$ & $5812$ & $1011010110100$ \\ -\hline $3$ & $x + 2^{2}n = 6840$ & $1101010111000$ \\ -\hline $4$ & $x + 2^{3}n = 8896$ & $10001011000000$ \\ -\hline $5$ & $8896$ & $10001011000000$ \\ -\hline $6$ & $8896$ & $10001011000000$ \\ -\hline $7$ & $x + 2^{6}n = 25344$ & $110001100000000$ \\ -\hline $8$ & $25344$ & $110001100000000$ \\ -\hline $9$ & $x + 2^{7}n = 91136$ & $10110010000000000$ \\ -\hline -- & $x/2^k = 178$ & \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Example of Montgomery Reduction (II)} -\label{fig:MONT2} -\end{figure} - -Figure~\ref{fig:MONT2} demonstrates the modified algorithm reducing $x = 5555$ modulo $n = 257$ with $k = 9$. -With this algorithm a single shift right at the end is the only right shift required to reduce the input instead of $k$ right shifts inside the -loop. Note that for the iterations $t = 2, 5, 6$ and $8$ where the result $x$ is not changed. In those iterations the $t$'th bit of $x$ is -zero and the appropriate multiple of $n$ does not need to be added to force the $t$'th bit of the result to zero. - -\subsection{Digit Based Montgomery Reduction} -Instead of computing the reduction on a bit-by-bit basis it is actually much faster to compute it on digit-by-digit basis. Consider the -previous algorithm re-written to compute the Montgomery reduction in this new fashion. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{Montgomery Reduction} (modified II). \\ -\textbf{Input}. Integer $x$, $n$ and $k$ ($\beta^k > n$) \\ -\textbf{Output}. $\beta^{-k}x \mbox{ (mod }n\mbox{)}$ \\ -\hline \\ -1. for $t$ from $0$ to $k - 1$ do \\ -\hspace{3mm}1.1 $x \leftarrow x + \mu n \beta^t$ \\ -2. Return $x/\beta^k$. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm Montgomery Reduction (modified II)} -\end{figure} - -The value $\mu n \beta^t$ is a multiple of the modulus $n$ meaning that it will not change the residue. If the first digit of -the value $\mu n \beta^t$ equals the negative (modulo $\beta$) of the $t$'th digit of $x$ then the addition will result in a zero digit. This -problem breaks down to solving the following congruency. - -\begin{center} -\begin{tabular}{rcl} -$x_t + \mu n_0$ & $\equiv$ & $0 \mbox{ (mod }\beta\mbox{)}$ \\ -$\mu n_0$ & $\equiv$ & $-x_t \mbox{ (mod }\beta\mbox{)}$ \\ -$\mu$ & $\equiv$ & $-x_t/n_0 \mbox{ (mod }\beta\mbox{)}$ \\ -\end{tabular} -\end{center} - -In each iteration of the loop on step 1 a new value of $\mu$ must be calculated. The value of $-1/n_0 \mbox{ (mod }\beta\mbox{)}$ is used -extensively in this algorithm and should be precomputed. Let $\rho$ represent the negative of the modular inverse of $n_0$ modulo $\beta$. - -For example, let $\beta = 10$ represent the radix. Let $n = 17$ represent the modulus which implies $k = 2$ and $\rho \equiv 7$. Let $x = 33$ -represent the value to reduce. - -\newpage\begin{figure} -\begin{center} -\begin{tabular}{|c|c|c|} -\hline \textbf{Step ($t$)} & \textbf{Value of $x$} & \textbf{Value of $\mu$} \\ -\hline -- & $33$ & --\\ -\hline $0$ & $33 + \mu n = 50$ & $1$ \\ -\hline $1$ & $50 + \mu n \beta = 900$ & $5$ \\ -\hline -\end{tabular} -\end{center} -\caption{Example of Montgomery Reduction} -\end{figure} - -The final result $900$ is then divided by $\beta^k$ to produce the final result $9$. The first observation is that $9 \nequiv x \mbox{ (mod }n\mbox{)}$ -which implies the result is not the modular residue of $x$ modulo $n$. However, recall that the residue is actually multiplied by $\beta^{-k}$ in -the algorithm. To get the true residue the value must be multiplied by $\beta^k$. In this case $\beta^k \equiv 15 \mbox{ (mod }n\mbox{)}$ and -the correct residue is $9 \cdot 15 \equiv 16 \mbox{ (mod }n\mbox{)}$. - -\subsection{Baseline Montgomery Reduction} -The baseline Montgomery reduction algorithm will produce the residue for any size input. It is designed to be a catch-all algororithm for -Montgomery reductions. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_montgomery\_reduce}. \\ -\textbf{Input}. mp\_int $x$, mp\_int $n$ and a digit $\rho \equiv -1/n_0 \mbox{ (mod }n\mbox{)}$. \\ -\hspace{11.5mm}($0 \le x < n^2, n > 1, (n, \beta) = 1, \beta^k > n$) \\ -\textbf{Output}. $\beta^{-k}x \mbox{ (mod }n\mbox{)}$ \\ -\hline \\ -1. $digs \leftarrow 2n.used + 1$ \\ -2. If $digs < MP\_ARRAY$ and $m.used < \delta$ then \\ -\hspace{3mm}2.1 Use algorithm fast\_mp\_montgomery\_reduce instead. \\ -\\ -Setup $x$ for the reduction. \\ -3. If $x.alloc < digs$ then grow $x$ to $digs$ digits. \\ -4. $x.used \leftarrow digs$ \\ -\\ -Eliminate the lower $k$ digits. \\ -5. For $ix$ from $0$ to $k - 1$ do \\ -\hspace{3mm}5.1 $\mu \leftarrow x_{ix} \cdot \rho \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{3mm}5.2 $u \leftarrow 0$ \\ -\hspace{3mm}5.3 For $iy$ from $0$ to $k - 1$ do \\ -\hspace{6mm}5.3.1 $\hat r \leftarrow \mu n_{iy} + x_{ix + iy} + u$ \\ -\hspace{6mm}5.3.2 $x_{ix + iy} \leftarrow \hat r \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{6mm}5.3.3 $u \leftarrow \lfloor \hat r / \beta \rfloor$ \\ -\hspace{3mm}5.4 While $u > 0$ do \\ -\hspace{6mm}5.4.1 $iy \leftarrow iy + 1$ \\ -\hspace{6mm}5.4.2 $x_{ix + iy} \leftarrow x_{ix + iy} + u$ \\ -\hspace{6mm}5.4.3 $u \leftarrow \lfloor x_{ix+iy} / \beta \rfloor$ \\ -\hspace{6mm}5.4.4 $x_{ix + iy} \leftarrow x_{ix+iy} \mbox{ (mod }\beta\mbox{)}$ \\ -\\ -Divide by $\beta^k$ and fix up as required. \\ -6. $x \leftarrow \lfloor x / \beta^k \rfloor$ \\ -7. If $x \ge n$ then \\ -\hspace{3mm}7.1 $x \leftarrow x - n$ \\ -8. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_montgomery\_reduce} -\end{figure} - -\textbf{Algorithm mp\_montgomery\_reduce.} -This algorithm reduces the input $x$ modulo $n$ in place using the Montgomery reduction algorithm. The algorithm is loosely based -on algorithm 14.32 of \cite[pp.601]{HAC} except it merges the multiplication of $\mu n \beta^t$ with the addition in the inner loop. The -restrictions on this algorithm are fairly easy to adapt to. First $0 \le x < n^2$ bounds the input to numbers in the same range as -for the Barrett algorithm. Additionally if $n > 1$ and $n$ is odd there will exist a modular inverse $\rho$. $\rho$ must be calculated in -advance of this algorithm. Finally the variable $k$ is fixed and a pseudonym for $n.used$. - -Step 2 decides whether a faster Montgomery algorithm can be used. It is based on the Comba technique meaning that there are limits on -the size of the input. This algorithm is discussed in ~COMBARED~. - -Step 5 is the main reduction loop of the algorithm. The value of $\mu$ is calculated once per iteration in the outer loop. The inner loop -calculates $x + \mu n \beta^{ix}$ by multiplying $\mu n$ and adding the result to $x$ shifted by $ix$ digits. Both the addition and -multiplication are performed in the same loop to save time and memory. Step 5.4 will handle any additional carries that escape the inner loop. - -Using a quick inspection this algorithm requires $n$ single precision multiplications for the outer loop and $n^2$ single precision multiplications -in the inner loop. In total $n^2 + n$ single precision multiplications which compares favourably to Barrett at $n^2 + 2n - 1$ single precision -multiplications. - -EXAM,bn_mp_montgomery_reduce.c - -This is the baseline implementation of the Montgomery reduction algorithm. Lines @30,digs@ to @35,}@ determine if the Comba based -routine can be used instead. Line @47,mu@ computes the value of $\mu$ for that particular iteration of the outer loop. - -The multiplication $\mu n \beta^{ix}$ is performed in one step in the inner loop. The alias $tmpx$ refers to the $ix$'th digit of $x$ and -the alias $tmpn$ refers to the modulus $n$. - -\subsection{Faster ``Comba'' Montgomery Reduction} -MARK,COMBARED - -The Montgomery reduction requires fewer single precision multiplications than a Barrett reduction, however it is much slower due to the serial -nature of the inner loop. The Barrett reduction algorithm requires two slightly modified multipliers which can be implemented with the Comba -technique. The Montgomery reduction algorithm cannot directly use the Comba technique to any significant advantage since the inner loop calculates -a $k \times 1$ product $k$ times. - -The biggest obstacle is that at the $ix$'th iteration of the outer loop the value of $x_{ix}$ is required to calculate $\mu$. This means the -carries from $0$ to $ix - 1$ must have been propagated upwards to form a valid $ix$'th digit. The solution as it turns out is very simple. -Perform a Comba like multiplier and inside the outer loop just after the inner loop fix up the $ix + 1$'th digit by forwarding the carry. - -With this change in place the Montgomery reduction algorithm can be performed with a Comba style multiplication loop which substantially increases -the speed of the algorithm. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{fast\_mp\_montgomery\_reduce}. \\ -\textbf{Input}. mp\_int $x$, mp\_int $n$ and a digit $\rho \equiv -1/n_0 \mbox{ (mod }n\mbox{)}$. \\ -\hspace{11.5mm}($0 \le x < n^2, n > 1, (n, \beta) = 1, \beta^k > n$) \\ -\textbf{Output}. $\beta^{-k}x \mbox{ (mod }n\mbox{)}$ \\ -\hline \\ -Place an array of \textbf{MP\_WARRAY} mp\_word variables called $\hat W$ on the stack. \\ -1. if $x.alloc < n.used + 1$ then grow $x$ to $n.used + 1$ digits. \\ -Copy the digits of $x$ into the array $\hat W$ \\ -2. For $ix$ from $0$ to $x.used - 1$ do \\ -\hspace{3mm}2.1 $\hat W_{ix} \leftarrow x_{ix}$ \\ -3. For $ix$ from $x.used$ to $2n.used - 1$ do \\ -\hspace{3mm}3.1 $\hat W_{ix} \leftarrow 0$ \\ -Elimiate the lower $k$ digits. \\ -4. for $ix$ from $0$ to $n.used - 1$ do \\ -\hspace{3mm}4.1 $\mu \leftarrow \hat W_{ix} \cdot \rho \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{3mm}4.2 For $iy$ from $0$ to $n.used - 1$ do \\ -\hspace{6mm}4.2.1 $\hat W_{iy + ix} \leftarrow \hat W_{iy + ix} + \mu \cdot n_{iy}$ \\ -\hspace{3mm}4.3 $\hat W_{ix + 1} \leftarrow \hat W_{ix + 1} + \lfloor \hat W_{ix} / \beta \rfloor$ \\ -Propagate carries upwards. \\ -5. for $ix$ from $n.used$ to $2n.used + 1$ do \\ -\hspace{3mm}5.1 $\hat W_{ix + 1} \leftarrow \hat W_{ix + 1} + \lfloor \hat W_{ix} / \beta \rfloor$ \\ -Shift right and reduce modulo $\beta$ simultaneously. \\ -6. for $ix$ from $0$ to $n.used + 1$ do \\ -\hspace{3mm}6.1 $x_{ix} \leftarrow \hat W_{ix + n.used} \mbox{ (mod }\beta\mbox{)}$ \\ -Zero excess digits and fixup $x$. \\ -7. if $x.used > n.used + 1$ then do \\ -\hspace{3mm}7.1 for $ix$ from $n.used + 1$ to $x.used - 1$ do \\ -\hspace{6mm}7.1.1 $x_{ix} \leftarrow 0$ \\ -8. $x.used \leftarrow n.used + 1$ \\ -9. Clamp excessive digits of $x$. \\ -10. If $x \ge n$ then \\ -\hspace{3mm}10.1 $x \leftarrow x - n$ \\ -11. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm fast\_mp\_montgomery\_reduce} -\end{figure} - -\textbf{Algorithm fast\_mp\_montgomery\_reduce.} -This algorithm will compute the Montgomery reduction of $x$ modulo $n$ using the Comba technique. It is on most computer platforms significantly -faster than algorithm mp\_montgomery\_reduce and algorithm mp\_reduce (\textit{Barrett reduction}). The algorithm has the same restrictions -on the input as the baseline reduction algorithm. An additional two restrictions are imposed on this algorithm. The number of digits $k$ in the -the modulus $n$ must not violate $MP\_WARRAY > 2k +1$ and $n < \delta$. When $\beta = 2^{28}$ this algorithm can be used to reduce modulo -a modulus of at most $3,556$ bits in length. - -As in the other Comba reduction algorithms there is a $\hat W$ array which stores the columns of the product. It is initially filled with the -contents of $x$ with the excess digits zeroed. The reduction loop is very similar the to the baseline loop at heart. The multiplication on step -4.1 can be single precision only since $ab \mbox{ (mod }\beta\mbox{)} \equiv (a \mbox{ mod }\beta)(b \mbox{ mod }\beta)$. Some multipliers such -as those on the ARM processors take a variable length time to complete depending on the number of bytes of result it must produce. By performing -a single precision multiplication instead half the amount of time is spent. - -Also note that digit $\hat W_{ix}$ must have the carry from the $ix - 1$'th digit propagated upwards in order for this to work. That is what step -4.3 will do. In effect over the $n.used$ iterations of the outer loop the $n.used$'th lower columns all have the their carries propagated forwards. Note -how the upper bits of those same words are not reduced modulo $\beta$. This is because those values will be discarded shortly and there is no -point. - -Step 5 will propagate the remainder of the carries upwards. On step 6 the columns are reduced modulo $\beta$ and shifted simultaneously as they are -stored in the destination $x$. - -EXAM,bn_fast_mp_montgomery_reduce.c - -The $\hat W$ array is first filled with digits of $x$ on line @49,for@ then the rest of the digits are zeroed on line @54,for@. Both loops share -the same alias variables to make the code easier to read. - -The value of $\mu$ is calculated in an interesting fashion. First the value $\hat W_{ix}$ is reduced modulo $\beta$ and cast to a mp\_digit. This -forces the compiler to use a single precision multiplication and prevents any concerns about loss of precision. Line @101,>>@ fixes the carry -for the next iteration of the loop by propagating the carry from $\hat W_{ix}$ to $\hat W_{ix+1}$. - -The for loop on line @113,for@ propagates the rest of the carries upwards through the columns. The for loop on line @126,for@ reduces the columns -modulo $\beta$ and shifts them $k$ places at the same time. The alias $\_ \hat W$ actually refers to the array $\hat W$ starting at the $n.used$'th -digit, that is $\_ \hat W_{t} = \hat W_{n.used + t}$. - -\subsection{Montgomery Setup} -To calculate the variable $\rho$ a relatively simple algorithm will be required. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_montgomery\_setup}. \\ -\textbf{Input}. mp\_int $n$ ($n > 1$ and $(n, 2) = 1$) \\ -\textbf{Output}. $\rho \equiv -1/n_0 \mbox{ (mod }\beta\mbox{)}$ \\ -\hline \\ -1. $b \leftarrow n_0$ \\ -2. If $b$ is even return(\textit{MP\_VAL}) \\ -3. $x \leftarrow (((b + 2) \mbox{ AND } 4) << 1) + b$ \\ -4. for $k$ from 0 to $\lceil lg(lg(\beta)) \rceil - 2$ do \\ -\hspace{3mm}4.1 $x \leftarrow x \cdot (2 - bx)$ \\ -5. $\rho \leftarrow \beta - x \mbox{ (mod }\beta\mbox{)}$ \\ -6. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_montgomery\_setup} -\end{figure} - -\textbf{Algorithm mp\_montgomery\_setup.} -This algorithm will calculate the value of $\rho$ required within the Montgomery reduction algorithms. It uses a very interesting trick -to calculate $1/n_0$ when $\beta$ is a power of two. - -EXAM,bn_mp_montgomery_setup.c - -This source code computes the value of $\rho$ required to perform Montgomery reduction. It has been modified to avoid performing excess -multiplications when $\beta$ is not the default 28-bits. - -\section{The Diminished Radix Algorithm} -The Diminished Radix method of modular reduction \cite{DRMET} is a fairly clever technique which can be more efficient than either the Barrett -or Montgomery methods for certain forms of moduli. The technique is based on the following simple congruence. - -\begin{equation} -(x \mbox{ mod } n) + k \lfloor x / n \rfloor \equiv x \mbox{ (mod }(n - k)\mbox{)} -\end{equation} - -This observation was used in the MMB \cite{MMB} block cipher to create a diffusion primitive. It used the fact that if $n = 2^{31}$ and $k=1$ that -then a x86 multiplier could produce the 62-bit product and use the ``shrd'' instruction to perform a double-precision right shift. The proof -of the above equation is very simple. First write $x$ in the product form. - -\begin{equation} -x = qn + r -\end{equation} - -Now reduce both sides modulo $(n - k)$. - -\begin{equation} -x \equiv qk + r \mbox{ (mod }(n-k)\mbox{)} -\end{equation} - -The variable $n$ reduces modulo $n - k$ to $k$. By putting $q = \lfloor x/n \rfloor$ and $r = x \mbox{ mod } n$ -into the equation the original congruence is reproduced, thus concluding the proof. The following algorithm is based on this observation. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{Diminished Radix Reduction}. \\ -\textbf{Input}. Integer $x$, $n$, $k$ \\ -\textbf{Output}. $x \mbox{ mod } (n - k)$ \\ -\hline \\ -1. $q \leftarrow \lfloor x / n \rfloor$ \\ -2. $q \leftarrow k \cdot q$ \\ -3. $x \leftarrow x \mbox{ (mod }n\mbox{)}$ \\ -4. $x \leftarrow x + q$ \\ -5. If $x \ge (n - k)$ then \\ -\hspace{3mm}5.1 $x \leftarrow x - (n - k)$ \\ -\hspace{3mm}5.2 Goto step 1. \\ -6. Return $x$ \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm Diminished Radix Reduction} -\label{fig:DR} -\end{figure} - -This algorithm will reduce $x$ modulo $n - k$ and return the residue. If $0 \le x < (n - k)^2$ then the algorithm will loop almost always -once or twice and occasionally three times. For simplicity sake the value of $x$ is bounded by the following simple polynomial. - -\begin{equation} -0 \le x < n^2 + k^2 - 2nk -\end{equation} - -The true bound is $0 \le x < (n - k - 1)^2$ but this has quite a few more terms. The value of $q$ after step 1 is bounded by the following. - -\begin{equation} -q < n - 2k - k^2/n -\end{equation} - -Since $k^2$ is going to be considerably smaller than $n$ that term will always be zero. The value of $x$ after step 3 is bounded trivially as -$0 \le x < n$. By step four the sum $x + q$ is bounded by - -\begin{equation} -0 \le q + x < (k + 1)n - 2k^2 - 1 -\end{equation} - -With a second pass $q$ will be loosely bounded by $0 \le q < k^2$ after step 2 while $x$ will still be loosely bounded by $0 \le x < n$ after step 3. After the second pass it is highly unlike that the -sum in step 4 will exceed $n - k$. In practice fewer than three passes of the algorithm are required to reduce virtually every input in the -range $0 \le x < (n - k - 1)^2$. - -\begin{figure} -\begin{small} -\begin{center} -\begin{tabular}{|l|} -\hline -$x = 123456789, n = 256, k = 3$ \\ -\hline $q \leftarrow \lfloor x/n \rfloor = 482253$ \\ -$q \leftarrow q*k = 1446759$ \\ -$x \leftarrow x \mbox{ mod } n = 21$ \\ -$x \leftarrow x + q = 1446780$ \\ -$x \leftarrow x - (n - k) = 1446527$ \\ -\hline -$q \leftarrow \lfloor x/n \rfloor = 5650$ \\ -$q \leftarrow q*k = 16950$ \\ -$x \leftarrow x \mbox{ mod } n = 127$ \\ -$x \leftarrow x + q = 17077$ \\ -$x \leftarrow x - (n - k) = 16824$ \\ -\hline -$q \leftarrow \lfloor x/n \rfloor = 65$ \\ -$q \leftarrow q*k = 195$ \\ -$x \leftarrow x \mbox{ mod } n = 184$ \\ -$x \leftarrow x + q = 379$ \\ -$x \leftarrow x - (n - k) = 126$ \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Example Diminished Radix Reduction} -\label{fig:EXDR} -\end{figure} - -Figure~\ref{fig:EXDR} demonstrates the reduction of $x = 123456789$ modulo $n - k = 253$ when $n = 256$ and $k = 3$. Note that even while $x$ -is considerably larger than $(n - k - 1)^2 = 63504$ the algorithm still converges on the modular residue exceedingly fast. In this case only -three passes were required to find the residue $x \equiv 126$. - - -\subsection{Choice of Moduli} -On the surface this algorithm looks like a very expensive algorithm. It requires a couple of subtractions followed by multiplication and other -modular reductions. The usefulness of this algorithm becomes exceedingly clear when an appropriate modulus is chosen. - -Division in general is a very expensive operation to perform. The one exception is when the division is by a power of the radix of representation used. -Division by ten for example is simple for pencil and paper mathematics since it amounts to shifting the decimal place to the right. Similarly division -by two (\textit{or powers of two}) is very simple for binary computers to perform. It would therefore seem logical to choose $n$ of the form $2^p$ -which would imply that $\lfloor x / n \rfloor$ is a simple shift of $x$ right $p$ bits. - -However, there is one operation related to division of power of twos that is even faster than this. If $n = \beta^p$ then the division may be -performed by moving whole digits to the right $p$ places. In practice division by $\beta^p$ is much faster than division by $2^p$ for any $p$. -Also with the choice of $n = \beta^p$ reducing $x$ modulo $n$ merely requires zeroing the digits above the $p-1$'th digit of $x$. - -Throughout the next section the term ``restricted modulus'' will refer to a modulus of the form $\beta^p - k$ whereas the term ``unrestricted -modulus'' will refer to a modulus of the form $2^p - k$. The word ``restricted'' in this case refers to the fact that it is based on the -$2^p$ logic except $p$ must be a multiple of $lg(\beta)$. - -\subsection{Choice of $k$} -Now that division and reduction (\textit{step 1 and 3 of figure~\ref{fig:DR}}) have been optimized to simple digit operations the multiplication by $k$ -in step 2 is the most expensive operation. Fortunately the choice of $k$ is not terribly limited. For all intents and purposes it might -as well be a single digit. The smaller the value of $k$ is the faster the algorithm will be. - -\subsection{Restricted Diminished Radix Reduction} -The restricted Diminished Radix algorithm can quickly reduce an input modulo a modulus of the form $n = \beta^p - k$. This algorithm can reduce -an input $x$ within the range $0 \le x < n^2$ using only a couple passes of the algorithm demonstrated in figure~\ref{fig:DR}. The implementation -of this algorithm has been optimized to avoid additional overhead associated with a division by $\beta^p$, the multiplication by $k$ or the addition -of $x$ and $q$. The resulting algorithm is very efficient and can lead to substantial improvements over Barrett and Montgomery reduction when modular -exponentiations are performed. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_dr\_reduce}. \\ -\textbf{Input}. mp\_int $x$, $n$ and a mp\_digit $k = \beta - n_0$ \\ -\hspace{11.5mm}($0 \le x < n^2$, $n > 1$, $0 < k < \beta$) \\ -\textbf{Output}. $x \mbox{ mod } n$ \\ -\hline \\ -1. $m \leftarrow n.used$ \\ -2. If $x.alloc < 2m$ then grow $x$ to $2m$ digits. \\ -3. $\mu \leftarrow 0$ \\ -4. for $i$ from $0$ to $m - 1$ do \\ -\hspace{3mm}4.1 $\hat r \leftarrow k \cdot x_{m+i} + x_{i} + \mu$ \\ -\hspace{3mm}4.2 $x_{i} \leftarrow \hat r \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{3mm}4.3 $\mu \leftarrow \lfloor \hat r / \beta \rfloor$ \\ -5. $x_{m} \leftarrow \mu$ \\ -6. for $i$ from $m + 1$ to $x.used - 1$ do \\ -\hspace{3mm}6.1 $x_{i} \leftarrow 0$ \\ -7. Clamp excess digits of $x$. \\ -8. If $x \ge n$ then \\ -\hspace{3mm}8.1 $x \leftarrow x - n$ \\ -\hspace{3mm}8.2 Goto step 3. \\ -9. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_dr\_reduce} -\end{figure} - -\textbf{Algorithm mp\_dr\_reduce.} -This algorithm will perform the Dimished Radix reduction of $x$ modulo $n$. It has similar restrictions to that of the Barrett reduction -with the addition that $n$ must be of the form $n = \beta^m - k$ where $0 < k <\beta$. - -This algorithm essentially implements the pseudo-code in figure~\ref{fig:DR} except with a slight optimization. The division by $\beta^m$, multiplication by $k$ -and addition of $x \mbox{ mod }\beta^m$ are all performed simultaneously inside the loop on step 4. The division by $\beta^m$ is emulated by accessing -the term at the $m+i$'th position which is subsequently multiplied by $k$ and added to the term at the $i$'th position. After the loop the $m$'th -digit is set to the carry and the upper digits are zeroed. Steps 5 and 6 emulate the reduction modulo $\beta^m$ that should have happend to -$x$ before the addition of the multiple of the upper half. - -At step 8 if $x$ is still larger than $n$ another pass of the algorithm is required. First $n$ is subtracted from $x$ and then the algorithm resumes -at step 3. - -EXAM,bn_mp_dr_reduce.c - -The first step is to grow $x$ as required to $2m$ digits since the reduction is performed in place on $x$. The label on line @49,top:@ is where -the algorithm will resume if further reduction passes are required. In theory it could be placed at the top of the function however, the size of -the modulus and question of whether $x$ is large enough are invariant after the first pass meaning that it would be a waste of time. - -The aliases $tmpx1$ and $tmpx2$ refer to the digits of $x$ where the latter is offset by $m$ digits. By reading digits from $x$ offset by $m$ digits -a division by $\beta^m$ can be simulated virtually for free. The loop on line @61,for@ performs the bulk of the work (\textit{corresponds to step 4 of algorithm 7.11}) -in this algorithm. - -By line @68,mu@ the pointer $tmpx1$ points to the $m$'th digit of $x$ which is where the final carry will be placed. Similarly by line @71,for@ the -same pointer will point to the $m+1$'th digit where the zeroes will be placed. - -Since the algorithm is only valid if both $x$ and $n$ are greater than zero an unsigned comparison suffices to determine if another pass is required. -With the same logic at line @82,sub@ the value of $x$ is known to be greater than or equal to $n$ meaning that an unsigned subtraction can be used -as well. Since the destination of the subtraction is the larger of the inputs the call to algorithm s\_mp\_sub cannot fail and the return code -does not need to be checked. - -\subsubsection{Setup} -To setup the restricted Diminished Radix algorithm the value $k = \beta - n_0$ is required. This algorithm is not really complicated but provided for -completeness. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_dr\_setup}. \\ -\textbf{Input}. mp\_int $n$ \\ -\textbf{Output}. $k = \beta - n_0$ \\ -\hline \\ -1. $k \leftarrow \beta - n_0$ \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_dr\_setup} -\end{figure} - -EXAM,bn_mp_dr_setup.c - -\subsubsection{Modulus Detection} -Another algorithm which will be useful is the ability to detect a restricted Diminished Radix modulus. An integer is said to be -of restricted Diminished Radix form if all of the digits are equal to $\beta - 1$ except the trailing digit which may be any value. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_dr\_is\_modulus}. \\ -\textbf{Input}. mp\_int $n$ \\ -\textbf{Output}. $1$ if $n$ is in D.R form, $0$ otherwise \\ -\hline -1. If $n.used < 2$ then return($0$). \\ -2. for $ix$ from $1$ to $n.used - 1$ do \\ -\hspace{3mm}2.1 If $n_{ix} \ne \beta - 1$ return($0$). \\ -3. Return($1$). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_dr\_is\_modulus} -\end{figure} - -\textbf{Algorithm mp\_dr\_is\_modulus.} -This algorithm determines if a value is in Diminished Radix form. Step 1 rejects obvious cases where fewer than two digits are -in the mp\_int. Step 2 tests all but the first digit to see if they are equal to $\beta - 1$. If the algorithm manages to get to -step 3 then $n$ must be of Diminished Radix form. - -EXAM,bn_mp_dr_is_modulus.c - -\subsection{Unrestricted Diminished Radix Reduction} -The unrestricted Diminished Radix algorithm allows modular reductions to be performed when the modulus is of the form $2^p - k$. This algorithm -is a straightforward adaptation of algorithm~\ref{fig:DR}. - -In general the restricted Diminished Radix reduction algorithm is much faster since it has considerably lower overhead. However, this new -algorithm is much faster than either Montgomery or Barrett reduction when the moduli are of the appropriate form. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_reduce\_2k}. \\ -\textbf{Input}. mp\_int $a$ and $n$. mp\_digit $k$ \\ -\hspace{11.5mm}($a \ge 0$, $n > 1$, $0 < k < \beta$, $n + k$ is a power of two) \\ -\textbf{Output}. $a \mbox{ (mod }n\mbox{)}$ \\ -\hline -1. $p \leftarrow \lceil lg(n) \rceil$ (\textit{mp\_count\_bits}) \\ -2. While $a \ge n$ do \\ -\hspace{3mm}2.1 $q \leftarrow \lfloor a / 2^p \rfloor$ (\textit{mp\_div\_2d}) \\ -\hspace{3mm}2.2 $a \leftarrow a \mbox{ (mod }2^p\mbox{)}$ (\textit{mp\_mod\_2d}) \\ -\hspace{3mm}2.3 $q \leftarrow q \cdot k$ (\textit{mp\_mul\_d}) \\ -\hspace{3mm}2.4 $a \leftarrow a - q$ (\textit{s\_mp\_sub}) \\ -\hspace{3mm}2.5 If $a \ge n$ then do \\ -\hspace{6mm}2.5.1 $a \leftarrow a - n$ \\ -3. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_reduce\_2k} -\end{figure} - -\textbf{Algorithm mp\_reduce\_2k.} -This algorithm quickly reduces an input $a$ modulo an unrestricted Diminished Radix modulus $n$. Division by $2^p$ is emulated with a right -shift which makes the algorithm fairly inexpensive to use. - -EXAM,bn_mp_reduce_2k.c - -The algorithm mp\_count\_bits calculates the number of bits in an mp\_int which is used to find the initial value of $p$. The call to mp\_div\_2d -on line @31,mp_div_2d@ calculates both the quotient $q$ and the remainder $a$ required. By doing both in a single function call the code size -is kept fairly small. The multiplication by $k$ is only performed if $k > 1$. This allows reductions modulo $2^p - 1$ to be performed without -any multiplications. - -The unsigned s\_mp\_add, mp\_cmp\_mag and s\_mp\_sub are used in place of their full sign counterparts since the inputs are only valid if they are -positive. By using the unsigned versions the overhead is kept to a minimum. - -\subsubsection{Unrestricted Setup} -To setup this reduction algorithm the value of $k = 2^p - n$ is required. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_reduce\_2k\_setup}. \\ -\textbf{Input}. mp\_int $n$ \\ -\textbf{Output}. $k = 2^p - n$ \\ -\hline -1. $p \leftarrow \lceil lg(n) \rceil$ (\textit{mp\_count\_bits}) \\ -2. $x \leftarrow 2^p$ (\textit{mp\_2expt}) \\ -3. $x \leftarrow x - n$ (\textit{mp\_sub}) \\ -4. $k \leftarrow x_0$ \\ -5. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_reduce\_2k\_setup} -\end{figure} - -\textbf{Algorithm mp\_reduce\_2k\_setup.} -This algorithm computes the value of $k$ required for the algorithm mp\_reduce\_2k. By making a temporary variable $x$ equal to $2^p$ a subtraction -is sufficient to solve for $k$. Alternatively if $n$ has more than one digit the value of $k$ is simply $\beta - n_0$. - -EXAM,bn_mp_reduce_2k_setup.c - -\subsubsection{Unrestricted Detection} -An integer $n$ is a valid unrestricted Diminished Radix modulus if either of the following are true. - -\begin{enumerate} -\item The number has only one digit. -\item The number has more than one digit and every bit from the $\beta$'th to the most significant is one. -\end{enumerate} - -If either condition is true than there is a power of two $2^p$ such that $0 < 2^p - n < \beta$. If the input is only -one digit than it will always be of the correct form. Otherwise all of the bits above the first digit must be one. This arises from the fact -that there will be value of $k$ that when added to the modulus causes a carry in the first digit which propagates all the way to the most -significant bit. The resulting sum will be a power of two. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_reduce\_is\_2k}. \\ -\textbf{Input}. mp\_int $n$ \\ -\textbf{Output}. $1$ if of proper form, $0$ otherwise \\ -\hline -1. If $n.used = 0$ then return($0$). \\ -2. If $n.used = 1$ then return($1$). \\ -3. $p \leftarrow \lceil lg(n) \rceil$ (\textit{mp\_count\_bits}) \\ -4. for $x$ from $lg(\beta)$ to $p$ do \\ -\hspace{3mm}4.1 If the ($x \mbox{ mod }lg(\beta)$)'th bit of the $\lfloor x / lg(\beta) \rfloor$ of $n$ is zero then return($0$). \\ -5. Return($1$). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_reduce\_is\_2k} -\end{figure} - -\textbf{Algorithm mp\_reduce\_is\_2k.} -This algorithm quickly determines if a modulus is of the form required for algorithm mp\_reduce\_2k to function properly. - -EXAM,bn_mp_reduce_is_2k.c - - - -\section{Algorithm Comparison} -So far three very different algorithms for modular reduction have been discussed. Each of the algorithms have their own strengths and weaknesses -that makes having such a selection very useful. The following table sumarizes the three algorithms along with comparisons of work factors. Since -all three algorithms have the restriction that $0 \le x < n^2$ and $n > 1$ those limitations are not included in the table. - -\begin{center} -\begin{small} -\begin{tabular}{|c|c|c|c|c|c|} -\hline \textbf{Method} & \textbf{Work Required} & \textbf{Limitations} & \textbf{$m = 8$} & \textbf{$m = 32$} & \textbf{$m = 64$} \\ -\hline Barrett & $m^2 + 2m - 1$ & None & $79$ & $1087$ & $4223$ \\ -\hline Montgomery & $m^2 + m$ & $n$ must be odd & $72$ & $1056$ & $4160$ \\ -\hline D.R. & $2m$ & $n = \beta^m - k$ & $16$ & $64$ & $128$ \\ -\hline -\end{tabular} -\end{small} -\end{center} - -In theory Montgomery and Barrett reductions would require roughly the same amount of time to complete. However, in practice since Montgomery -reduction can be written as a single function with the Comba technique it is much faster. Barrett reduction suffers from the overhead of -calling the half precision multipliers, addition and division by $\beta$ algorithms. - -For almost every cryptographic algorithm Montgomery reduction is the algorithm of choice. The one set of algorithms where Diminished Radix reduction truly -shines are based on the discrete logarithm problem such as Diffie-Hellman \cite{DH} and ElGamal \cite{ELGAMAL}. In these algorithms -primes of the form $\beta^m - k$ can be found and shared amongst users. These primes will allow the Diminished Radix algorithm to be used in -modular exponentiation to greatly speed up the operation. - - - -\section*{Exercises} -\begin{tabular}{cl} -$\left [ 3 \right ]$ & Prove that the ``trick'' in algorithm mp\_montgomery\_setup actually \\ - & calculates the correct value of $\rho$. \\ - & \\ -$\left [ 2 \right ]$ & Devise an algorithm to reduce modulo $n + k$ for small $k$ quickly. \\ - & \\ -$\left [ 4 \right ]$ & Prove that the pseudo-code algorithm ``Diminished Radix Reduction'' \\ - & (\textit{figure~\ref{fig:DR}}) terminates. Also prove the probability that it will \\ - & terminate within $1 \le k \le 10$ iterations. \\ - & \\ -\end{tabular} - - -\chapter{Exponentiation} -Exponentiation is the operation of raising one variable to the power of another, for example, $a^b$. A variant of exponentiation, computed -in a finite field or ring, is called modular exponentiation. This latter style of operation is typically used in public key -cryptosystems such as RSA and Diffie-Hellman. The ability to quickly compute modular exponentiations is of great benefit to any -such cryptosystem and many methods have been sought to speed it up. - -\section{Exponentiation Basics} -A trivial algorithm would simply multiply $a$ against itself $b - 1$ times to compute the exponentiation desired. However, as $b$ grows in size -the number of multiplications becomes prohibitive. Imagine what would happen if $b$ $\approx$ $2^{1024}$ as is the case when computing an RSA signature -with a $1024$-bit key. Such a calculation could never be completed as it would take simply far too long. - -Fortunately there is a very simple algorithm based on the laws of exponents. Recall that $lg_a(a^b) = b$ and that $lg_a(a^ba^c) = b + c$ which -are two trivial relationships between the base and the exponent. Let $b_i$ represent the $i$'th bit of $b$ starting from the least -significant bit. If $b$ is a $k$-bit integer than the following equation is true. - -\begin{equation} -a^b = \prod_{i=0}^{k-1} a^{2^i \cdot b_i} -\end{equation} - -By taking the base $a$ logarithm of both sides of the equation the following equation is the result. - -\begin{equation} -b = \sum_{i=0}^{k-1}2^i \cdot b_i -\end{equation} - -The term $a^{2^i}$ can be found from the $i - 1$'th term by squaring the term since $\left ( a^{2^i} \right )^2$ is equal to -$a^{2^{i+1}}$. This observation forms the basis of essentially all fast exponentiation algorithms. It requires $k$ squarings and on average -$k \over 2$ multiplications to compute the result. This is indeed quite an improvement over simply multiplying by $a$ a total of $b-1$ times. - -While this current method is a considerable speed up there are further improvements to be made. For example, the $a^{2^i}$ term does not need to -be computed in an auxilary variable. Consider the following equivalent algorithm. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{Left to Right Exponentiation}. \\ -\textbf{Input}. Integer $a$, $b$ and $k$ \\ -\textbf{Output}. $c = a^b$ \\ -\hline \\ -1. $c \leftarrow 1$ \\ -2. for $i$ from $k - 1$ to $0$ do \\ -\hspace{3mm}2.1 $c \leftarrow c^2$ \\ -\hspace{3mm}2.2 $c \leftarrow c \cdot a^{b_i}$ \\ -3. Return $c$. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Left to Right Exponentiation} -\label{fig:LTOR} -\end{figure} - -This algorithm starts from the most significant bit and works towards the least significant bit. When the $i$'th bit of $b$ is set $a$ is -multiplied against the current product. In each iteration the product is squared which doubles the exponent of the individual terms of the -product. - -For example, let $b = 101100_2 \equiv 44_{10}$. The following chart demonstrates the actions of the algorithm. - -\newpage\begin{figure} -\begin{center} -\begin{tabular}{|c|c|} -\hline \textbf{Value of $i$} & \textbf{Value of $c$} \\ -\hline - & $1$ \\ -\hline $5$ & $a$ \\ -\hline $4$ & $a^2$ \\ -\hline $3$ & $a^4 \cdot a$ \\ -\hline $2$ & $a^8 \cdot a^2 \cdot a$ \\ -\hline $1$ & $a^{16} \cdot a^4 \cdot a^2$ \\ -\hline $0$ & $a^{32} \cdot a^8 \cdot a^4$ \\ -\hline -\end{tabular} -\end{center} -\caption{Example of Left to Right Exponentiation} -\end{figure} - -When the product $a^{32} \cdot a^8 \cdot a^4$ is simplified it is equal $a^{44}$ which is the desired exponentiation. This particular algorithm is -called ``Left to Right'' because it reads the exponent in that order. All of the exponentiation algorithms that will be presented are of this nature. - -\subsection{Single Digit Exponentiation} -The first algorithm in the series of exponentiation algorithms will be an unbounded algorithm where the exponent is a single digit. It is intended -to be used when a small power of an input is required (\textit{e.g. $a^5$}). It is faster than simply multiplying $b - 1$ times for all values of -$b$ that are greater than three. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_expt\_d}. \\ -\textbf{Input}. mp\_int $a$ and mp\_digit $b$ \\ -\textbf{Output}. $c = a^b$ \\ -\hline \\ -1. $g \leftarrow a$ (\textit{mp\_init\_copy}) \\ -2. $c \leftarrow 1$ (\textit{mp\_set}) \\ -3. for $x$ from 1 to $lg(\beta)$ do \\ -\hspace{3mm}3.1 $c \leftarrow c^2$ (\textit{mp\_sqr}) \\ -\hspace{3mm}3.2 If $b$ AND $2^{lg(\beta) - 1} \ne 0$ then \\ -\hspace{6mm}3.2.1 $c \leftarrow c \cdot g$ (\textit{mp\_mul}) \\ -\hspace{3mm}3.3 $b \leftarrow b << 1$ \\ -4. Clear $g$. \\ -5. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_expt\_d} -\end{figure} - -\textbf{Algorithm mp\_expt\_d.} -This algorithm computes the value of $a$ raised to the power of a single digit $b$. It uses the left to right exponentiation algorithm to -quickly compute the exponentiation. It is loosely based on algorithm 14.79 of HAC \cite[pp. 615]{HAC} with the difference that the -exponent is a fixed width. - -A copy of $a$ is made first to allow destination variable $c$ be the same as the source variable $a$. The result is set to the initial value of -$1$ in the subsequent step. - -Inside the loop the exponent is read from the most significant bit first down to the least significant bit. First $c$ is invariably squared -on step 3.1. In the following step if the most significant bit of $b$ is one the copy of $a$ is multiplied against $c$. The value -of $b$ is shifted left one bit to make the next bit down from the most signficant bit the new most significant bit. In effect each -iteration of the loop moves the bits of the exponent $b$ upwards to the most significant location. - -EXAM,bn_mp_expt_d_ex.c - -This describes only the algorithm that is used when the parameter $fast$ is $0$. Line @31,mp_set@ sets the initial value of the result to $1$. Next the loop on line @54,for@ steps through each bit of the exponent starting from -the most significant down towards the least significant. The invariant squaring operation placed on line @333,mp_sqr@ is performed first. After -the squaring the result $c$ is multiplied by the base $g$ if and only if the most significant bit of the exponent is set. The shift on line -@69,<<@ moves all of the bits of the exponent upwards towards the most significant location. - -\section{$k$-ary Exponentiation} -When calculating an exponentiation the most time consuming bottleneck is the multiplications which are in general a small factor -slower than squaring. Recall from the previous algorithm that $b_{i}$ refers to the $i$'th bit of the exponent $b$. Suppose instead it referred to -the $i$'th $k$-bit digit of the exponent of $b$. For $k = 1$ the definitions are synonymous and for $k > 1$ algorithm~\ref{fig:KARY} -computes the same exponentiation. A group of $k$ bits from the exponent is called a \textit{window}. That is it is a small window on only a -portion of the entire exponent. Consider the following modification to the basic left to right exponentiation algorithm. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{$k$-ary Exponentiation}. \\ -\textbf{Input}. Integer $a$, $b$, $k$ and $t$ \\ -\textbf{Output}. $c = a^b$ \\ -\hline \\ -1. $c \leftarrow 1$ \\ -2. for $i$ from $t - 1$ to $0$ do \\ -\hspace{3mm}2.1 $c \leftarrow c^{2^k} $ \\ -\hspace{3mm}2.2 Extract the $i$'th $k$-bit word from $b$ and store it in $g$. \\ -\hspace{3mm}2.3 $c \leftarrow c \cdot a^g$ \\ -3. Return $c$. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{$k$-ary Exponentiation} -\label{fig:KARY} -\end{figure} - -The squaring on step 2.1 can be calculated by squaring the value $c$ successively $k$ times. If the values of $a^g$ for $0 < g < 2^k$ have been -precomputed this algorithm requires only $t$ multiplications and $tk$ squarings. The table can be generated with $2^{k - 1} - 1$ squarings and -$2^{k - 1} + 1$ multiplications. This algorithm assumes that the number of bits in the exponent is evenly divisible by $k$. -However, when it is not the remaining $0 < x \le k - 1$ bits can be handled with algorithm~\ref{fig:LTOR}. - -Suppose $k = 4$ and $t = 100$. This modified algorithm will require $109$ multiplications and $408$ squarings to compute the exponentiation. The -original algorithm would on average have required $200$ multiplications and $400$ squrings to compute the same value. The total number of squarings -has increased slightly but the number of multiplications has nearly halved. - -\subsection{Optimal Values of $k$} -An optimal value of $k$ will minimize $2^{k} + \lceil n / k \rceil + n - 1$ for a fixed number of bits in the exponent $n$. The simplest -approach is to brute force search amongst the values $k = 2, 3, \ldots, 8$ for the lowest result. Table~\ref{fig:OPTK} lists optimal values of $k$ -for various exponent sizes and compares the number of multiplication and squarings required against algorithm~\ref{fig:LTOR}. - -\begin{figure}[here] -\begin{center} -\begin{small} -\begin{tabular}{|c|c|c|c|c|c|} -\hline \textbf{Exponent (bits)} & \textbf{Optimal $k$} & \textbf{Work at $k$} & \textbf{Work with ~\ref{fig:LTOR}} \\ -\hline $16$ & $2$ & $27$ & $24$ \\ -\hline $32$ & $3$ & $49$ & $48$ \\ -\hline $64$ & $3$ & $92$ & $96$ \\ -\hline $128$ & $4$ & $175$ & $192$ \\ -\hline $256$ & $4$ & $335$ & $384$ \\ -\hline $512$ & $5$ & $645$ & $768$ \\ -\hline $1024$ & $6$ & $1257$ & $1536$ \\ -\hline $2048$ & $6$ & $2452$ & $3072$ \\ -\hline $4096$ & $7$ & $4808$ & $6144$ \\ -\hline -\end{tabular} -\end{small} -\end{center} -\caption{Optimal Values of $k$ for $k$-ary Exponentiation} -\label{fig:OPTK} -\end{figure} - -\subsection{Sliding-Window Exponentiation} -A simple modification to the previous algorithm is only generate the upper half of the table in the range $2^{k-1} \le g < 2^k$. Essentially -this is a table for all values of $g$ where the most significant bit of $g$ is a one. However, in order for this to be allowed in the -algorithm values of $g$ in the range $0 \le g < 2^{k-1}$ must be avoided. - -Table~\ref{fig:OPTK2} lists optimal values of $k$ for various exponent sizes and compares the work required against algorithm {\ref{fig:KARY}}. - -\begin{figure}[here] -\begin{center} -\begin{small} -\begin{tabular}{|c|c|c|c|c|c|} -\hline \textbf{Exponent (bits)} & \textbf{Optimal $k$} & \textbf{Work at $k$} & \textbf{Work with ~\ref{fig:KARY}} \\ -\hline $16$ & $3$ & $24$ & $27$ \\ -\hline $32$ & $3$ & $45$ & $49$ \\ -\hline $64$ & $4$ & $87$ & $92$ \\ -\hline $128$ & $4$ & $167$ & $175$ \\ -\hline $256$ & $5$ & $322$ & $335$ \\ -\hline $512$ & $6$ & $628$ & $645$ \\ -\hline $1024$ & $6$ & $1225$ & $1257$ \\ -\hline $2048$ & $7$ & $2403$ & $2452$ \\ -\hline $4096$ & $8$ & $4735$ & $4808$ \\ -\hline -\end{tabular} -\end{small} -\end{center} -\caption{Optimal Values of $k$ for Sliding Window Exponentiation} -\label{fig:OPTK2} -\end{figure} - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{Sliding Window $k$-ary Exponentiation}. \\ -\textbf{Input}. Integer $a$, $b$, $k$ and $t$ \\ -\textbf{Output}. $c = a^b$ \\ -\hline \\ -1. $c \leftarrow 1$ \\ -2. for $i$ from $t - 1$ to $0$ do \\ -\hspace{3mm}2.1 If the $i$'th bit of $b$ is a zero then \\ -\hspace{6mm}2.1.1 $c \leftarrow c^2$ \\ -\hspace{3mm}2.2 else do \\ -\hspace{6mm}2.2.1 $c \leftarrow c^{2^k}$ \\ -\hspace{6mm}2.2.2 Extract the $k$ bits from $(b_{i}b_{i-1}\ldots b_{i-(k-1)})$ and store it in $g$. \\ -\hspace{6mm}2.2.3 $c \leftarrow c \cdot a^g$ \\ -\hspace{6mm}2.2.4 $i \leftarrow i - k$ \\ -3. Return $c$. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Sliding Window $k$-ary Exponentiation} -\end{figure} - -Similar to the previous algorithm this algorithm must have a special handler when fewer than $k$ bits are left in the exponent. While this -algorithm requires the same number of squarings it can potentially have fewer multiplications. The pre-computed table $a^g$ is also half -the size as the previous table. - -Consider the exponent $b = 111101011001000_2 \equiv 31432_{10}$ with $k = 3$ using both algorithms. The first algorithm will divide the exponent up as -the following five $3$-bit words $b \equiv \left ( 111, 101, 011, 001, 000 \right )_{2}$. The second algorithm will break the -exponent as $b \equiv \left ( 111, 101, 0, 110, 0, 100, 0 \right )_{2}$. The single digit $0$ in the second representation are where -a single squaring took place instead of a squaring and multiplication. In total the first method requires $10$ multiplications and $18$ -squarings. The second method requires $8$ multiplications and $18$ squarings. - -In general the sliding window method is never slower than the generic $k$-ary method and often it is slightly faster. - -\section{Modular Exponentiation} - -Modular exponentiation is essentially computing the power of a base within a finite field or ring. For example, computing -$d \equiv a^b \mbox{ (mod }c\mbox{)}$ is a modular exponentiation. Instead of first computing $a^b$ and then reducing it -modulo $c$ the intermediate result is reduced modulo $c$ after every squaring or multiplication operation. - -This guarantees that any intermediate result is bounded by $0 \le d \le c^2 - 2c + 1$ and can be reduced modulo $c$ quickly using -one of the algorithms presented in ~REDUCTION~. - -Before the actual modular exponentiation algorithm can be written a wrapper algorithm must be written first. This algorithm -will allow the exponent $b$ to be negative which is computed as $c \equiv \left (1 / a \right )^{\vert b \vert} \mbox{(mod }d\mbox{)}$. The -value of $(1/a) \mbox{ mod }c$ is computed using the modular inverse (\textit{see \ref{sec;modinv}}). If no inverse exists the algorithm -terminates with an error. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_exptmod}. \\ -\textbf{Input}. mp\_int $a$, $b$ and $c$ \\ -\textbf{Output}. $y \equiv g^x \mbox{ (mod }p\mbox{)}$ \\ -\hline \\ -1. If $c.sign = MP\_NEG$ return(\textit{MP\_VAL}). \\ -2. If $b.sign = MP\_NEG$ then \\ -\hspace{3mm}2.1 $g' \leftarrow g^{-1} \mbox{ (mod }c\mbox{)}$ \\ -\hspace{3mm}2.2 $x' \leftarrow \vert x \vert$ \\ -\hspace{3mm}2.3 Compute $d \equiv g'^{x'} \mbox{ (mod }c\mbox{)}$ via recursion. \\ -3. if $p$ is odd \textbf{OR} $p$ is a D.R. modulus then \\ -\hspace{3mm}3.1 Compute $y \equiv g^{x} \mbox{ (mod }p\mbox{)}$ via algorithm mp\_exptmod\_fast. \\ -4. else \\ -\hspace{3mm}4.1 Compute $y \equiv g^{x} \mbox{ (mod }p\mbox{)}$ via algorithm s\_mp\_exptmod. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_exptmod} -\end{figure} - -\textbf{Algorithm mp\_exptmod.} -The first algorithm which actually performs modular exponentiation is algorithm s\_mp\_exptmod. It is a sliding window $k$-ary algorithm -which uses Barrett reduction to reduce the product modulo $p$. The second algorithm mp\_exptmod\_fast performs the same operation -except it uses either Montgomery or Diminished Radix reduction. The two latter reduction algorithms are clumped in the same exponentiation -algorithm since their arguments are essentially the same (\textit{two mp\_ints and one mp\_digit}). - -EXAM,bn_mp_exptmod.c - -In order to keep the algorithms in a known state the first step on line @29,if@ is to reject any negative modulus as input. If the exponent is -negative the algorithm tries to perform a modular exponentiation with the modular inverse of the base $G$. The temporary variable $tmpG$ is assigned -the modular inverse of $G$ and $tmpX$ is assigned the absolute value of $X$. The algorithm will recuse with these new values with a positive -exponent. - -If the exponent is positive the algorithm resumes the exponentiation. Line @63,dr_@ determines if the modulus is of the restricted Diminished Radix -form. If it is not line @65,reduce@ attempts to determine if it is of a unrestricted Diminished Radix form. The integer $dr$ will take on one -of three values. - -\begin{enumerate} -\item $dr = 0$ means that the modulus is not of either restricted or unrestricted Diminished Radix form. -\item $dr = 1$ means that the modulus is of restricted Diminished Radix form. -\item $dr = 2$ means that the modulus is of unrestricted Diminished Radix form. -\end{enumerate} - -Line @69,if@ determines if the fast modular exponentiation algorithm can be used. It is allowed if $dr \ne 0$ or if the modulus is odd. Otherwise, -the slower s\_mp\_exptmod algorithm is used which uses Barrett reduction. - -\subsection{Barrett Modular Exponentiation} - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{s\_mp\_exptmod}. \\ -\textbf{Input}. mp\_int $a$, $b$ and $c$ \\ -\textbf{Output}. $y \equiv g^x \mbox{ (mod }p\mbox{)}$ \\ -\hline \\ -1. $k \leftarrow lg(x)$ \\ -2. $winsize \leftarrow \left \lbrace \begin{array}{ll} - 2 & \mbox{if }k \le 7 \\ - 3 & \mbox{if }7 < k \le 36 \\ - 4 & \mbox{if }36 < k \le 140 \\ - 5 & \mbox{if }140 < k \le 450 \\ - 6 & \mbox{if }450 < k \le 1303 \\ - 7 & \mbox{if }1303 < k \le 3529 \\ - 8 & \mbox{if }3529 < k \\ - \end{array} \right .$ \\ -3. Initialize $2^{winsize}$ mp\_ints in an array named $M$ and one mp\_int named $\mu$ \\ -4. Calculate the $\mu$ required for Barrett Reduction (\textit{mp\_reduce\_setup}). \\ -5. $M_1 \leftarrow g \mbox{ (mod }p\mbox{)}$ \\ -\\ -Setup the table of small powers of $g$. First find $g^{2^{winsize}}$ and then all multiples of it. \\ -6. $k \leftarrow 2^{winsize - 1}$ \\ -7. $M_{k} \leftarrow M_1$ \\ -8. for $ix$ from 0 to $winsize - 2$ do \\ -\hspace{3mm}8.1 $M_k \leftarrow \left ( M_k \right )^2$ (\textit{mp\_sqr}) \\ -\hspace{3mm}8.2 $M_k \leftarrow M_k \mbox{ (mod }p\mbox{)}$ (\textit{mp\_reduce}) \\ -9. for $ix$ from $2^{winsize - 1} + 1$ to $2^{winsize} - 1$ do \\ -\hspace{3mm}9.1 $M_{ix} \leftarrow M_{ix - 1} \cdot M_{1}$ (\textit{mp\_mul}) \\ -\hspace{3mm}9.2 $M_{ix} \leftarrow M_{ix} \mbox{ (mod }p\mbox{)}$ (\textit{mp\_reduce}) \\ -10. $res \leftarrow 1$ \\ -\\ -Start Sliding Window. \\ -11. $mode \leftarrow 0, bitcnt \leftarrow 1, buf \leftarrow 0, digidx \leftarrow x.used - 1, bitcpy \leftarrow 0, bitbuf \leftarrow 0$ \\ -12. Loop \\ -\hspace{3mm}12.1 $bitcnt \leftarrow bitcnt - 1$ \\ -\hspace{3mm}12.2 If $bitcnt = 0$ then do \\ -\hspace{6mm}12.2.1 If $digidx = -1$ goto step 13. \\ -\hspace{6mm}12.2.2 $buf \leftarrow x_{digidx}$ \\ -\hspace{6mm}12.2.3 $digidx \leftarrow digidx - 1$ \\ -\hspace{6mm}12.2.4 $bitcnt \leftarrow lg(\beta)$ \\ -Continued on next page. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm s\_mp\_exptmod} -\end{figure} - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{s\_mp\_exptmod} (\textit{continued}). \\ -\textbf{Input}. mp\_int $a$, $b$ and $c$ \\ -\textbf{Output}. $y \equiv g^x \mbox{ (mod }p\mbox{)}$ \\ -\hline \\ -\hspace{3mm}12.3 $y \leftarrow (buf >> (lg(\beta) - 1))$ AND $1$ \\ -\hspace{3mm}12.4 $buf \leftarrow buf << 1$ \\ -\hspace{3mm}12.5 if $mode = 0$ and $y = 0$ then goto step 12. \\ -\hspace{3mm}12.6 if $mode = 1$ and $y = 0$ then do \\ -\hspace{6mm}12.6.1 $res \leftarrow res^2$ \\ -\hspace{6mm}12.6.2 $res \leftarrow res \mbox{ (mod }p\mbox{)}$ \\ -\hspace{6mm}12.6.3 Goto step 12. \\ -\hspace{3mm}12.7 $bitcpy \leftarrow bitcpy + 1$ \\ -\hspace{3mm}12.8 $bitbuf \leftarrow bitbuf + (y << (winsize - bitcpy))$ \\ -\hspace{3mm}12.9 $mode \leftarrow 2$ \\ -\hspace{3mm}12.10 If $bitcpy = winsize$ then do \\ -\hspace{6mm}Window is full so perform the squarings and single multiplication. \\ -\hspace{6mm}12.10.1 for $ix$ from $0$ to $winsize -1$ do \\ -\hspace{9mm}12.10.1.1 $res \leftarrow res^2$ \\ -\hspace{9mm}12.10.1.2 $res \leftarrow res \mbox{ (mod }p\mbox{)}$ \\ -\hspace{6mm}12.10.2 $res \leftarrow res \cdot M_{bitbuf}$ \\ -\hspace{6mm}12.10.3 $res \leftarrow res \mbox{ (mod }p\mbox{)}$ \\ -\hspace{6mm}Reset the window. \\ -\hspace{6mm}12.10.4 $bitcpy \leftarrow 0, bitbuf \leftarrow 0, mode \leftarrow 1$ \\ -\\ -No more windows left. Check for residual bits of exponent. \\ -13. If $mode = 2$ and $bitcpy > 0$ then do \\ -\hspace{3mm}13.1 for $ix$ form $0$ to $bitcpy - 1$ do \\ -\hspace{6mm}13.1.1 $res \leftarrow res^2$ \\ -\hspace{6mm}13.1.2 $res \leftarrow res \mbox{ (mod }p\mbox{)}$ \\ -\hspace{6mm}13.1.3 $bitbuf \leftarrow bitbuf << 1$ \\ -\hspace{6mm}13.1.4 If $bitbuf$ AND $2^{winsize} \ne 0$ then do \\ -\hspace{9mm}13.1.4.1 $res \leftarrow res \cdot M_{1}$ \\ -\hspace{9mm}13.1.4.2 $res \leftarrow res \mbox{ (mod }p\mbox{)}$ \\ -14. $y \leftarrow res$ \\ -15. Clear $res$, $mu$ and the $M$ array. \\ -16. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm s\_mp\_exptmod (continued)} -\end{figure} - -\textbf{Algorithm s\_mp\_exptmod.} -This algorithm computes the $x$'th power of $g$ modulo $p$ and stores the result in $y$. It takes advantage of the Barrett reduction -algorithm to keep the product small throughout the algorithm. - -The first two steps determine the optimal window size based on the number of bits in the exponent. The larger the exponent the -larger the window size becomes. After a window size $winsize$ has been chosen an array of $2^{winsize}$ mp\_int variables is allocated. This -table will hold the values of $g^x \mbox{ (mod }p\mbox{)}$ for $2^{winsize - 1} \le x < 2^{winsize}$. - -After the table is allocated the first power of $g$ is found. Since $g \ge p$ is allowed it must be first reduced modulo $p$ to make -the rest of the algorithm more efficient. The first element of the table at $2^{winsize - 1}$ is found by squaring $M_1$ successively $winsize - 2$ -times. The rest of the table elements are found by multiplying the previous element by $M_1$ modulo $p$. - -Now that the table is available the sliding window may begin. The following list describes the functions of all the variables in the window. -\begin{enumerate} -\item The variable $mode$ dictates how the bits of the exponent are interpreted. -\begin{enumerate} - \item When $mode = 0$ the bits are ignored since no non-zero bit of the exponent has been seen yet. For example, if the exponent were simply - $1$ then there would be $lg(\beta) - 1$ zero bits before the first non-zero bit. In this case bits are ignored until a non-zero bit is found. - \item When $mode = 1$ a non-zero bit has been seen before and a new $winsize$-bit window has not been formed yet. In this mode leading $0$ bits - are read and a single squaring is performed. If a non-zero bit is read a new window is created. - \item When $mode = 2$ the algorithm is in the middle of forming a window and new bits are appended to the window from the most significant bit - downwards. -\end{enumerate} -\item The variable $bitcnt$ indicates how many bits are left in the current digit of the exponent left to be read. When it reaches zero a new digit - is fetched from the exponent. -\item The variable $buf$ holds the currently read digit of the exponent. -\item The variable $digidx$ is an index into the exponents digits. It starts at the leading digit $x.used - 1$ and moves towards the trailing digit. -\item The variable $bitcpy$ indicates how many bits are in the currently formed window. When it reaches $winsize$ the window is flushed and - the appropriate operations performed. -\item The variable $bitbuf$ holds the current bits of the window being formed. -\end{enumerate} - -All of step 12 is the window processing loop. It will iterate while there are digits available form the exponent to read. The first step -inside this loop is to extract a new digit if no more bits are available in the current digit. If there are no bits left a new digit is -read and if there are no digits left than the loop terminates. - -After a digit is made available step 12.3 will extract the most significant bit of the current digit and move all other bits in the digit -upwards. In effect the digit is read from most significant bit to least significant bit and since the digits are read from leading to -trailing edges the entire exponent is read from most significant bit to least significant bit. - -At step 12.5 if the $mode$ and currently extracted bit $y$ are both zero the bit is ignored and the next bit is read. This prevents the -algorithm from having to perform trivial squaring and reduction operations before the first non-zero bit is read. Step 12.6 and 12.7-10 handle -the two cases of $mode = 1$ and $mode = 2$ respectively. - -FIGU,expt_state,Sliding Window State Diagram - -By step 13 there are no more digits left in the exponent. However, there may be partial bits in the window left. If $mode = 2$ then -a Left-to-Right algorithm is used to process the remaining few bits. - -EXAM,bn_s_mp_exptmod.c - -Lines @31,if@ through @45,}@ determine the optimal window size based on the length of the exponent in bits. The window divisions are sorted -from smallest to greatest so that in each \textbf{if} statement only one condition must be tested. For example, by the \textbf{if} statement -on line @37,if@ the value of $x$ is already known to be greater than $140$. - -The conditional piece of code beginning on line @42,ifdef@ allows the window size to be restricted to five bits. This logic is used to ensure -the table of precomputed powers of $G$ remains relatively small. - -The for loop on line @60,for@ initializes the $M$ array while lines @71,mp_init@ and @75,mp_reduce@ through @85,}@ initialize the reduction -function that will be used for this modulus. - --- More later. - -\section{Quick Power of Two} -Calculating $b = 2^a$ can be performed much quicker than with any of the previous algorithms. Recall that a logical shift left $m << k$ is -equivalent to $m \cdot 2^k$. By this logic when $m = 1$ a quick power of two can be achieved. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_2expt}. \\ -\textbf{Input}. integer $b$ \\ -\textbf{Output}. $a \leftarrow 2^b$ \\ -\hline \\ -1. $a \leftarrow 0$ \\ -2. If $a.alloc < \lfloor b / lg(\beta) \rfloor + 1$ then grow $a$ appropriately. \\ -3. $a.used \leftarrow \lfloor b / lg(\beta) \rfloor + 1$ \\ -4. $a_{\lfloor b / lg(\beta) \rfloor} \leftarrow 1 << (b \mbox{ mod } lg(\beta))$ \\ -5. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_2expt} -\end{figure} - -\textbf{Algorithm mp\_2expt.} - -EXAM,bn_mp_2expt.c - -\chapter{Higher Level Algorithms} - -This chapter discusses the various higher level algorithms that are required to complete a well rounded multiple precision integer package. These -routines are less performance oriented than the algorithms of chapters five, six and seven but are no less important. - -The first section describes a method of integer division with remainder that is universally well known. It provides the signed division logic -for the package. The subsequent section discusses a set of algorithms which allow a single digit to be the 2nd operand for a variety of operations. -These algorithms serve mostly to simplify other algorithms where small constants are required. The last two sections discuss how to manipulate -various representations of integers. For example, converting from an mp\_int to a string of character. - -\section{Integer Division with Remainder} -\label{sec:division} - -Integer division aside from modular exponentiation is the most intensive algorithm to compute. Like addition, subtraction and multiplication -the basis of this algorithm is the long-hand division algorithm taught to school children. Throughout this discussion several common variables -will be used. Let $x$ represent the divisor and $y$ represent the dividend. Let $q$ represent the integer quotient $\lfloor y / x \rfloor$ and -let $r$ represent the remainder $r = y - x \lfloor y / x \rfloor$. The following simple algorithm will be used to start the discussion. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{Radix-$\beta$ Integer Division}. \\ -\textbf{Input}. integer $x$ and $y$ \\ -\textbf{Output}. $q = \lfloor y/x\rfloor, r = y - xq$ \\ -\hline \\ -1. $q \leftarrow 0$ \\ -2. $n \leftarrow \vert \vert y \vert \vert - \vert \vert x \vert \vert$ \\ -3. for $t$ from $n$ down to $0$ do \\ -\hspace{3mm}3.1 Maximize $k$ such that $kx\beta^t$ is less than or equal to $y$ and $(k + 1)x\beta^t$ is greater. \\ -\hspace{3mm}3.2 $q \leftarrow q + k\beta^t$ \\ -\hspace{3mm}3.3 $y \leftarrow y - kx\beta^t$ \\ -4. $r \leftarrow y$ \\ -5. Return($q, r$) \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm Radix-$\beta$ Integer Division} -\label{fig:raddiv} -\end{figure} - -As children we are taught this very simple algorithm for the case of $\beta = 10$. Almost instinctively several optimizations are taught for which -their reason of existing are never explained. For this example let $y = 5471$ represent the dividend and $x = 23$ represent the divisor. - -To find the first digit of the quotient the value of $k$ must be maximized such that $kx\beta^t$ is less than or equal to $y$ and -simultaneously $(k + 1)x\beta^t$ is greater than $y$. Implicitly $k$ is the maximum value the $t$'th digit of the quotient may have. The habitual method -used to find the maximum is to ``eyeball'' the two numbers, typically only the leading digits and quickly estimate a quotient. By only using leading -digits a much simpler division may be used to form an educated guess at what the value must be. In this case $k = \lfloor 54/23\rfloor = 2$ quickly -arises as a possible solution. Indeed $2x\beta^2 = 4600$ is less than $y = 5471$ and simultaneously $(k + 1)x\beta^2 = 6900$ is larger than $y$. -As a result $k\beta^2$ is added to the quotient which now equals $q = 200$ and $4600$ is subtracted from $y$ to give a remainder of $y = 841$. - -Again this process is repeated to produce the quotient digit $k = 3$ which makes the quotient $q = 200 + 3\beta = 230$ and the remainder -$y = 841 - 3x\beta = 181$. Finally the last iteration of the loop produces $k = 7$ which leads to the quotient $q = 230 + 7 = 237$ and the -remainder $y = 181 - 7x = 20$. The final quotient and remainder found are $q = 237$ and $r = y = 20$ which are indeed correct since -$237 \cdot 23 + 20 = 5471$ is true. - -\subsection{Quotient Estimation} -\label{sec:divest} -As alluded to earlier the quotient digit $k$ can be estimated from only the leading digits of both the divisor and dividend. When $p$ leading -digits are used from both the divisor and dividend to form an estimation the accuracy of the estimation rises as $p$ grows. Technically -speaking the estimation is based on assuming the lower $\vert \vert y \vert \vert - p$ and $\vert \vert x \vert \vert - p$ lower digits of the -dividend and divisor are zero. - -The value of the estimation may off by a few values in either direction and in general is fairly correct. A simplification \cite[pp. 271]{TAOCPV2} -of the estimation technique is to use $t + 1$ digits of the dividend and $t$ digits of the divisor, in particularly when $t = 1$. The estimate -using this technique is never too small. For the following proof let $t = \vert \vert y \vert \vert - 1$ and $s = \vert \vert x \vert \vert - 1$ -represent the most significant digits of the dividend and divisor respectively. - -\textbf{Proof.}\textit{ The quotient $\hat k = \lfloor (y_t\beta + y_{t-1}) / x_s \rfloor$ is greater than or equal to -$k = \lfloor y / (x \cdot \beta^{\vert \vert y \vert \vert - \vert \vert x \vert \vert - 1}) \rfloor$. } -The first obvious case is when $\hat k = \beta - 1$ in which case the proof is concluded since the real quotient cannot be larger. For all other -cases $\hat k = \lfloor (y_t\beta + y_{t-1}) / x_s \rfloor$ and $\hat k x_s \ge y_t\beta + y_{t-1} - x_s + 1$. The latter portion of the inequalility -$-x_s + 1$ arises from the fact that a truncated integer division will give the same quotient for at most $x_s - 1$ values. Next a series of -inequalities will prove the hypothesis. - -\begin{equation} -y - \hat k x \le y - \hat k x_s\beta^s -\end{equation} - -This is trivially true since $x \ge x_s\beta^s$. Next we replace $\hat kx_s\beta^s$ by the previous inequality for $\hat kx_s$. - -\begin{equation} -y - \hat k x \le y_t\beta^t + \ldots + y_0 - (y_t\beta^t + y_{t-1}\beta^{t-1} - x_s\beta^t + \beta^s) -\end{equation} - -By simplifying the previous inequality the following inequality is formed. - -\begin{equation} -y - \hat k x \le y_{t-2}\beta^{t-2} + \ldots + y_0 + x_s\beta^s - \beta^s -\end{equation} - -Subsequently, - -\begin{equation} -y_{t-2}\beta^{t-2} + \ldots + y_0 + x_s\beta^s - \beta^s < x_s\beta^s \le x -\end{equation} - -Which proves that $y - \hat kx \le x$ and by consequence $\hat k \ge k$ which concludes the proof. \textbf{QED} - - -\subsection{Normalized Integers} -For the purposes of division a normalized input is when the divisors leading digit $x_n$ is greater than or equal to $\beta / 2$. By multiplying both -$x$ and $y$ by $j = \lfloor (\beta / 2) / x_n \rfloor$ the quotient remains unchanged and the remainder is simply $j$ times the original -remainder. The purpose of normalization is to ensure the leading digit of the divisor is sufficiently large such that the estimated quotient will -lie in the domain of a single digit. Consider the maximum dividend $(\beta - 1) \cdot \beta + (\beta - 1)$ and the minimum divisor $\beta / 2$. - -\begin{equation} -{{\beta^2 - 1} \over { \beta / 2}} \le 2\beta - {2 \over \beta} -\end{equation} - -At most the quotient approaches $2\beta$, however, in practice this will not occur since that would imply the previous quotient digit was too small. - -\subsection{Radix-$\beta$ Division with Remainder} -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_div}. \\ -\textbf{Input}. mp\_int $a, b$ \\ -\textbf{Output}. $c = \lfloor a/b \rfloor$, $d = a - bc$ \\ -\hline \\ -1. If $b = 0$ return(\textit{MP\_VAL}). \\ -2. If $\vert a \vert < \vert b \vert$ then do \\ -\hspace{3mm}2.1 $d \leftarrow a$ \\ -\hspace{3mm}2.2 $c \leftarrow 0$ \\ -\hspace{3mm}2.3 Return(\textit{MP\_OKAY}). \\ -\\ -Setup the quotient to receive the digits. \\ -3. Grow $q$ to $a.used + 2$ digits. \\ -4. $q \leftarrow 0$ \\ -5. $x \leftarrow \vert a \vert , y \leftarrow \vert b \vert$ \\ -6. $sign \leftarrow \left \lbrace \begin{array}{ll} - MP\_ZPOS & \mbox{if }a.sign = b.sign \\ - MP\_NEG & \mbox{otherwise} \\ - \end{array} \right .$ \\ -\\ -Normalize the inputs such that the leading digit of $y$ is greater than or equal to $\beta / 2$. \\ -7. $norm \leftarrow (lg(\beta) - 1) - (\lceil lg(y) \rceil \mbox{ (mod }lg(\beta)\mbox{)})$ \\ -8. $x \leftarrow x \cdot 2^{norm}, y \leftarrow y \cdot 2^{norm}$ \\ -\\ -Find the leading digit of the quotient. \\ -9. $n \leftarrow x.used - 1, t \leftarrow y.used - 1$ \\ -10. $y \leftarrow y \cdot \beta^{n - t}$ \\ -11. While ($x \ge y$) do \\ -\hspace{3mm}11.1 $q_{n - t} \leftarrow q_{n - t} + 1$ \\ -\hspace{3mm}11.2 $x \leftarrow x - y$ \\ -12. $y \leftarrow \lfloor y / \beta^{n-t} \rfloor$ \\ -\\ -Continued on the next page. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_div} -\end{figure} - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_div} (continued). \\ -\textbf{Input}. mp\_int $a, b$ \\ -\textbf{Output}. $c = \lfloor a/b \rfloor$, $d = a - bc$ \\ -\hline \\ -Now find the remainder fo the digits. \\ -13. for $i$ from $n$ down to $(t + 1)$ do \\ -\hspace{3mm}13.1 If $i > x.used$ then jump to the next iteration of this loop. \\ -\hspace{3mm}13.2 If $x_{i} = y_{t}$ then \\ -\hspace{6mm}13.2.1 $q_{i - t - 1} \leftarrow \beta - 1$ \\ -\hspace{3mm}13.3 else \\ -\hspace{6mm}13.3.1 $\hat r \leftarrow x_{i} \cdot \beta + x_{i - 1}$ \\ -\hspace{6mm}13.3.2 $\hat r \leftarrow \lfloor \hat r / y_{t} \rfloor$ \\ -\hspace{6mm}13.3.3 $q_{i - t - 1} \leftarrow \hat r$ \\ -\hspace{3mm}13.4 $q_{i - t - 1} \leftarrow q_{i - t - 1} + 1$ \\ -\\ -Fixup quotient estimation. \\ -\hspace{3mm}13.5 Loop \\ -\hspace{6mm}13.5.1 $q_{i - t - 1} \leftarrow q_{i - t - 1} - 1$ \\ -\hspace{6mm}13.5.2 t$1 \leftarrow 0$ \\ -\hspace{6mm}13.5.3 t$1_0 \leftarrow y_{t - 1}, $ t$1_1 \leftarrow y_t,$ t$1.used \leftarrow 2$ \\ -\hspace{6mm}13.5.4 $t1 \leftarrow t1 \cdot q_{i - t - 1}$ \\ -\hspace{6mm}13.5.5 t$2_0 \leftarrow x_{i - 2}, $ t$2_1 \leftarrow x_{i - 1}, $ t$2_2 \leftarrow x_i, $ t$2.used \leftarrow 3$ \\ -\hspace{6mm}13.5.6 If $\vert t1 \vert > \vert t2 \vert$ then goto step 13.5. \\ -\hspace{3mm}13.6 t$1 \leftarrow y \cdot q_{i - t - 1}$ \\ -\hspace{3mm}13.7 t$1 \leftarrow $ t$1 \cdot \beta^{i - t - 1}$ \\ -\hspace{3mm}13.8 $x \leftarrow x - $ t$1$ \\ -\hspace{3mm}13.9 If $x.sign = MP\_NEG$ then \\ -\hspace{6mm}13.10 t$1 \leftarrow y$ \\ -\hspace{6mm}13.11 t$1 \leftarrow $ t$1 \cdot \beta^{i - t - 1}$ \\ -\hspace{6mm}13.12 $x \leftarrow x + $ t$1$ \\ -\hspace{6mm}13.13 $q_{i - t - 1} \leftarrow q_{i - t - 1} - 1$ \\ -\\ -Finalize the result. \\ -14. Clamp excess digits of $q$ \\ -15. $c \leftarrow q, c.sign \leftarrow sign$ \\ -16. $x.sign \leftarrow a.sign$ \\ -17. $d \leftarrow \lfloor x / 2^{norm} \rfloor$ \\ -18. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_div (continued)} -\end{figure} -\textbf{Algorithm mp\_div.} -This algorithm will calculate quotient and remainder from an integer division given a dividend and divisor. The algorithm is a signed -division and will produce a fully qualified quotient and remainder. - -First the divisor $b$ must be non-zero which is enforced in step one. If the divisor is larger than the dividend than the quotient is implicitly -zero and the remainder is the dividend. - -After the first two trivial cases of inputs are handled the variable $q$ is setup to receive the digits of the quotient. Two unsigned copies of the -divisor $y$ and dividend $x$ are made as well. The core of the division algorithm is an unsigned division and will only work if the values are -positive. Now the two values $x$ and $y$ must be normalized such that the leading digit of $y$ is greater than or equal to $\beta / 2$. -This is performed by shifting both to the left by enough bits to get the desired normalization. - -At this point the division algorithm can begin producing digits of the quotient. Recall that maximum value of the estimation used is -$2\beta - {2 \over \beta}$ which means that a digit of the quotient must be first produced by another means. In this case $y$ is shifted -to the left (\textit{step ten}) so that it has the same number of digits as $x$. The loop on step eleven will subtract multiples of the -shifted copy of $y$ until $x$ is smaller. Since the leading digit of $y$ is greater than or equal to $\beta/2$ this loop will iterate at most two -times to produce the desired leading digit of the quotient. - -Now the remainder of the digits can be produced. The equation $\hat q = \lfloor {{x_i \beta + x_{i-1}}\over y_t} \rfloor$ is used to fairly -accurately approximate the true quotient digit. The estimation can in theory produce an estimation as high as $2\beta - {2 \over \beta}$ but by -induction the upper quotient digit is correct (\textit{as established on step eleven}) and the estimate must be less than $\beta$. - -Recall from section~\ref{sec:divest} that the estimation is never too low but may be too high. The next step of the estimation process is -to refine the estimation. The loop on step 13.5 uses $x_i\beta^2 + x_{i-1}\beta + x_{i-2}$ and $q_{i - t - 1}(y_t\beta + y_{t-1})$ as a higher -order approximation to adjust the quotient digit. - -After both phases of estimation the quotient digit may still be off by a value of one\footnote{This is similar to the error introduced -by optimizing Barrett reduction.}. Steps 13.6 and 13.7 subtract the multiple of the divisor from the dividend (\textit{Similar to step 3.3 of -algorithm~\ref{fig:raddiv}} and then subsequently add a multiple of the divisor if the quotient was too large. - -Now that the quotient has been determine finializing the result is a matter of clamping the quotient, fixing the sizes and de-normalizing the -remainder. An important aspect of this algorithm seemingly overlooked in other descriptions such as that of Algorithm 14.20 HAC \cite[pp. 598]{HAC} -is that when the estimations are being made (\textit{inside the loop on step 13.5}) that the digits $y_{t-1}$, $x_{i-2}$ and $x_{i-1}$ may lie -outside their respective boundaries. For example, if $t = 0$ or $i \le 1$ then the digits would be undefined. In those cases the digits should -respectively be replaced with a zero. - -EXAM,bn_mp_div.c - -The implementation of this algorithm differs slightly from the pseudo code presented previously. In this algorithm either of the quotient $c$ or -remainder $d$ may be passed as a \textbf{NULL} pointer which indicates their value is not desired. For example, the C code to call the division -algorithm with only the quotient is - -\begin{verbatim} -mp_div(&a, &b, &c, NULL); /* c = [a/b] */ -\end{verbatim} - -Lines @108,if@ and @113,if@ handle the two trivial cases of inputs which are division by zero and dividend smaller than the divisor -respectively. After the two trivial cases all of the temporary variables are initialized. Line @147,neg@ determines the sign of -the quotient and line @148,sign@ ensures that both $x$ and $y$ are positive. - -The number of bits in the leading digit is calculated on line @151,norm@. Implictly an mp\_int with $r$ digits will require $lg(\beta)(r-1) + k$ bits -of precision which when reduced modulo $lg(\beta)$ produces the value of $k$. In this case $k$ is the number of bits in the leading digit which is -exactly what is required. For the algorithm to operate $k$ must equal $lg(\beta) - 1$ and when it does not the inputs must be normalized by shifting -them to the left by $lg(\beta) - 1 - k$ bits. - -Throughout the variables $n$ and $t$ will represent the highest digit of $x$ and $y$ respectively. These are first used to produce the -leading digit of the quotient. The loop beginning on line @184,for@ will produce the remainder of the quotient digits. - -The conditional ``continue'' on line @186,continue@ is used to prevent the algorithm from reading past the leading edge of $x$ which can occur when the -algorithm eliminates multiple non-zero digits in a single iteration. This ensures that $x_i$ is always non-zero since by definition the digits -above the $i$'th position $x$ must be zero in order for the quotient to be precise\footnote{Precise as far as integer division is concerned.}. - -Lines @214,t1@, @216,t1@ and @222,t2@ through @225,t2@ manually construct the high accuracy estimations by setting the digits of the two mp\_int -variables directly. - -\section{Single Digit Helpers} - -This section briefly describes a series of single digit helper algorithms which come in handy when working with small constants. All of -the helper functions assume the single digit input is positive and will treat them as such. - -\subsection{Single Digit Addition and Subtraction} - -Both addition and subtraction are performed by ``cheating'' and using mp\_set followed by the higher level addition or subtraction -algorithms. As a result these algorithms are subtantially simpler with a slight cost in performance. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_add\_d}. \\ -\textbf{Input}. mp\_int $a$ and a mp\_digit $b$ \\ -\textbf{Output}. $c = a + b$ \\ -\hline \\ -1. $t \leftarrow b$ (\textit{mp\_set}) \\ -2. $c \leftarrow a + t$ \\ -3. Return(\textit{MP\_OKAY}) \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_add\_d} -\end{figure} - -\textbf{Algorithm mp\_add\_d.} -This algorithm initiates a temporary mp\_int with the value of the single digit and uses algorithm mp\_add to add the two values together. - -EXAM,bn_mp_add_d.c - -Clever use of the letter 't'. - -\subsubsection{Subtraction} -The single digit subtraction algorithm mp\_sub\_d is essentially the same except it uses mp\_sub to subtract the digit from the mp\_int. - -\subsection{Single Digit Multiplication} -Single digit multiplication arises enough in division and radix conversion that it ought to be implement as a special case of the baseline -multiplication algorithm. Essentially this algorithm is a modified version of algorithm s\_mp\_mul\_digs where one of the multiplicands -only has one digit. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_mul\_d}. \\ -\textbf{Input}. mp\_int $a$ and a mp\_digit $b$ \\ -\textbf{Output}. $c = ab$ \\ -\hline \\ -1. $pa \leftarrow a.used$ \\ -2. Grow $c$ to at least $pa + 1$ digits. \\ -3. $oldused \leftarrow c.used$ \\ -4. $c.used \leftarrow pa + 1$ \\ -5. $c.sign \leftarrow a.sign$ \\ -6. $\mu \leftarrow 0$ \\ -7. for $ix$ from $0$ to $pa - 1$ do \\ -\hspace{3mm}7.1 $\hat r \leftarrow \mu + a_{ix}b$ \\ -\hspace{3mm}7.2 $c_{ix} \leftarrow \hat r \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{3mm}7.3 $\mu \leftarrow \lfloor \hat r / \beta \rfloor$ \\ -8. $c_{pa} \leftarrow \mu$ \\ -9. for $ix$ from $pa + 1$ to $oldused$ do \\ -\hspace{3mm}9.1 $c_{ix} \leftarrow 0$ \\ -10. Clamp excess digits of $c$. \\ -11. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_mul\_d} -\end{figure} -\textbf{Algorithm mp\_mul\_d.} -This algorithm quickly multiplies an mp\_int by a small single digit value. It is specially tailored to the job and has a minimal of overhead. -Unlike the full multiplication algorithms this algorithm does not require any significnat temporary storage or memory allocations. - -EXAM,bn_mp_mul_d.c - -In this implementation the destination $c$ may point to the same mp\_int as the source $a$ since the result is written after the digit is -read from the source. This function uses pointer aliases $tmpa$ and $tmpc$ for the digits of $a$ and $c$ respectively. - -\subsection{Single Digit Division} -Like the single digit multiplication algorithm, single digit division is also a fairly common algorithm used in radix conversion. Since the -divisor is only a single digit a specialized variant of the division algorithm can be used to compute the quotient. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_div\_d}. \\ -\textbf{Input}. mp\_int $a$ and a mp\_digit $b$ \\ -\textbf{Output}. $c = \lfloor a / b \rfloor, d = a - cb$ \\ -\hline \\ -1. If $b = 0$ then return(\textit{MP\_VAL}).\\ -2. If $b = 3$ then use algorithm mp\_div\_3 instead. \\ -3. Init $q$ to $a.used$ digits. \\ -4. $q.used \leftarrow a.used$ \\ -5. $q.sign \leftarrow a.sign$ \\ -6. $\hat w \leftarrow 0$ \\ -7. for $ix$ from $a.used - 1$ down to $0$ do \\ -\hspace{3mm}7.1 $\hat w \leftarrow \hat w \beta + a_{ix}$ \\ -\hspace{3mm}7.2 If $\hat w \ge b$ then \\ -\hspace{6mm}7.2.1 $t \leftarrow \lfloor \hat w / b \rfloor$ \\ -\hspace{6mm}7.2.2 $\hat w \leftarrow \hat w \mbox{ (mod }b\mbox{)}$ \\ -\hspace{3mm}7.3 else\\ -\hspace{6mm}7.3.1 $t \leftarrow 0$ \\ -\hspace{3mm}7.4 $q_{ix} \leftarrow t$ \\ -8. $d \leftarrow \hat w$ \\ -9. Clamp excess digits of $q$. \\ -10. $c \leftarrow q$ \\ -11. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_div\_d} -\end{figure} -\textbf{Algorithm mp\_div\_d.} -This algorithm divides the mp\_int $a$ by the single mp\_digit $b$ using an optimized approach. Essentially in every iteration of the -algorithm another digit of the dividend is reduced and another digit of quotient produced. Provided $b < \beta$ the value of $\hat w$ -after step 7.1 will be limited such that $0 \le \lfloor \hat w / b \rfloor < \beta$. - -If the divisor $b$ is equal to three a variant of this algorithm is used which is called mp\_div\_3. It replaces the division by three with -a multiplication by $\lfloor \beta / 3 \rfloor$ and the appropriate shift and residual fixup. In essence it is much like the Barrett reduction -from chapter seven. - -EXAM,bn_mp_div_d.c - -Like the implementation of algorithm mp\_div this algorithm allows either of the quotient or remainder to be passed as a \textbf{NULL} pointer to -indicate the respective value is not required. This allows a trivial single digit modular reduction algorithm, mp\_mod\_d to be created. - -The division and remainder on lines @90,/@ and @91,-@ can be replaced often by a single division on most processors. For example, the 32-bit x86 based -processors can divide a 64-bit quantity by a 32-bit quantity and produce the quotient and remainder simultaneously. Unfortunately the GCC -compiler does not recognize that optimization and will actually produce two function calls to find the quotient and remainder respectively. - -\subsection{Single Digit Root Extraction} - -Finding the $n$'th root of an integer is fairly easy as far as numerical analysis is concerned. Algorithms such as the Newton-Raphson approximation -(\ref{eqn:newton}) series will converge very quickly to a root for any continuous function $f(x)$. - -\begin{equation} -x_{i+1} = x_i - {f(x_i) \over f'(x_i)} -\label{eqn:newton} -\end{equation} - -In this case the $n$'th root is desired and $f(x) = x^n - a$ where $a$ is the integer of which the root is desired. The derivative of $f(x)$ is -simply $f'(x) = nx^{n - 1}$. Of particular importance is that this algorithm will be used over the integers not over the a more continuous domain -such as the real numbers. As a result the root found can be above the true root by few and must be manually adjusted. Ideally at the end of the -algorithm the $n$'th root $b$ of an integer $a$ is desired such that $b^n \le a$. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_n\_root}. \\ -\textbf{Input}. mp\_int $a$ and a mp\_digit $b$ \\ -\textbf{Output}. $c^b \le a$ \\ -\hline \\ -1. If $b$ is even and $a.sign = MP\_NEG$ return(\textit{MP\_VAL}). \\ -2. $sign \leftarrow a.sign$ \\ -3. $a.sign \leftarrow MP\_ZPOS$ \\ -4. t$2 \leftarrow 2$ \\ -5. Loop \\ -\hspace{3mm}5.1 t$1 \leftarrow $ t$2$ \\ -\hspace{3mm}5.2 t$3 \leftarrow $ t$1^{b - 1}$ \\ -\hspace{3mm}5.3 t$2 \leftarrow $ t$3 $ $\cdot$ t$1$ \\ -\hspace{3mm}5.4 t$2 \leftarrow $ t$2 - a$ \\ -\hspace{3mm}5.5 t$3 \leftarrow $ t$3 \cdot b$ \\ -\hspace{3mm}5.6 t$3 \leftarrow \lfloor $t$2 / $t$3 \rfloor$ \\ -\hspace{3mm}5.7 t$2 \leftarrow $ t$1 - $ t$3$ \\ -\hspace{3mm}5.8 If t$1 \ne $ t$2$ then goto step 5. \\ -6. Loop \\ -\hspace{3mm}6.1 t$2 \leftarrow $ t$1^b$ \\ -\hspace{3mm}6.2 If t$2 > a$ then \\ -\hspace{6mm}6.2.1 t$1 \leftarrow $ t$1 - 1$ \\ -\hspace{6mm}6.2.2 Goto step 6. \\ -7. $a.sign \leftarrow sign$ \\ -8. $c \leftarrow $ t$1$ \\ -9. $c.sign \leftarrow sign$ \\ -10. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_n\_root} -\end{figure} -\textbf{Algorithm mp\_n\_root.} -This algorithm finds the integer $n$'th root of an input using the Newton-Raphson approach. It is partially optimized based on the observation -that the numerator of ${f(x) \over f'(x)}$ can be derived from a partial denominator. That is at first the denominator is calculated by finding -$x^{b - 1}$. This value can then be multiplied by $x$ and have $a$ subtracted from it to find the numerator. This saves a total of $b - 1$ -multiplications by t$1$ inside the loop. - -The initial value of the approximation is t$2 = 2$ which allows the algorithm to start with very small values and quickly converge on the -root. Ideally this algorithm is meant to find the $n$'th root of an input where $n$ is bounded by $2 \le n \le 5$. - -EXAM,bn_mp_n_root.c - -\section{Random Number Generation} - -Random numbers come up in a variety of activities from public key cryptography to simple simulations and various randomized algorithms. Pollard-Rho -factoring for example, can make use of random values as starting points to find factors of a composite integer. In this case the algorithm presented -is solely for simulations and not intended for cryptographic use. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_rand}. \\ -\textbf{Input}. An integer $b$ \\ -\textbf{Output}. A pseudo-random number of $b$ digits \\ -\hline \\ -1. $a \leftarrow 0$ \\ -2. If $b \le 0$ return(\textit{MP\_OKAY}) \\ -3. Pick a non-zero random digit $d$. \\ -4. $a \leftarrow a + d$ \\ -5. for $ix$ from 1 to $d - 1$ do \\ -\hspace{3mm}5.1 $a \leftarrow a \cdot \beta$ \\ -\hspace{3mm}5.2 Pick a random digit $d$. \\ -\hspace{3mm}5.3 $a \leftarrow a + d$ \\ -6. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_rand} -\end{figure} -\textbf{Algorithm mp\_rand.} -This algorithm produces a pseudo-random integer of $b$ digits. By ensuring that the first digit is non-zero the algorithm also guarantees that the -final result has at least $b$ digits. It relies heavily on a third-part random number generator which should ideally generate uniformly all of -the integers from $0$ to $\beta - 1$. - -EXAM,bn_mp_rand.c - -\section{Formatted Representations} -The ability to emit a radix-$n$ textual representation of an integer is useful for interacting with human parties. For example, the ability to -be given a string of characters such as ``114585'' and turn it into the radix-$\beta$ equivalent would make it easier to enter numbers -into a program. - -\subsection{Reading Radix-n Input} -For the purposes of this text we will assume that a simple lower ASCII map (\ref{fig:ASC}) is used for the values of from $0$ to $63$ to -printable characters. For example, when the character ``N'' is read it represents the integer $23$. The first $16$ characters of the -map are for the common representations up to hexadecimal. After that they match the ``base64'' encoding scheme which are suitable chosen -such that they are printable. While outputting as base64 may not be too helpful for human operators it does allow communication via non binary -mediums. - -\newpage\begin{figure}[here] -\begin{center} -\begin{tabular}{cc|cc|cc|cc} -\hline \textbf{Value} & \textbf{Char} & \textbf{Value} & \textbf{Char} & \textbf{Value} & \textbf{Char} & \textbf{Value} & \textbf{Char} \\ -\hline -0 & 0 & 1 & 1 & 2 & 2 & 3 & 3 \\ -4 & 4 & 5 & 5 & 6 & 6 & 7 & 7 \\ -8 & 8 & 9 & 9 & 10 & A & 11 & B \\ -12 & C & 13 & D & 14 & E & 15 & F \\ -16 & G & 17 & H & 18 & I & 19 & J \\ -20 & K & 21 & L & 22 & M & 23 & N \\ -24 & O & 25 & P & 26 & Q & 27 & R \\ -28 & S & 29 & T & 30 & U & 31 & V \\ -32 & W & 33 & X & 34 & Y & 35 & Z \\ -36 & a & 37 & b & 38 & c & 39 & d \\ -40 & e & 41 & f & 42 & g & 43 & h \\ -44 & i & 45 & j & 46 & k & 47 & l \\ -48 & m & 49 & n & 50 & o & 51 & p \\ -52 & q & 53 & r & 54 & s & 55 & t \\ -56 & u & 57 & v & 58 & w & 59 & x \\ -60 & y & 61 & z & 62 & $+$ & 63 & $/$ \\ -\hline -\end{tabular} -\end{center} -\caption{Lower ASCII Map} -\label{fig:ASC} -\end{figure} - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_read\_radix}. \\ -\textbf{Input}. A string $str$ of length $sn$ and radix $r$. \\ -\textbf{Output}. The radix-$\beta$ equivalent mp\_int. \\ -\hline \\ -1. If $r < 2$ or $r > 64$ return(\textit{MP\_VAL}). \\ -2. $ix \leftarrow 0$ \\ -3. If $str_0 =$ ``-'' then do \\ -\hspace{3mm}3.1 $ix \leftarrow ix + 1$ \\ -\hspace{3mm}3.2 $sign \leftarrow MP\_NEG$ \\ -4. else \\ -\hspace{3mm}4.1 $sign \leftarrow MP\_ZPOS$ \\ -5. $a \leftarrow 0$ \\ -6. for $iy$ from $ix$ to $sn - 1$ do \\ -\hspace{3mm}6.1 Let $y$ denote the position in the map of $str_{iy}$. \\ -\hspace{3mm}6.2 If $str_{iy}$ is not in the map or $y \ge r$ then goto step 7. \\ -\hspace{3mm}6.3 $a \leftarrow a \cdot r$ \\ -\hspace{3mm}6.4 $a \leftarrow a + y$ \\ -7. If $a \ne 0$ then $a.sign \leftarrow sign$ \\ -8. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_read\_radix} -\end{figure} -\textbf{Algorithm mp\_read\_radix.} -This algorithm will read an ASCII string and produce the radix-$\beta$ mp\_int representation of the same integer. A minus symbol ``-'' may precede the -string to indicate the value is negative, otherwise it is assumed to be positive. The algorithm will read up to $sn$ characters from the input -and will stop when it reads a character it cannot map the algorithm stops reading characters from the string. This allows numbers to be embedded -as part of larger input without any significant problem. - -EXAM,bn_mp_read_radix.c - -\subsection{Generating Radix-$n$ Output} -Generating radix-$n$ output is fairly trivial with a division and remainder algorithm. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_toradix}. \\ -\textbf{Input}. A mp\_int $a$ and an integer $r$\\ -\textbf{Output}. The radix-$r$ representation of $a$ \\ -\hline \\ -1. If $r < 2$ or $r > 64$ return(\textit{MP\_VAL}). \\ -2. If $a = 0$ then $str = $ ``$0$'' and return(\textit{MP\_OKAY}). \\ -3. $t \leftarrow a$ \\ -4. $str \leftarrow$ ``'' \\ -5. if $t.sign = MP\_NEG$ then \\ -\hspace{3mm}5.1 $str \leftarrow str + $ ``-'' \\ -\hspace{3mm}5.2 $t.sign = MP\_ZPOS$ \\ -6. While ($t \ne 0$) do \\ -\hspace{3mm}6.1 $d \leftarrow t \mbox{ (mod }r\mbox{)}$ \\ -\hspace{3mm}6.2 $t \leftarrow \lfloor t / r \rfloor$ \\ -\hspace{3mm}6.3 Look up $d$ in the map and store the equivalent character in $y$. \\ -\hspace{3mm}6.4 $str \leftarrow str + y$ \\ -7. If $str_0 = $``$-$'' then \\ -\hspace{3mm}7.1 Reverse the digits $str_1, str_2, \ldots str_n$. \\ -8. Otherwise \\ -\hspace{3mm}8.1 Reverse the digits $str_0, str_1, \ldots str_n$. \\ -9. Return(\textit{MP\_OKAY}).\\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_toradix} -\end{figure} -\textbf{Algorithm mp\_toradix.} -This algorithm computes the radix-$r$ representation of an mp\_int $a$. The ``digits'' of the representation are extracted by reducing -successive powers of $\lfloor a / r^k \rfloor$ the input modulo $r$ until $r^k > a$. Note that instead of actually dividing by $r^k$ in -each iteration the quotient $\lfloor a / r \rfloor$ is saved for the next iteration. As a result a series of trivial $n \times 1$ divisions -are required instead of a series of $n \times k$ divisions. One design flaw of this approach is that the digits are produced in the reverse order -(see~\ref{fig:mpradix}). To remedy this flaw the digits must be swapped or simply ``reversed''. - -\begin{figure} -\begin{center} -\begin{tabular}{|c|c|c|} -\hline \textbf{Value of $a$} & \textbf{Value of $d$} & \textbf{Value of $str$} \\ -\hline $1234$ & -- & -- \\ -\hline $123$ & $4$ & ``4'' \\ -\hline $12$ & $3$ & ``43'' \\ -\hline $1$ & $2$ & ``432'' \\ -\hline $0$ & $1$ & ``4321'' \\ -\hline -\end{tabular} -\end{center} -\caption{Example of Algorithm mp\_toradix.} -\label{fig:mpradix} -\end{figure} - -EXAM,bn_mp_toradix.c - -\chapter{Number Theoretic Algorithms} -This chapter discusses several fundamental number theoretic algorithms such as the greatest common divisor, least common multiple and Jacobi -symbol computation. These algorithms arise as essential components in several key cryptographic algorithms such as the RSA public key algorithm and -various Sieve based factoring algorithms. - -\section{Greatest Common Divisor} -The greatest common divisor of two integers $a$ and $b$, often denoted as $(a, b)$ is the largest integer $k$ that is a proper divisor of -both $a$ and $b$. That is, $k$ is the largest integer such that $0 \equiv a \mbox{ (mod }k\mbox{)}$ and $0 \equiv b \mbox{ (mod }k\mbox{)}$ occur -simultaneously. - -The most common approach (cite) is to reduce one input modulo another. That is if $a$ and $b$ are divisible by some integer $k$ and if $qa + r = b$ then -$r$ is also divisible by $k$. The reduction pattern follows $\left < a , b \right > \rightarrow \left < b, a \mbox{ mod } b \right >$. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{Greatest Common Divisor (I)}. \\ -\textbf{Input}. Two positive integers $a$ and $b$ greater than zero. \\ -\textbf{Output}. The greatest common divisor $(a, b)$. \\ -\hline \\ -1. While ($b > 0$) do \\ -\hspace{3mm}1.1 $r \leftarrow a \mbox{ (mod }b\mbox{)}$ \\ -\hspace{3mm}1.2 $a \leftarrow b$ \\ -\hspace{3mm}1.3 $b \leftarrow r$ \\ -2. Return($a$). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm Greatest Common Divisor (I)} -\label{fig:gcd1} -\end{figure} - -This algorithm will quickly converge on the greatest common divisor since the residue $r$ tends diminish rapidly. However, divisions are -relatively expensive operations to perform and should ideally be avoided. There is another approach based on a similar relationship of -greatest common divisors. The faster approach is based on the observation that if $k$ divides both $a$ and $b$ it will also divide $a - b$. -In particular, we would like $a - b$ to decrease in magnitude which implies that $b \ge a$. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{Greatest Common Divisor (II)}. \\ -\textbf{Input}. Two positive integers $a$ and $b$ greater than zero. \\ -\textbf{Output}. The greatest common divisor $(a, b)$. \\ -\hline \\ -1. While ($b > 0$) do \\ -\hspace{3mm}1.1 Swap $a$ and $b$ such that $a$ is the smallest of the two. \\ -\hspace{3mm}1.2 $b \leftarrow b - a$ \\ -2. Return($a$). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm Greatest Common Divisor (II)} -\label{fig:gcd2} -\end{figure} - -\textbf{Proof} \textit{Algorithm~\ref{fig:gcd2} will return the greatest common divisor of $a$ and $b$.} -The algorithm in figure~\ref{fig:gcd2} will eventually terminate since $b \ge a$ the subtraction in step 1.2 will be a value less than $b$. In other -words in every iteration that tuple $\left < a, b \right >$ decrease in magnitude until eventually $a = b$. Since both $a$ and $b$ are always -divisible by the greatest common divisor (\textit{until the last iteration}) and in the last iteration of the algorithm $b = 0$, therefore, in the -second to last iteration of the algorithm $b = a$ and clearly $(a, a) = a$ which concludes the proof. \textbf{QED}. - -As a matter of practicality algorithm \ref{fig:gcd1} decreases far too slowly to be useful. Specially if $b$ is much larger than $a$ such that -$b - a$ is still very much larger than $a$. A simple addition to the algorithm is to divide $b - a$ by a power of some integer $p$ which does -not divide the greatest common divisor but will divide $b - a$. In this case ${b - a} \over p$ is also an integer and still divisible by -the greatest common divisor. - -However, instead of factoring $b - a$ to find a suitable value of $p$ the powers of $p$ can be removed from $a$ and $b$ that are in common first. -Then inside the loop whenever $b - a$ is divisible by some power of $p$ it can be safely removed. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{Greatest Common Divisor (III)}. \\ -\textbf{Input}. Two positive integers $a$ and $b$ greater than zero. \\ -\textbf{Output}. The greatest common divisor $(a, b)$. \\ -\hline \\ -1. $k \leftarrow 0$ \\ -2. While $a$ and $b$ are both divisible by $p$ do \\ -\hspace{3mm}2.1 $a \leftarrow \lfloor a / p \rfloor$ \\ -\hspace{3mm}2.2 $b \leftarrow \lfloor b / p \rfloor$ \\ -\hspace{3mm}2.3 $k \leftarrow k + 1$ \\ -3. While $a$ is divisible by $p$ do \\ -\hspace{3mm}3.1 $a \leftarrow \lfloor a / p \rfloor$ \\ -4. While $b$ is divisible by $p$ do \\ -\hspace{3mm}4.1 $b \leftarrow \lfloor b / p \rfloor$ \\ -5. While ($b > 0$) do \\ -\hspace{3mm}5.1 Swap $a$ and $b$ such that $a$ is the smallest of the two. \\ -\hspace{3mm}5.2 $b \leftarrow b - a$ \\ -\hspace{3mm}5.3 While $b$ is divisible by $p$ do \\ -\hspace{6mm}5.3.1 $b \leftarrow \lfloor b / p \rfloor$ \\ -6. Return($a \cdot p^k$). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm Greatest Common Divisor (III)} -\label{fig:gcd3} -\end{figure} - -This algorithm is based on the first except it removes powers of $p$ first and inside the main loop to ensure the tuple $\left < a, b \right >$ -decreases more rapidly. The first loop on step two removes powers of $p$ that are in common. A count, $k$, is kept which will present a common -divisor of $p^k$. After step two the remaining common divisor of $a$ and $b$ cannot be divisible by $p$. This means that $p$ can be safely -divided out of the difference $b - a$ so long as the division leaves no remainder. - -In particular the value of $p$ should be chosen such that the division on step 5.3.1 occur often. It also helps that division by $p$ be easy -to compute. The ideal choice of $p$ is two since division by two amounts to a right logical shift. Another important observation is that by -step five both $a$ and $b$ are odd. Therefore, the diffrence $b - a$ must be even which means that each iteration removes one bit from the -largest of the pair. - -\subsection{Complete Greatest Common Divisor} -The algorithms presented so far cannot handle inputs which are zero or negative. The following algorithm can handle all input cases properly -and will produce the greatest common divisor. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_gcd}. \\ -\textbf{Input}. mp\_int $a$ and $b$ \\ -\textbf{Output}. The greatest common divisor $c = (a, b)$. \\ -\hline \\ -1. If $a = 0$ then \\ -\hspace{3mm}1.1 $c \leftarrow \vert b \vert $ \\ -\hspace{3mm}1.2 Return(\textit{MP\_OKAY}). \\ -2. If $b = 0$ then \\ -\hspace{3mm}2.1 $c \leftarrow \vert a \vert $ \\ -\hspace{3mm}2.2 Return(\textit{MP\_OKAY}). \\ -3. $u \leftarrow \vert a \vert, v \leftarrow \vert b \vert$ \\ -4. $k \leftarrow 0$ \\ -5. While $u.used > 0$ and $v.used > 0$ and $u_0 \equiv v_0 \equiv 0 \mbox{ (mod }2\mbox{)}$ \\ -\hspace{3mm}5.1 $k \leftarrow k + 1$ \\ -\hspace{3mm}5.2 $u \leftarrow \lfloor u / 2 \rfloor$ \\ -\hspace{3mm}5.3 $v \leftarrow \lfloor v / 2 \rfloor$ \\ -6. While $u.used > 0$ and $u_0 \equiv 0 \mbox{ (mod }2\mbox{)}$ \\ -\hspace{3mm}6.1 $u \leftarrow \lfloor u / 2 \rfloor$ \\ -7. While $v.used > 0$ and $v_0 \equiv 0 \mbox{ (mod }2\mbox{)}$ \\ -\hspace{3mm}7.1 $v \leftarrow \lfloor v / 2 \rfloor$ \\ -8. While $v.used > 0$ \\ -\hspace{3mm}8.1 If $\vert u \vert > \vert v \vert$ then \\ -\hspace{6mm}8.1.1 Swap $u$ and $v$. \\ -\hspace{3mm}8.2 $v \leftarrow \vert v \vert - \vert u \vert$ \\ -\hspace{3mm}8.3 While $v.used > 0$ and $v_0 \equiv 0 \mbox{ (mod }2\mbox{)}$ \\ -\hspace{6mm}8.3.1 $v \leftarrow \lfloor v / 2 \rfloor$ \\ -9. $c \leftarrow u \cdot 2^k$ \\ -10. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_gcd} -\end{figure} -\textbf{Algorithm mp\_gcd.} -This algorithm will produce the greatest common divisor of two mp\_ints $a$ and $b$. The algorithm was originally based on Algorithm B of -Knuth \cite[pp. 338]{TAOCPV2} but has been modified to be simpler to explain. In theory it achieves the same asymptotic working time as -Algorithm B and in practice this appears to be true. - -The first two steps handle the cases where either one of or both inputs are zero. If either input is zero the greatest common divisor is the -largest input or zero if they are both zero. If the inputs are not trivial than $u$ and $v$ are assigned the absolute values of -$a$ and $b$ respectively and the algorithm will proceed to reduce the pair. - -Step five will divide out any common factors of two and keep track of the count in the variable $k$. After this step, two is no longer a -factor of the remaining greatest common divisor between $u$ and $v$ and can be safely evenly divided out of either whenever they are even. Step -six and seven ensure that the $u$ and $v$ respectively have no more factors of two. At most only one of the while--loops will iterate since -they cannot both be even. - -By step eight both of $u$ and $v$ are odd which is required for the inner logic. First the pair are swapped such that $v$ is equal to -or greater than $u$. This ensures that the subtraction on step 8.2 will always produce a positive and even result. Step 8.3 removes any -factors of two from the difference $u$ to ensure that in the next iteration of the loop both are once again odd. - -After $v = 0$ occurs the variable $u$ has the greatest common divisor of the pair $\left < u, v \right >$ just after step six. The result -must be adjusted by multiplying by the common factors of two ($2^k$) removed earlier. - -EXAM,bn_mp_gcd.c - -This function makes use of the macros mp\_iszero and mp\_iseven. The former evaluates to $1$ if the input mp\_int is equivalent to the -integer zero otherwise it evaluates to $0$. The latter evaluates to $1$ if the input mp\_int represents a non-zero even integer otherwise -it evaluates to $0$. Note that just because mp\_iseven may evaluate to $0$ does not mean the input is odd, it could also be zero. The three -trivial cases of inputs are handled on lines @23,zero@ through @29,}@. After those lines the inputs are assumed to be non-zero. - -Lines @32,if@ and @36,if@ make local copies $u$ and $v$ of the inputs $a$ and $b$ respectively. At this point the common factors of two -must be divided out of the two inputs. The block starting at line @43,common@ removes common factors of two by first counting the number of trailing -zero bits in both. The local integer $k$ is used to keep track of how many factors of $2$ are pulled out of both values. It is assumed that -the number of factors will not exceed the maximum value of a C ``int'' data type\footnote{Strictly speaking no array in C may have more than -entries than are accessible by an ``int'' so this is not a limitation.}. - -At this point there are no more common factors of two in the two values. The divisions by a power of two on lines @60,div_2d@ and @67,div_2d@ remove -any independent factors of two such that both $u$ and $v$ are guaranteed to be an odd integer before hitting the main body of the algorithm. The while loop -on line @72, while@ performs the reduction of the pair until $v$ is equal to zero. The unsigned comparison and subtraction algorithms are used in -place of the full signed routines since both values are guaranteed to be positive and the result of the subtraction is guaranteed to be non-negative. - -\section{Least Common Multiple} -The least common multiple of a pair of integers is their product divided by their greatest common divisor. For two integers $a$ and $b$ the -least common multiple is normally denoted as $[ a, b ]$ and numerically equivalent to ${ab} \over {(a, b)}$. For example, if $a = 2 \cdot 2 \cdot 3 = 12$ -and $b = 2 \cdot 3 \cdot 3 \cdot 7 = 126$ the least common multiple is ${126 \over {(12, 126)}} = {126 \over 6} = 21$. - -The least common multiple arises often in coding theory as well as number theory. If two functions have periods of $a$ and $b$ respectively they will -collide, that is be in synchronous states, after only $[ a, b ]$ iterations. This is why, for example, random number generators based on -Linear Feedback Shift Registers (LFSR) tend to use registers with periods which are co-prime (\textit{e.g. the greatest common divisor is one.}). -Similarly in number theory if a composite $n$ has two prime factors $p$ and $q$ then maximal order of any unit of $\Z/n\Z$ will be $[ p - 1, q - 1] $. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_lcm}. \\ -\textbf{Input}. mp\_int $a$ and $b$ \\ -\textbf{Output}. The least common multiple $c = [a, b]$. \\ -\hline \\ -1. $c \leftarrow (a, b)$ \\ -2. $t \leftarrow a \cdot b$ \\ -3. $c \leftarrow \lfloor t / c \rfloor$ \\ -4. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_lcm} -\end{figure} -\textbf{Algorithm mp\_lcm.} -This algorithm computes the least common multiple of two mp\_int inputs $a$ and $b$. It computes the least common multiple directly by -dividing the product of the two inputs by their greatest common divisor. - -EXAM,bn_mp_lcm.c - -\section{Jacobi Symbol Computation} -To explain the Jacobi Symbol we shall first discuss the Legendre function\footnote{Arrg. What is the name of this?} off which the Jacobi symbol is -defined. The Legendre function computes whether or not an integer $a$ is a quadratic residue modulo an odd prime $p$. Numerically it is -equivalent to equation \ref{eqn:legendre}. - -\textit{-- Tom, don't be an ass, cite your source here...!} - -\begin{equation} -a^{(p-1)/2} \equiv \begin{array}{rl} - -1 & \mbox{if }a\mbox{ is a quadratic non-residue.} \\ - 0 & \mbox{if }a\mbox{ divides }p\mbox{.} \\ - 1 & \mbox{if }a\mbox{ is a quadratic residue}. - \end{array} \mbox{ (mod }p\mbox{)} -\label{eqn:legendre} -\end{equation} - -\textbf{Proof.} \textit{Equation \ref{eqn:legendre} correctly identifies the residue status of an integer $a$ modulo a prime $p$.} -An integer $a$ is a quadratic residue if the following equation has a solution. - -\begin{equation} -x^2 \equiv a \mbox{ (mod }p\mbox{)} -\label{eqn:root} -\end{equation} - -Consider the following equation. - -\begin{equation} -0 \equiv x^{p-1} - 1 \equiv \left \lbrace \left (x^2 \right )^{(p-1)/2} - a^{(p-1)/2} \right \rbrace + \left ( a^{(p-1)/2} - 1 \right ) \mbox{ (mod }p\mbox{)} -\label{eqn:rooti} -\end{equation} - -Whether equation \ref{eqn:root} has a solution or not equation \ref{eqn:rooti} is always true. If $a^{(p-1)/2} - 1 \equiv 0 \mbox{ (mod }p\mbox{)}$ -then the quantity in the braces must be zero. By reduction, - -\begin{eqnarray} -\left (x^2 \right )^{(p-1)/2} - a^{(p-1)/2} \equiv 0 \nonumber \\ -\left (x^2 \right )^{(p-1)/2} \equiv a^{(p-1)/2} \nonumber \\ -x^2 \equiv a \mbox{ (mod }p\mbox{)} -\end{eqnarray} - -As a result there must be a solution to the quadratic equation and in turn $a$ must be a quadratic residue. If $a$ does not divide $p$ and $a$ -is not a quadratic residue then the only other value $a^{(p-1)/2}$ may be congruent to is $-1$ since -\begin{equation} -0 \equiv a^{p - 1} - 1 \equiv (a^{(p-1)/2} + 1)(a^{(p-1)/2} - 1) \mbox{ (mod }p\mbox{)} -\end{equation} -One of the terms on the right hand side must be zero. \textbf{QED} - -\subsection{Jacobi Symbol} -The Jacobi symbol is a generalization of the Legendre function for any odd non prime moduli $p$ greater than 2. If $p = \prod_{i=0}^n p_i$ then -the Jacobi symbol $\left ( { a \over p } \right )$ is equal to the following equation. - -\begin{equation} -\left ( { a \over p } \right ) = \left ( { a \over p_0} \right ) \left ( { a \over p_1} \right ) \ldots \left ( { a \over p_n} \right ) -\end{equation} - -By inspection if $p$ is prime the Jacobi symbol is equivalent to the Legendre function. The following facts\footnote{See HAC \cite[pp. 72-74]{HAC} for -further details.} will be used to derive an efficient Jacobi symbol algorithm. Where $p$ is an odd integer greater than two and $a, b \in \Z$ the -following are true. - -\begin{enumerate} -\item $\left ( { a \over p} \right )$ equals $-1$, $0$ or $1$. -\item $\left ( { ab \over p} \right ) = \left ( { a \over p} \right )\left ( { b \over p} \right )$. -\item If $a \equiv b$ then $\left ( { a \over p} \right ) = \left ( { b \over p} \right )$. -\item $\left ( { 2 \over p} \right )$ equals $1$ if $p \equiv 1$ or $7 \mbox{ (mod }8\mbox{)}$. Otherwise, it equals $-1$. -\item $\left ( { a \over p} \right ) \equiv \left ( { p \over a} \right ) \cdot (-1)^{(p-1)(a-1)/4}$. More specifically -$\left ( { a \over p} \right ) = \left ( { p \over a} \right )$ if $p \equiv a \equiv 1 \mbox{ (mod }4\mbox{)}$. -\end{enumerate} - -Using these facts if $a = 2^k \cdot a'$ then - -\begin{eqnarray} -\left ( { a \over p } \right ) = \left ( {{2^k} \over p } \right ) \left ( {a' \over p} \right ) \nonumber \\ - = \left ( {2 \over p } \right )^k \left ( {a' \over p} \right ) -\label{eqn:jacobi} -\end{eqnarray} - -By fact five, - -\begin{equation} -\left ( { a \over p } \right ) = \left ( { p \over a } \right ) \cdot (-1)^{(p-1)(a-1)/4} -\end{equation} - -Subsequently by fact three since $p \equiv (p \mbox{ mod }a) \mbox{ (mod }a\mbox{)}$ then - -\begin{equation} -\left ( { a \over p } \right ) = \left ( { {p \mbox{ mod } a} \over a } \right ) \cdot (-1)^{(p-1)(a-1)/4} -\end{equation} - -By putting both observations into equation \ref{eqn:jacobi} the following simplified equation is formed. - -\begin{equation} -\left ( { a \over p } \right ) = \left ( {2 \over p } \right )^k \left ( {{p\mbox{ mod }a'} \over a'} \right ) \cdot (-1)^{(p-1)(a'-1)/4} -\end{equation} - -The value of $\left ( {{p \mbox{ mod }a'} \over a'} \right )$ can be found by using the same equation recursively. The value of -$\left ( {2 \over p } \right )^k$ equals $1$ if $k$ is even otherwise it equals $\left ( {2 \over p } \right )$. Using this approach the -factors of $p$ do not have to be known. Furthermore, if $(a, p) = 1$ then the algorithm will terminate when the recursion requests the -Jacobi symbol computation of $\left ( {1 \over a'} \right )$ which is simply $1$. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_jacobi}. \\ -\textbf{Input}. mp\_int $a$ and $p$, $a \ge 0$, $p \ge 3$, $p \equiv 1 \mbox{ (mod }2\mbox{)}$ \\ -\textbf{Output}. The Jacobi symbol $c = \left ( {a \over p } \right )$. \\ -\hline \\ -1. If $a = 0$ then \\ -\hspace{3mm}1.1 $c \leftarrow 0$ \\ -\hspace{3mm}1.2 Return(\textit{MP\_OKAY}). \\ -2. If $a = 1$ then \\ -\hspace{3mm}2.1 $c \leftarrow 1$ \\ -\hspace{3mm}2.2 Return(\textit{MP\_OKAY}). \\ -3. $a' \leftarrow a$ \\ -4. $k \leftarrow 0$ \\ -5. While $a'.used > 0$ and $a'_0 \equiv 0 \mbox{ (mod }2\mbox{)}$ \\ -\hspace{3mm}5.1 $k \leftarrow k + 1$ \\ -\hspace{3mm}5.2 $a' \leftarrow \lfloor a' / 2 \rfloor$ \\ -6. If $k \equiv 0 \mbox{ (mod }2\mbox{)}$ then \\ -\hspace{3mm}6.1 $s \leftarrow 1$ \\ -7. else \\ -\hspace{3mm}7.1 $r \leftarrow p_0 \mbox{ (mod }8\mbox{)}$ \\ -\hspace{3mm}7.2 If $r = 1$ or $r = 7$ then \\ -\hspace{6mm}7.2.1 $s \leftarrow 1$ \\ -\hspace{3mm}7.3 else \\ -\hspace{6mm}7.3.1 $s \leftarrow -1$ \\ -8. If $p_0 \equiv a'_0 \equiv 3 \mbox{ (mod }4\mbox{)}$ then \\ -\hspace{3mm}8.1 $s \leftarrow -s$ \\ -9. If $a' \ne 1$ then \\ -\hspace{3mm}9.1 $p' \leftarrow p \mbox{ (mod }a'\mbox{)}$ \\ -\hspace{3mm}9.2 $s \leftarrow s \cdot \mbox{mp\_jacobi}(p', a')$ \\ -10. $c \leftarrow s$ \\ -11. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_jacobi} -\end{figure} -\textbf{Algorithm mp\_jacobi.} -This algorithm computes the Jacobi symbol for an arbitrary positive integer $a$ with respect to an odd integer $p$ greater than three. The algorithm -is based on algorithm 2.149 of HAC \cite[pp. 73]{HAC}. - -Step numbers one and two handle the trivial cases of $a = 0$ and $a = 1$ respectively. Step five determines the number of two factors in the -input $a$. If $k$ is even than the term $\left ( { 2 \over p } \right )^k$ must always evaluate to one. If $k$ is odd than the term evaluates to one -if $p_0$ is congruent to one or seven modulo eight, otherwise it evaluates to $-1$. After the the $\left ( { 2 \over p } \right )^k$ term is handled -the $(-1)^{(p-1)(a'-1)/4}$ is computed and multiplied against the current product $s$. The latter term evaluates to one if both $p$ and $a'$ -are congruent to one modulo four, otherwise it evaluates to negative one. - -By step nine if $a'$ does not equal one a recursion is required. Step 9.1 computes $p' \equiv p \mbox{ (mod }a'\mbox{)}$ and will recurse to compute -$\left ( {p' \over a'} \right )$ which is multiplied against the current Jacobi product. - -EXAM,bn_mp_jacobi.c - -As a matter of practicality the variable $a'$ as per the pseudo-code is reprensented by the variable $a1$ since the $'$ symbol is not valid for a C -variable name character. - -The two simple cases of $a = 0$ and $a = 1$ are handled at the very beginning to simplify the algorithm. If the input is non-trivial the algorithm -has to proceed compute the Jacobi. The variable $s$ is used to hold the current Jacobi product. Note that $s$ is merely a C ``int'' data type since -the values it may obtain are merely $-1$, $0$ and $1$. - -After a local copy of $a$ is made all of the factors of two are divided out and the total stored in $k$. Technically only the least significant -bit of $k$ is required, however, it makes the algorithm simpler to follow to perform an addition. In practice an exclusive-or and addition have the same -processor requirements and neither is faster than the other. - -Line @59, if@ through @70, }@ determines the value of $\left ( { 2 \over p } \right )^k$. If the least significant bit of $k$ is zero than -$k$ is even and the value is one. Otherwise, the value of $s$ depends on which residue class $p$ belongs to modulo eight. The value of -$(-1)^{(p-1)(a'-1)/4}$ is compute and multiplied against $s$ on lines @73, if@ through @75, }@. - -Finally, if $a1$ does not equal one the algorithm must recurse and compute $\left ( {p' \over a'} \right )$. - -\textit{-- Comment about default $s$ and such...} - -\section{Modular Inverse} -\label{sec:modinv} -The modular inverse of a number actually refers to the modular multiplicative inverse. Essentially for any integer $a$ such that $(a, p) = 1$ there -exist another integer $b$ such that $ab \equiv 1 \mbox{ (mod }p\mbox{)}$. The integer $b$ is called the multiplicative inverse of $a$ which is -denoted as $b = a^{-1}$. Technically speaking modular inversion is a well defined operation for any finite ring or field not just for rings and -fields of integers. However, the former will be the matter of discussion. - -The simplest approach is to compute the algebraic inverse of the input. That is to compute $b \equiv a^{\Phi(p) - 1}$. If $\Phi(p)$ is the -order of the multiplicative subgroup modulo $p$ then $b$ must be the multiplicative inverse of $a$. The proof of which is trivial. - -\begin{equation} -ab \equiv a \left (a^{\Phi(p) - 1} \right ) \equiv a^{\Phi(p)} \equiv a^0 \equiv 1 \mbox{ (mod }p\mbox{)} -\end{equation} - -However, as simple as this approach may be it has two serious flaws. It requires that the value of $\Phi(p)$ be known which if $p$ is composite -requires all of the prime factors. This approach also is very slow as the size of $p$ grows. - -A simpler approach is based on the observation that solving for the multiplicative inverse is equivalent to solving the linear -Diophantine\footnote{See LeVeque \cite[pp. 40-43]{LeVeque} for more information.} equation. - -\begin{equation} -ab + pq = 1 -\end{equation} - -Where $a$, $b$, $p$ and $q$ are all integers. If such a pair of integers $ \left < b, q \right >$ exist than $b$ is the multiplicative inverse of -$a$ modulo $p$. The extended Euclidean algorithm (Knuth \cite[pp. 342]{TAOCPV2}) can be used to solve such equations provided $(a, p) = 1$. -However, instead of using that algorithm directly a variant known as the binary Extended Euclidean algorithm will be used in its place. The -binary approach is very similar to the binary greatest common divisor algorithm except it will produce a full solution to the Diophantine -equation. - -\subsection{General Case} -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_invmod}. \\ -\textbf{Input}. mp\_int $a$ and $b$, $(a, b) = 1$, $p \ge 2$, $0 < a < p$. \\ -\textbf{Output}. The modular inverse $c \equiv a^{-1} \mbox{ (mod }b\mbox{)}$. \\ -\hline \\ -1. If $b \le 0$ then return(\textit{MP\_VAL}). \\ -2. If $b_0 \equiv 1 \mbox{ (mod }2\mbox{)}$ then use algorithm fast\_mp\_invmod. \\ -3. $x \leftarrow \vert a \vert, y \leftarrow b$ \\ -4. If $x_0 \equiv y_0 \equiv 0 \mbox{ (mod }2\mbox{)}$ then return(\textit{MP\_VAL}). \\ -5. $B \leftarrow 0, C \leftarrow 0, A \leftarrow 1, D \leftarrow 1$ \\ -6. While $u.used > 0$ and $u_0 \equiv 0 \mbox{ (mod }2\mbox{)}$ \\ -\hspace{3mm}6.1 $u \leftarrow \lfloor u / 2 \rfloor$ \\ -\hspace{3mm}6.2 If ($A.used > 0$ and $A_0 \equiv 1 \mbox{ (mod }2\mbox{)}$) or ($B.used > 0$ and $B_0 \equiv 1 \mbox{ (mod }2\mbox{)}$) then \\ -\hspace{6mm}6.2.1 $A \leftarrow A + y$ \\ -\hspace{6mm}6.2.2 $B \leftarrow B - x$ \\ -\hspace{3mm}6.3 $A \leftarrow \lfloor A / 2 \rfloor$ \\ -\hspace{3mm}6.4 $B \leftarrow \lfloor B / 2 \rfloor$ \\ -7. While $v.used > 0$ and $v_0 \equiv 0 \mbox{ (mod }2\mbox{)}$ \\ -\hspace{3mm}7.1 $v \leftarrow \lfloor v / 2 \rfloor$ \\ -\hspace{3mm}7.2 If ($C.used > 0$ and $C_0 \equiv 1 \mbox{ (mod }2\mbox{)}$) or ($D.used > 0$ and $D_0 \equiv 1 \mbox{ (mod }2\mbox{)}$) then \\ -\hspace{6mm}7.2.1 $C \leftarrow C + y$ \\ -\hspace{6mm}7.2.2 $D \leftarrow D - x$ \\ -\hspace{3mm}7.3 $C \leftarrow \lfloor C / 2 \rfloor$ \\ -\hspace{3mm}7.4 $D \leftarrow \lfloor D / 2 \rfloor$ \\ -8. If $u \ge v$ then \\ -\hspace{3mm}8.1 $u \leftarrow u - v$ \\ -\hspace{3mm}8.2 $A \leftarrow A - C$ \\ -\hspace{3mm}8.3 $B \leftarrow B - D$ \\ -9. else \\ -\hspace{3mm}9.1 $v \leftarrow v - u$ \\ -\hspace{3mm}9.2 $C \leftarrow C - A$ \\ -\hspace{3mm}9.3 $D \leftarrow D - B$ \\ -10. If $u \ne 0$ goto step 6. \\ -11. If $v \ne 1$ return(\textit{MP\_VAL}). \\ -12. While $C \le 0$ do \\ -\hspace{3mm}12.1 $C \leftarrow C + b$ \\ -13. While $C \ge b$ do \\ -\hspace{3mm}13.1 $C \leftarrow C - b$ \\ -14. $c \leftarrow C$ \\ -15. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\end{figure} -\textbf{Algorithm mp\_invmod.} -This algorithm computes the modular multiplicative inverse of an integer $a$ modulo an integer $b$. This algorithm is a variation of the -extended binary Euclidean algorithm from HAC \cite[pp. 608]{HAC}. It has been modified to only compute the modular inverse and not a complete -Diophantine solution. - -If $b \le 0$ than the modulus is invalid and MP\_VAL is returned. Similarly if both $a$ and $b$ are even then there cannot be a multiplicative -inverse for $a$ and the error is reported. - -The astute reader will observe that steps seven through nine are very similar to the binary greatest common divisor algorithm mp\_gcd. In this case -the other variables to the Diophantine equation are solved. The algorithm terminates when $u = 0$ in which case the solution is - -\begin{equation} -Ca + Db = v -\end{equation} - -If $v$, the greatest common divisor of $a$ and $b$ is not equal to one then the algorithm will report an error as no inverse exists. Otherwise, $C$ -is the modular inverse of $a$. The actual value of $C$ is congruent to, but not necessarily equal to, the ideal modular inverse which should lie -within $1 \le a^{-1} < b$. Step numbers twelve and thirteen adjust the inverse until it is in range. If the original input $a$ is within $0 < a < p$ -then only a couple of additions or subtractions will be required to adjust the inverse. - -EXAM,bn_mp_invmod.c - -\subsubsection{Odd Moduli} - -When the modulus $b$ is odd the variables $A$ and $C$ are fixed and are not required to compute the inverse. In particular by attempting to solve -the Diophantine $Cb + Da = 1$ only $B$ and $D$ are required to find the inverse of $a$. - -The algorithm fast\_mp\_invmod is a direct adaptation of algorithm mp\_invmod with all all steps involving either $A$ or $C$ removed. This -optimization will halve the time required to compute the modular inverse. - -\section{Primality Tests} - -A non-zero integer $a$ is said to be prime if it is not divisible by any other integer excluding one and itself. For example, $a = 7$ is prime -since the integers $2 \ldots 6$ do not evenly divide $a$. By contrast, $a = 6$ is not prime since $a = 6 = 2 \cdot 3$. - -Prime numbers arise in cryptography considerably as they allow finite fields to be formed. The ability to determine whether an integer is prime or -not quickly has been a viable subject in cryptography and number theory for considerable time. The algorithms that will be presented are all -probablistic algorithms in that when they report an integer is composite it must be composite. However, when the algorithms report an integer is -prime the algorithm may be incorrect. - -As will be discussed it is possible to limit the probability of error so well that for practical purposes the probablity of error might as -well be zero. For the purposes of these discussions let $n$ represent the candidate integer of which the primality is in question. - -\subsection{Trial Division} - -Trial division means to attempt to evenly divide a candidate integer by small prime integers. If the candidate can be evenly divided it obviously -cannot be prime. By dividing by all primes $1 < p \le \sqrt{n}$ this test can actually prove whether an integer is prime. However, such a test -would require a prohibitive amount of time as $n$ grows. - -Instead of dividing by every prime, a smaller, more mangeable set of primes may be used instead. By performing trial division with only a subset -of the primes less than $\sqrt{n} + 1$ the algorithm cannot prove if a candidate is prime. However, often it can prove a candidate is not prime. - -The benefit of this test is that trial division by small values is fairly efficient. Specially compared to the other algorithms that will be -discussed shortly. The probability that this approach correctly identifies a composite candidate when tested with all primes upto $q$ is given by -$1 - {1.12 \over ln(q)}$. The graph (\ref{pic:primality}, will be added later) demonstrates the probability of success for the range -$3 \le q \le 100$. - -At approximately $q = 30$ the gain of performing further tests diminishes fairly quickly. At $q = 90$ further testing is generally not going to -be of any practical use. In the case of LibTomMath the default limit $q = 256$ was chosen since it is not too high and will eliminate -approximately $80\%$ of all candidate integers. The constant \textbf{PRIME\_SIZE} is equal to the number of primes in the test base. The -array \_\_prime\_tab is an array of the first \textbf{PRIME\_SIZE} prime numbers. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_prime\_is\_divisible}. \\ -\textbf{Input}. mp\_int $a$ \\ -\textbf{Output}. $c = 1$ if $n$ is divisible by a small prime, otherwise $c = 0$. \\ -\hline \\ -1. for $ix$ from $0$ to $PRIME\_SIZE$ do \\ -\hspace{3mm}1.1 $d \leftarrow n \mbox{ (mod }\_\_prime\_tab_{ix}\mbox{)}$ \\ -\hspace{3mm}1.2 If $d = 0$ then \\ -\hspace{6mm}1.2.1 $c \leftarrow 1$ \\ -\hspace{6mm}1.2.2 Return(\textit{MP\_OKAY}). \\ -2. $c \leftarrow 0$ \\ -3. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_prime\_is\_divisible} -\end{figure} -\textbf{Algorithm mp\_prime\_is\_divisible.} -This algorithm attempts to determine if a candidate integer $n$ is composite by performing trial divisions. - -EXAM,bn_mp_prime_is_divisible.c - -The algorithm defaults to a return of $0$ in case an error occurs. The values in the prime table are all specified to be in the range of a -mp\_digit. The table \_\_prime\_tab is defined in the following file. - -EXAM,bn_prime_tab.c - -Note that there are two possible tables. When an mp\_digit is 7-bits long only the primes upto $127$ may be included, otherwise the primes -upto $1619$ are used. Note that the value of \textbf{PRIME\_SIZE} is a constant dependent on the size of a mp\_digit. - -\subsection{The Fermat Test} -The Fermat test is probably one the oldest tests to have a non-trivial probability of success. It is based on the fact that if $n$ is in -fact prime then $a^{n} \equiv a \mbox{ (mod }n\mbox{)}$ for all $0 < a < n$. The reason being that if $n$ is prime than the order of -the multiplicative sub group is $n - 1$. Any base $a$ must have an order which divides $n - 1$ and as such $a^n$ is equivalent to -$a^1 = a$. - -If $n$ is composite then any given base $a$ does not have to have a period which divides $n - 1$. In which case -it is possible that $a^n \nequiv a \mbox{ (mod }n\mbox{)}$. However, this test is not absolute as it is possible that the order -of a base will divide $n - 1$ which would then be reported as prime. Such a base yields what is known as a Fermat pseudo-prime. Several -integers known as Carmichael numbers will be a pseudo-prime to all valid bases. Fortunately such numbers are extremely rare as $n$ grows -in size. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_prime\_fermat}. \\ -\textbf{Input}. mp\_int $a$ and $b$, $a \ge 2$, $0 < b < a$. \\ -\textbf{Output}. $c = 1$ if $b^a \equiv b \mbox{ (mod }a\mbox{)}$, otherwise $c = 0$. \\ -\hline \\ -1. $t \leftarrow b^a \mbox{ (mod }a\mbox{)}$ \\ -2. If $t = b$ then \\ -\hspace{3mm}2.1 $c = 1$ \\ -3. else \\ -\hspace{3mm}3.1 $c = 0$ \\ -4. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_prime\_fermat} -\end{figure} -\textbf{Algorithm mp\_prime\_fermat.} -This algorithm determines whether an mp\_int $a$ is a Fermat prime to the base $b$ or not. It uses a single modular exponentiation to -determine the result. - -EXAM,bn_mp_prime_fermat.c - -\subsection{The Miller-Rabin Test} -The Miller-Rabin (citation) test is another primality test which has tighter error bounds than the Fermat test specifically with sequentially chosen -candidate integers. The algorithm is based on the observation that if $n - 1 = 2^kr$ and if $b^r \nequiv \pm 1$ then after upto $k - 1$ squarings the -value must be equal to $-1$. The squarings are stopped as soon as $-1$ is observed. If the value of $1$ is observed first it means that -some value not congruent to $\pm 1$ when squared equals one which cannot occur if $n$ is prime. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_prime\_miller\_rabin}. \\ -\textbf{Input}. mp\_int $a$ and $b$, $a \ge 2$, $0 < b < a$. \\ -\textbf{Output}. $c = 1$ if $a$ is a Miller-Rabin prime to the base $a$, otherwise $c = 0$. \\ -\hline -1. $a' \leftarrow a - 1$ \\ -2. $r \leftarrow n1$ \\ -3. $c \leftarrow 0, s \leftarrow 0$ \\ -4. While $r.used > 0$ and $r_0 \equiv 0 \mbox{ (mod }2\mbox{)}$ \\ -\hspace{3mm}4.1 $s \leftarrow s + 1$ \\ -\hspace{3mm}4.2 $r \leftarrow \lfloor r / 2 \rfloor$ \\ -5. $y \leftarrow b^r \mbox{ (mod }a\mbox{)}$ \\ -6. If $y \nequiv \pm 1$ then \\ -\hspace{3mm}6.1 $j \leftarrow 1$ \\ -\hspace{3mm}6.2 While $j \le (s - 1)$ and $y \nequiv a'$ \\ -\hspace{6mm}6.2.1 $y \leftarrow y^2 \mbox{ (mod }a\mbox{)}$ \\ -\hspace{6mm}6.2.2 If $y = 1$ then goto step 8. \\ -\hspace{6mm}6.2.3 $j \leftarrow j + 1$ \\ -\hspace{3mm}6.3 If $y \nequiv a'$ goto step 8. \\ -7. $c \leftarrow 1$\\ -8. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_prime\_miller\_rabin} -\end{figure} -\textbf{Algorithm mp\_prime\_miller\_rabin.} -This algorithm performs one trial round of the Miller-Rabin algorithm to the base $b$. It will set $c = 1$ if the algorithm cannot determine -if $b$ is composite or $c = 0$ if $b$ is provably composite. The values of $s$ and $r$ are computed such that $a' = a - 1 = 2^sr$. - -If the value $y \equiv b^r$ is congruent to $\pm 1$ then the algorithm cannot prove if $a$ is composite or not. Otherwise, the algorithm will -square $y$ upto $s - 1$ times stopping only when $y \equiv -1$. If $y^2 \equiv 1$ and $y \nequiv \pm 1$ then the algorithm can report that $a$ -is provably composite. If the algorithm performs $s - 1$ squarings and $y \nequiv -1$ then $a$ is provably composite. If $a$ is not provably -composite then it is \textit{probably} prime. - -EXAM,bn_mp_prime_miller_rabin.c - - - - -\backmatter -\appendix -\begin{thebibliography}{ABCDEF} -\bibitem[1]{TAOCPV2} -Donald Knuth, \textit{The Art of Computer Programming}, Third Edition, Volume Two, Seminumerical Algorithms, Addison-Wesley, 1998 - -\bibitem[2]{HAC} -A. Menezes, P. van Oorschot, S. Vanstone, \textit{Handbook of Applied Cryptography}, CRC Press, 1996 - -\bibitem[3]{ROSE} -Michael Rosing, \textit{Implementing Elliptic Curve Cryptography}, Manning Publications, 1999 - -\bibitem[4]{COMBA} -Paul G. Comba, \textit{Exponentiation Cryptosystems on the IBM PC}. IBM Systems Journal 29(4): 526-538 (1990) - -\bibitem[5]{KARA} -A. Karatsuba, Doklay Akad. Nauk SSSR 145 (1962), pp.293-294 - -\bibitem[6]{KARAP} -Andre Weimerskirch and Christof Paar, \textit{Generalizations of the Karatsuba Algorithm for Polynomial Multiplication}, Submitted to Design, Codes and Cryptography, March 2002 - -\bibitem[7]{BARRETT} -Paul Barrett, \textit{Implementing the Rivest Shamir and Adleman Public Key Encryption Algorithm on a Standard Digital Signal Processor}, Advances in Cryptology, Crypto '86, Springer-Verlag. - -\bibitem[8]{MONT} -P.L.Montgomery. \textit{Modular multiplication without trial division}. Mathematics of Computation, 44(170):519-521, April 1985. - -\bibitem[9]{DRMET} -Chae Hoon Lim and Pil Joong Lee, \textit{Generating Efficient Primes for Discrete Log Cryptosystems}, POSTECH Information Research Laboratories - -\bibitem[10]{MMB} -J. Daemen and R. Govaerts and J. Vandewalle, \textit{Block ciphers based on Modular Arithmetic}, State and {P}rogress in the {R}esearch of {C}ryptography, 1993, pp. 80-89 - -\bibitem[11]{RSAREF} -R.L. Rivest, A. Shamir, L. Adleman, \textit{A Method for Obtaining Digital Signatures and Public-Key Cryptosystems} - -\bibitem[12]{DHREF} -Whitfield Diffie, Martin E. Hellman, \textit{New Directions in Cryptography}, IEEE Transactions on Information Theory, 1976 - -\bibitem[13]{IEEE} -IEEE Standard for Binary Floating-Point Arithmetic (ANSI/IEEE Std 754-1985) - -\bibitem[14]{GMP} -GNU Multiple Precision (GMP), \url{http://www.swox.com/gmp/} - -\bibitem[15]{MPI} -Multiple Precision Integer Library (MPI), Michael Fromberger, \url{http://thayer.dartmouth.edu/~sting/mpi/} - -\bibitem[16]{OPENSSL} -OpenSSL Cryptographic Toolkit, \url{http://openssl.org} - -\bibitem[17]{LIP} -Large Integer Package, \url{http://home.hetnet.nl/~ecstr/LIP.zip} - -\bibitem[18]{ISOC} -JTC1/SC22/WG14, ISO/IEC 9899:1999, ``A draft rationale for the C99 standard.'' - -\bibitem[19]{JAVA} -The Sun Java Website, \url{http://java.sun.com/} - -\end{thebibliography} - -\input{tommath.ind} - -\end{document} diff --git a/libtommath/tommath.tex b/libtommath/tommath.tex deleted file mode 100644 index d70b64b..0000000 --- a/libtommath/tommath.tex +++ /dev/null @@ -1,10816 +0,0 @@ -\documentclass[b5paper]{book} -\usepackage{hyperref} -\usepackage{makeidx} -\usepackage{amssymb} -\usepackage{color} -\usepackage{alltt} -\usepackage{graphicx} -\usepackage{layout} -\def\union{\cup} -\def\intersect{\cap} -\def\getsrandom{\stackrel{\rm R}{\gets}} -\def\cross{\times} -\def\cat{\hspace{0.5em} \| \hspace{0.5em}} -\def\catn{$\|$} -\def\divides{\hspace{0.3em} | \hspace{0.3em}} -\def\nequiv{\not\equiv} -\def\approx{\raisebox{0.2ex}{\mbox{\small $\sim$}}} -\def\lcm{{\rm lcm}} -\def\gcd{{\rm gcd}} -\def\log{{\rm log}} -\def\ord{{\rm ord}} -\def\abs{{\mathit abs}} -\def\rep{{\mathit rep}} -\def\mod{{\mathit\ mod\ }} -\renewcommand{\pmod}[1]{\ ({\rm mod\ }{#1})} -\newcommand{\floor}[1]{\left\lfloor{#1}\right\rfloor} -\newcommand{\ceil}[1]{\left\lceil{#1}\right\rceil} -\def\Or{{\rm\ or\ }} -\def\And{{\rm\ and\ }} -\def\iff{\hspace{1em}\Longleftrightarrow\hspace{1em}} -\def\implies{\Rightarrow} -\def\undefined{{\rm ``undefined"}} -\def\Proof{\vspace{1ex}\noindent {\bf Proof:}\hspace{1em}} -\let\oldphi\phi -\def\phi{\varphi} -\def\Pr{{\rm Pr}} -\newcommand{\str}[1]{{\mathbf{#1}}} -\def\F{{\mathbb F}} -\def\N{{\mathbb N}} -\def\Z{{\mathbb Z}} -\def\R{{\mathbb R}} -\def\C{{\mathbb C}} -\def\Q{{\mathbb Q}} -\definecolor{DGray}{gray}{0.5} -\newcommand{\emailaddr}[1]{\mbox{$<${#1}$>$}} -\def\twiddle{\raisebox{0.3ex}{\mbox{\tiny $\sim$}}} -\def\gap{\vspace{0.5ex}} -\makeindex -\begin{document} -\frontmatter -\pagestyle{empty} -\title{Multi--Precision Math} -\author{\mbox{ -%\begin{small} -\begin{tabular}{c} -Tom St Denis \\ -Algonquin College \\ -\\ -Mads Rasmussen \\ -Open Communications Security \\ -\\ -Greg Rose \\ -QUALCOMM Australia \\ -\end{tabular} -%\end{small} -} -} -\maketitle -This text has been placed in the public domain. This text corresponds to the v0.39 release of the -LibTomMath project. - -This text is formatted to the international B5 paper size of 176mm wide by 250mm tall using the \LaTeX{} -{\em book} macro package and the Perl {\em booker} package. - -\tableofcontents -\listoffigures -\chapter*{Prefaces} -When I tell people about my LibTom projects and that I release them as public domain they are often puzzled. -They ask why I did it and especially why I continue to work on them for free. The best I can explain it is ``Because I can.'' -Which seems odd and perhaps too terse for adult conversation. I often qualify it with ``I am able, I am willing.'' which -perhaps explains it better. I am the first to admit there is not anything that special with what I have done. Perhaps -others can see that too and then we would have a society to be proud of. My LibTom projects are what I am doing to give -back to society in the form of tools and knowledge that can help others in their endeavours. - -I started writing this book because it was the most logical task to further my goal of open academia. The LibTomMath source -code itself was written to be easy to follow and learn from. There are times, however, where pure C source code does not -explain the algorithms properly. Hence this book. The book literally starts with the foundation of the library and works -itself outwards to the more complicated algorithms. The use of both pseudo--code and verbatim source code provides a duality -of ``theory'' and ``practice'' that the computer science students of the world shall appreciate. I never deviate too far -from relatively straightforward algebra and I hope that this book can be a valuable learning asset. - -This book and indeed much of the LibTom projects would not exist in their current form if it was not for a plethora -of kind people donating their time, resources and kind words to help support my work. Writing a text of significant -length (along with the source code) is a tiresome and lengthy process. Currently the LibTom project is four years old, -comprises of literally thousands of users and over 100,000 lines of source code, TeX and other material. People like Mads and Greg -were there at the beginning to encourage me to work well. It is amazing how timely validation from others can boost morale to -continue the project. Definitely my parents were there for me by providing room and board during the many months of work in 2003. - -To my many friends whom I have met through the years I thank you for the good times and the words of encouragement. I hope I -honour your kind gestures with this project. - -Open Source. Open Academia. Open Minds. - -\begin{flushright} Tom St Denis \end{flushright} - -\newpage -I found the opportunity to work with Tom appealing for several reasons, not only could I broaden my own horizons, but also -contribute to educate others facing the problem of having to handle big number mathematical calculations. - -This book is Tom's child and he has been caring and fostering the project ever since the beginning with a clear mind of -how he wanted the project to turn out. I have helped by proofreading the text and we have had several discussions about -the layout and language used. - -I hold a masters degree in cryptography from the University of Southern Denmark and have always been interested in the -practical aspects of cryptography. - -Having worked in the security consultancy business for several years in S\~{a}o Paulo, Brazil, I have been in touch with a -great deal of work in which multiple precision mathematics was needed. Understanding the possibilities for speeding up -multiple precision calculations is often very important since we deal with outdated machine architecture where modular -reductions, for example, become painfully slow. - -This text is for people who stop and wonder when first examining algorithms such as RSA for the first time and asks -themselves, ``You tell me this is only secure for large numbers, fine; but how do you implement these numbers?'' - -\begin{flushright} -Mads Rasmussen - -S\~{a}o Paulo - SP - -Brazil -\end{flushright} - -\newpage -It's all because I broke my leg. That just happened to be at about the same time that Tom asked for someone to review the section of the book about -Karatsuba multiplication. I was laid up, alone and immobile, and thought ``Why not?'' I vaguely knew what Karatsuba multiplication was, but not -really, so I thought I could help, learn, and stop myself from watching daytime cable TV, all at once. - -At the time of writing this, I've still not met Tom or Mads in meatspace. I've been following Tom's progress since his first splash on the -sci.crypt Usenet news group. I watched him go from a clueless newbie, to the cryptographic equivalent of a reformed smoker, to a real -contributor to the field, over a period of about two years. I've been impressed with his obvious intelligence, and astounded by his productivity. -Of course, he's young enough to be my own child, so he doesn't have my problems with staying awake. - -When I reviewed that single section of the book, in its very earliest form, I was very pleasantly surprised. So I decided to collaborate more fully, -and at least review all of it, and perhaps write some bits too. There's still a long way to go with it, and I have watched a number of close -friends go through the mill of publication, so I think that the way to go is longer than Tom thinks it is. Nevertheless, it's a good effort, -and I'm pleased to be involved with it. - -\begin{flushright} -Greg Rose, Sydney, Australia, June 2003. -\end{flushright} - -\mainmatter -\pagestyle{headings} -\chapter{Introduction} -\section{Multiple Precision Arithmetic} - -\subsection{What is Multiple Precision Arithmetic?} -When we think of long-hand arithmetic such as addition or multiplication we rarely consider the fact that we instinctively -raise or lower the precision of the numbers we are dealing with. For example, in decimal we almost immediate can -reason that $7$ times $6$ is $42$. However, $42$ has two digits of precision as opposed to one digit we started with. -Further multiplications of say $3$ result in a larger precision result $126$. In these few examples we have multiple -precisions for the numbers we are working with. Despite the various levels of precision a single subset\footnote{With the occasional optimization.} - of algorithms can be designed to accomodate them. - -By way of comparison a fixed or single precision operation would lose precision on various operations. For example, in -the decimal system with fixed precision $6 \cdot 7 = 2$. - -Essentially at the heart of computer based multiple precision arithmetic are the same long-hand algorithms taught in -schools to manually add, subtract, multiply and divide. - -\subsection{The Need for Multiple Precision Arithmetic} -The most prevalent need for multiple precision arithmetic, often referred to as ``bignum'' math, is within the implementation -of public-key cryptography algorithms. Algorithms such as RSA \cite{RSAREF} and Diffie-Hellman \cite{DHREF} require -integers of significant magnitude to resist known cryptanalytic attacks. For example, at the time of this writing a -typical RSA modulus would be at least greater than $10^{309}$. However, modern programming languages such as ISO C \cite{ISOC} and -Java \cite{JAVA} only provide instrinsic support for integers which are relatively small and single precision. - -\begin{figure}[!here] -\begin{center} -\begin{tabular}{|r|c|} -\hline \textbf{Data Type} & \textbf{Range} \\ -\hline char & $-128 \ldots 127$ \\ -\hline short & $-32768 \ldots 32767$ \\ -\hline long & $-2147483648 \ldots 2147483647$ \\ -\hline long long & $-9223372036854775808 \ldots 9223372036854775807$ \\ -\hline -\end{tabular} -\end{center} -\caption{Typical Data Types for the C Programming Language} -\label{fig:ISOC} -\end{figure} - -The largest data type guaranteed to be provided by the ISO C programming -language\footnote{As per the ISO C standard. However, each compiler vendor is allowed to augment the precision as they -see fit.} can only represent values up to $10^{19}$ as shown in figure \ref{fig:ISOC}. On its own the C language is -insufficient to accomodate the magnitude required for the problem at hand. An RSA modulus of magnitude $10^{19}$ could be -trivially factored\footnote{A Pollard-Rho factoring would take only $2^{16}$ time.} on the average desktop computer, -rendering any protocol based on the algorithm insecure. Multiple precision algorithms solve this very problem by -extending the range of representable integers while using single precision data types. - -Most advancements in fast multiple precision arithmetic stem from the need for faster and more efficient cryptographic -primitives. Faster modular reduction and exponentiation algorithms such as Barrett's algorithm, which have appeared in -various cryptographic journals, can render algorithms such as RSA and Diffie-Hellman more efficient. In fact, several -major companies such as RSA Security, Certicom and Entrust have built entire product lines on the implementation and -deployment of efficient algorithms. - -However, cryptography is not the only field of study that can benefit from fast multiple precision integer routines. -Another auxiliary use of multiple precision integers is high precision floating point data types. -The basic IEEE \cite{IEEE} standard floating point type is made up of an integer mantissa $q$, an exponent $e$ and a sign bit $s$. -Numbers are given in the form $n = q \cdot b^e \cdot -1^s$ where $b = 2$ is the most common base for IEEE. Since IEEE -floating point is meant to be implemented in hardware the precision of the mantissa is often fairly small -(\textit{23, 48 and 64 bits}). The mantissa is merely an integer and a multiple precision integer could be used to create -a mantissa of much larger precision than hardware alone can efficiently support. This approach could be useful where -scientific applications must minimize the total output error over long calculations. - -Yet another use for large integers is within arithmetic on polynomials of large characteristic (i.e. $GF(p)[x]$ for large $p$). -In fact the library discussed within this text has already been used to form a polynomial basis library\footnote{See \url{http://poly.libtomcrypt.org} for more details.}. - -\subsection{Benefits of Multiple Precision Arithmetic} -\index{precision} -The benefit of multiple precision representations over single or fixed precision representations is that -no precision is lost while representing the result of an operation which requires excess precision. For example, -the product of two $n$-bit integers requires at least $2n$ bits of precision to be represented faithfully. A multiple -precision algorithm would augment the precision of the destination to accomodate the result while a single precision system -would truncate excess bits to maintain a fixed level of precision. - -It is possible to implement algorithms which require large integers with fixed precision algorithms. For example, elliptic -curve cryptography (\textit{ECC}) is often implemented on smartcards by fixing the precision of the integers to the maximum -size the system will ever need. Such an approach can lead to vastly simpler algorithms which can accomodate the -integers required even if the host platform cannot natively accomodate them\footnote{For example, the average smartcard -processor has an 8 bit accumulator.}. However, as efficient as such an approach may be, the resulting source code is not -normally very flexible. It cannot, at runtime, accomodate inputs of higher magnitude than the designer anticipated. - -Multiple precision algorithms have the most overhead of any style of arithmetic. For the the most part the -overhead can be kept to a minimum with careful planning, but overall, it is not well suited for most memory starved -platforms. However, multiple precision algorithms do offer the most flexibility in terms of the magnitude of the -inputs. That is, the same algorithms based on multiple precision integers can accomodate any reasonable size input -without the designer's explicit forethought. This leads to lower cost of ownership for the code as it only has to -be written and tested once. - -\section{Purpose of This Text} -The purpose of this text is to instruct the reader regarding how to implement efficient multiple precision algorithms. -That is to not only explain a limited subset of the core theory behind the algorithms but also the various ``house keeping'' -elements that are neglected by authors of other texts on the subject. Several well reknowned texts \cite{TAOCPV2,HAC} -give considerably detailed explanations of the theoretical aspects of algorithms and often very little information -regarding the practical implementation aspects. - -In most cases how an algorithm is explained and how it is actually implemented are two very different concepts. For -example, the Handbook of Applied Cryptography (\textit{HAC}), algorithm 14.7 on page 594, gives a relatively simple -algorithm for performing multiple precision integer addition. However, the description lacks any discussion concerning -the fact that the two integer inputs may be of differing magnitudes. As a result the implementation is not as simple -as the text would lead people to believe. Similarly the division routine (\textit{algorithm 14.20, pp. 598}) does not -discuss how to handle sign or handle the dividend's decreasing magnitude in the main loop (\textit{step \#3}). - -Both texts also do not discuss several key optimal algorithms required such as ``Comba'' and Karatsuba multipliers -and fast modular inversion, which we consider practical oversights. These optimal algorithms are vital to achieve -any form of useful performance in non-trivial applications. - -To solve this problem the focus of this text is on the practical aspects of implementing a multiple precision integer -package. As a case study the ``LibTomMath''\footnote{Available at \url{http://math.libtomcrypt.com}} package is used -to demonstrate algorithms with real implementations\footnote{In the ISO C programming language.} that have been field -tested and work very well. The LibTomMath library is freely available on the Internet for all uses and this text -discusses a very large portion of the inner workings of the library. - -The algorithms that are presented will always include at least one ``pseudo-code'' description followed -by the actual C source code that implements the algorithm. The pseudo-code can be used to implement the same -algorithm in other programming languages as the reader sees fit. - -This text shall also serve as a walkthrough of the creation of multiple precision algorithms from scratch. Showing -the reader how the algorithms fit together as well as where to start on various taskings. - -\section{Discussion and Notation} -\subsection{Notation} -A multiple precision integer of $n$-digits shall be denoted as $x = (x_{n-1}, \ldots, x_1, x_0)_{ \beta }$ and represent -the integer $x \equiv \sum_{i=0}^{n-1} x_i\beta^i$. The elements of the array $x$ are said to be the radix $\beta$ digits -of the integer. For example, $x = (1,2,3)_{10}$ would represent the integer -$1\cdot 10^2 + 2\cdot10^1 + 3\cdot10^0 = 123$. - -\index{mp\_int} -The term ``mp\_int'' shall refer to a composite structure which contains the digits of the integer it represents, as well -as auxilary data required to manipulate the data. These additional members are discussed further in section -\ref{sec:MPINT}. For the purposes of this text a ``multiple precision integer'' and an ``mp\_int'' are assumed to be -synonymous. When an algorithm is specified to accept an mp\_int variable it is assumed the various auxliary data members -are present as well. An expression of the type \textit{variablename.item} implies that it should evaluate to the -member named ``item'' of the variable. For example, a string of characters may have a member ``length'' which would -evaluate to the number of characters in the string. If the string $a$ equals ``hello'' then it follows that -$a.length = 5$. - -For certain discussions more generic algorithms are presented to help the reader understand the final algorithm used -to solve a given problem. When an algorithm is described as accepting an integer input it is assumed the input is -a plain integer with no additional multiple-precision members. That is, algorithms that use integers as opposed to -mp\_ints as inputs do not concern themselves with the housekeeping operations required such as memory management. These -algorithms will be used to establish the relevant theory which will subsequently be used to describe a multiple -precision algorithm to solve the same problem. - -\subsection{Precision Notation} -The variable $\beta$ represents the radix of a single digit of a multiple precision integer and -must be of the form $q^p$ for $q, p \in \Z^+$. A single precision variable must be able to represent integers in -the range $0 \le x < q \beta$ while a double precision variable must be able to represent integers in the range -$0 \le x < q \beta^2$. The extra radix-$q$ factor allows additions and subtractions to proceed without truncation of the -carry. Since all modern computers are binary, it is assumed that $q$ is two. - -\index{mp\_digit} \index{mp\_word} -Within the source code that will be presented for each algorithm, the data type \textbf{mp\_digit} will represent -a single precision integer type, while, the data type \textbf{mp\_word} will represent a double precision integer type. In -several algorithms (notably the Comba routines) temporary results will be stored in arrays of double precision mp\_words. -For the purposes of this text $x_j$ will refer to the $j$'th digit of a single precision array and $\hat x_j$ will refer to -the $j$'th digit of a double precision array. Whenever an expression is to be assigned to a double precision -variable it is assumed that all single precision variables are promoted to double precision during the evaluation. -Expressions that are assigned to a single precision variable are truncated to fit within the precision of a single -precision data type. - -For example, if $\beta = 10^2$ a single precision data type may represent a value in the -range $0 \le x < 10^3$, while a double precision data type may represent a value in the range $0 \le x < 10^5$. Let -$a = 23$ and $b = 49$ represent two single precision variables. The single precision product shall be written -as $c \leftarrow a \cdot b$ while the double precision product shall be written as $\hat c \leftarrow a \cdot b$. -In this particular case, $\hat c = 1127$ and $c = 127$. The most significant digit of the product would not fit -in a single precision data type and as a result $c \ne \hat c$. - -\subsection{Algorithm Inputs and Outputs} -Within the algorithm descriptions all variables are assumed to be scalars of either single or double precision -as indicated. The only exception to this rule is when variables have been indicated to be of type mp\_int. This -distinction is important as scalars are often used as array indicies and various other counters. - -\subsection{Mathematical Expressions} -The $\lfloor \mbox{ } \rfloor$ brackets imply an expression truncated to an integer not greater than the expression -itself. For example, $\lfloor 5.7 \rfloor = 5$. Similarly the $\lceil \mbox{ } \rceil$ brackets imply an expression -rounded to an integer not less than the expression itself. For example, $\lceil 5.1 \rceil = 6$. Typically when -the $/$ division symbol is used the intention is to perform an integer division with truncation. For example, -$5/2 = 2$ which will often be written as $\lfloor 5/2 \rfloor = 2$ for clarity. When an expression is written as a -fraction a real value division is implied, for example ${5 \over 2} = 2.5$. - -The norm of a multiple precision integer, for example $\vert \vert x \vert \vert$, will be used to represent the number of digits in the representation -of the integer. For example, $\vert \vert 123 \vert \vert = 3$ and $\vert \vert 79452 \vert \vert = 5$. - -\subsection{Work Effort} -\index{big-Oh} -To measure the efficiency of the specified algorithms, a modified big-Oh notation is used. In this system all -single precision operations are considered to have the same cost\footnote{Except where explicitly noted.}. -That is a single precision addition, multiplication and division are assumed to take the same time to -complete. While this is generally not true in practice, it will simplify the discussions considerably. - -Some algorithms have slight advantages over others which is why some constants will not be removed in -the notation. For example, a normal baseline multiplication (section \ref{sec:basemult}) requires $O(n^2)$ work while a -baseline squaring (section \ref{sec:basesquare}) requires $O({{n^2 + n}\over 2})$ work. In standard big-Oh notation these -would both be said to be equivalent to $O(n^2)$. However, -in the context of the this text this is not the case as the magnitude of the inputs will typically be rather small. As a -result small constant factors in the work effort will make an observable difference in algorithm efficiency. - -All of the algorithms presented in this text have a polynomial time work level. That is, of the form -$O(n^k)$ for $n, k \in \Z^{+}$. This will help make useful comparisons in terms of the speed of the algorithms and how -various optimizations will help pay off in the long run. - -\section{Exercises} -Within the more advanced chapters a section will be set aside to give the reader some challenging exercises related to -the discussion at hand. These exercises are not designed to be prize winning problems, but instead to be thought -provoking. Wherever possible the problems are forward minded, stating problems that will be answered in subsequent -chapters. The reader is encouraged to finish the exercises as they appear to get a better understanding of the -subject material. - -That being said, the problems are designed to affirm knowledge of a particular subject matter. Students in particular -are encouraged to verify they can answer the problems correctly before moving on. - -Similar to the exercises of \cite[pp. ix]{TAOCPV2} these exercises are given a scoring system based on the difficulty of -the problem. However, unlike \cite{TAOCPV2} the problems do not get nearly as hard. The scoring of these -exercises ranges from one (the easiest) to five (the hardest). The following table sumarizes the -scoring system used. - -\begin{figure}[here] -\begin{center} -\begin{small} -\begin{tabular}{|c|l|} -\hline $\left [ 1 \right ]$ & An easy problem that should only take the reader a manner of \\ - & minutes to solve. Usually does not involve much computer time \\ - & to solve. \\ -\hline $\left [ 2 \right ]$ & An easy problem that involves a marginal amount of computer \\ - & time usage. Usually requires a program to be written to \\ - & solve the problem. \\ -\hline $\left [ 3 \right ]$ & A moderately hard problem that requires a non-trivial amount \\ - & of work. Usually involves trivial research and development of \\ - & new theory from the perspective of a student. \\ -\hline $\left [ 4 \right ]$ & A moderately hard problem that involves a non-trivial amount \\ - & of work and research, the solution to which will demonstrate \\ - & a higher mastery of the subject matter. \\ -\hline $\left [ 5 \right ]$ & A hard problem that involves concepts that are difficult for a \\ - & novice to solve. Solutions to these problems will demonstrate a \\ - & complete mastery of the given subject. \\ -\hline -\end{tabular} -\end{small} -\end{center} -\caption{Exercise Scoring System} -\end{figure} - -Problems at the first level are meant to be simple questions that the reader can answer quickly without programming a solution or -devising new theory. These problems are quick tests to see if the material is understood. Problems at the second level -are also designed to be easy but will require a program or algorithm to be implemented to arrive at the answer. These -two levels are essentially entry level questions. - -Problems at the third level are meant to be a bit more difficult than the first two levels. The answer is often -fairly obvious but arriving at an exacting solution requires some thought and skill. These problems will almost always -involve devising a new algorithm or implementing a variation of another algorithm previously presented. Readers who can -answer these questions will feel comfortable with the concepts behind the topic at hand. - -Problems at the fourth level are meant to be similar to those of the level three questions except they will require -additional research to be completed. The reader will most likely not know the answer right away, nor will the text provide -the exact details of the answer until a subsequent chapter. - -Problems at the fifth level are meant to be the hardest -problems relative to all the other problems in the chapter. People who can correctly answer fifth level problems have a -mastery of the subject matter at hand. - -Often problems will be tied together. The purpose of this is to start a chain of thought that will be discussed in future chapters. The reader -is encouraged to answer the follow-up problems and try to draw the relevance of problems. - -\section{Introduction to LibTomMath} - -\subsection{What is LibTomMath?} -LibTomMath is a free and open source multiple precision integer library written entirely in portable ISO C. By portable it -is meant that the library does not contain any code that is computer platform dependent or otherwise problematic to use on -any given platform. - -The library has been successfully tested under numerous operating systems including Unix\footnote{All of these -trademarks belong to their respective rightful owners.}, MacOS, Windows, Linux, PalmOS and on standalone hardware such -as the Gameboy Advance. The library is designed to contain enough functionality to be able to develop applications such -as public key cryptosystems and still maintain a relatively small footprint. - -\subsection{Goals of LibTomMath} - -Libraries which obtain the most efficiency are rarely written in a high level programming language such as C. However, -even though this library is written entirely in ISO C, considerable care has been taken to optimize the algorithm implementations within the -library. Specifically the code has been written to work well with the GNU C Compiler (\textit{GCC}) on both x86 and ARM -processors. Wherever possible, highly efficient algorithms, such as Karatsuba multiplication, sliding window -exponentiation and Montgomery reduction have been provided to make the library more efficient. - -Even with the nearly optimal and specialized algorithms that have been included the Application Programing Interface -(\textit{API}) has been kept as simple as possible. Often generic place holder routines will make use of specialized -algorithms automatically without the developer's specific attention. One such example is the generic multiplication -algorithm \textbf{mp\_mul()} which will automatically use Toom--Cook, Karatsuba, Comba or baseline multiplication -based on the magnitude of the inputs and the configuration of the library. - -Making LibTomMath as efficient as possible is not the only goal of the LibTomMath project. Ideally the library should -be source compatible with another popular library which makes it more attractive for developers to use. In this case the -MPI library was used as a API template for all the basic functions. MPI was chosen because it is another library that fits -in the same niche as LibTomMath. Even though LibTomMath uses MPI as the template for the function names and argument -passing conventions, it has been written from scratch by Tom St Denis. - -The project is also meant to act as a learning tool for students, the logic being that no easy-to-follow ``bignum'' -library exists which can be used to teach computer science students how to perform fast and reliable multiple precision -integer arithmetic. To this end the source code has been given quite a few comments and algorithm discussion points. - -\section{Choice of LibTomMath} -LibTomMath was chosen as the case study of this text not only because the author of both projects is one and the same but -for more worthy reasons. Other libraries such as GMP \cite{GMP}, MPI \cite{MPI}, LIP \cite{LIP} and OpenSSL -\cite{OPENSSL} have multiple precision integer arithmetic routines but would not be ideal for this text for -reasons that will be explained in the following sub-sections. - -\subsection{Code Base} -The LibTomMath code base is all portable ISO C source code. This means that there are no platform dependent conditional -segments of code littered throughout the source. This clean and uncluttered approach to the library means that a -developer can more readily discern the true intent of a given section of source code without trying to keep track of -what conditional code will be used. - -The code base of LibTomMath is well organized. Each function is in its own separate source code file -which allows the reader to find a given function very quickly. On average there are $76$ lines of code per source -file which makes the source very easily to follow. By comparison MPI and LIP are single file projects making code tracing -very hard. GMP has many conditional code segments which also hinder tracing. - -When compiled with GCC for the x86 processor and optimized for speed the entire library is approximately $100$KiB\footnote{The notation ``KiB'' means $2^{10}$ octets, similarly ``MiB'' means $2^{20}$ octets.} - which is fairly small compared to GMP (over $250$KiB). LibTomMath is slightly larger than MPI (which compiles to about -$50$KiB) but LibTomMath is also much faster and more complete than MPI. - -\subsection{API Simplicity} -LibTomMath is designed after the MPI library and shares the API design. Quite often programs that use MPI will build -with LibTomMath without change. The function names correlate directly to the action they perform. Almost all of the -functions share the same parameter passing convention. The learning curve is fairly shallow with the API provided -which is an extremely valuable benefit for the student and developer alike. - -The LIP library is an example of a library with an API that is awkward to work with. LIP uses function names that are often ``compressed'' to -illegible short hand. LibTomMath does not share this characteristic. - -The GMP library also does not return error codes. Instead it uses a POSIX.1 \cite{POSIX1} signal system where errors -are signaled to the host application. This happens to be the fastest approach but definitely not the most versatile. In -effect a math error (i.e. invalid input, heap error, etc) can cause a program to stop functioning which is definitely -undersireable in many situations. - -\subsection{Optimizations} -While LibTomMath is certainly not the fastest library (GMP often beats LibTomMath by a factor of two) it does -feature a set of optimal algorithms for tasks such as modular reduction, exponentiation, multiplication and squaring. GMP -and LIP also feature such optimizations while MPI only uses baseline algorithms with no optimizations. GMP lacks a few -of the additional modular reduction optimizations that LibTomMath features\footnote{At the time of this writing GMP -only had Barrett and Montgomery modular reduction algorithms.}. - -LibTomMath is almost always an order of magnitude faster than the MPI library at computationally expensive tasks such as modular -exponentiation. In the grand scheme of ``bignum'' libraries LibTomMath is faster than the average library and usually -slower than the best libraries such as GMP and OpenSSL by only a small factor. - -\subsection{Portability and Stability} -LibTomMath will build ``out of the box'' on any platform equipped with a modern version of the GNU C Compiler -(\textit{GCC}). This means that without changes the library will build without configuration or setting up any -variables. LIP and MPI will build ``out of the box'' as well but have numerous known bugs. Most notably the author of -MPI has recently stopped working on his library and LIP has long since been discontinued. - -GMP requires a configuration script to run and will not build out of the box. GMP and LibTomMath are still in active -development and are very stable across a variety of platforms. - -\subsection{Choice} -LibTomMath is a relatively compact, well documented, highly optimized and portable library which seems only natural for -the case study of this text. Various source files from the LibTomMath project will be included within the text. However, -the reader is encouraged to download their own copy of the library to actually be able to work with the library. - -\chapter{Getting Started} -\section{Library Basics} -The trick to writing any useful library of source code is to build a solid foundation and work outwards from it. First, -a problem along with allowable solution parameters should be identified and analyzed. In this particular case the -inability to accomodate multiple precision integers is the problem. Futhermore, the solution must be written -as portable source code that is reasonably efficient across several different computer platforms. - -After a foundation is formed the remainder of the library can be designed and implemented in a hierarchical fashion. -That is, to implement the lowest level dependencies first and work towards the most abstract functions last. For example, -before implementing a modular exponentiation algorithm one would implement a modular reduction algorithm. -By building outwards from a base foundation instead of using a parallel design methodology the resulting project is -highly modular. Being highly modular is a desirable property of any project as it often means the resulting product -has a small footprint and updates are easy to perform. - -Usually when I start a project I will begin with the header files. I define the data types I think I will need and -prototype the initial functions that are not dependent on other functions (within the library). After I -implement these base functions I prototype more dependent functions and implement them. The process repeats until -I implement all of the functions I require. For example, in the case of LibTomMath I implemented functions such as -mp\_init() well before I implemented mp\_mul() and even further before I implemented mp\_exptmod(). As an example as to -why this design works note that the Karatsuba and Toom-Cook multipliers were written \textit{after} the -dependent function mp\_exptmod() was written. Adding the new multiplication algorithms did not require changes to the -mp\_exptmod() function itself and lowered the total cost of ownership (\textit{so to speak}) and of development -for new algorithms. This methodology allows new algorithms to be tested in a complete framework with relative ease. - -\begin{center} -\begin{figure}[here] -\includegraphics{pics/design_process.ps} -\caption{Design Flow of the First Few Original LibTomMath Functions.} -\label{pic:design_process} -\end{figure} -\end{center} - -Only after the majority of the functions were in place did I pursue a less hierarchical approach to auditing and optimizing -the source code. For example, one day I may audit the multipliers and the next day the polynomial basis functions. - -It only makes sense to begin the text with the preliminary data types and support algorithms required as well. -This chapter discusses the core algorithms of the library which are the dependents for every other algorithm. - -\section{What is a Multiple Precision Integer?} -Recall that most programming languages, in particular ISO C \cite{ISOC}, only have fixed precision data types that on their own cannot -be used to represent values larger than their precision will allow. The purpose of multiple precision algorithms is -to use fixed precision data types to create and manipulate multiple precision integers which may represent values -that are very large. - -As a well known analogy, school children are taught how to form numbers larger than nine by prepending more radix ten digits. In the decimal system -the largest single digit value is $9$. However, by concatenating digits together larger numbers may be represented. Newly prepended digits -(\textit{to the left}) are said to be in a different power of ten column. That is, the number $123$ can be described as having a $1$ in the hundreds -column, $2$ in the tens column and $3$ in the ones column. Or more formally $123 = 1 \cdot 10^2 + 2 \cdot 10^1 + 3 \cdot 10^0$. Computer based -multiple precision arithmetic is essentially the same concept. Larger integers are represented by adjoining fixed -precision computer words with the exception that a different radix is used. - -What most people probably do not think about explicitly are the various other attributes that describe a multiple precision -integer. For example, the integer $154_{10}$ has two immediately obvious properties. First, the integer is positive, -that is the sign of this particular integer is positive as opposed to negative. Second, the integer has three digits in -its representation. There is an additional property that the integer posesses that does not concern pencil-and-paper -arithmetic. The third property is how many digits placeholders are available to hold the integer. - -The human analogy of this third property is ensuring there is enough space on the paper to write the integer. For example, -if one starts writing a large number too far to the right on a piece of paper they will have to erase it and move left. -Similarly, computer algorithms must maintain strict control over memory usage to ensure that the digits of an integer -will not exceed the allowed boundaries. These three properties make up what is known as a multiple precision -integer or mp\_int for short. - -\subsection{The mp\_int Structure} -\label{sec:MPINT} -The mp\_int structure is the ISO C based manifestation of what represents a multiple precision integer. The ISO C standard does not provide for -any such data type but it does provide for making composite data types known as structures. The following is the structure definition -used within LibTomMath. - -\index{mp\_int} -\begin{figure}[here] -\begin{center} -\begin{small} -%\begin{verbatim} -\begin{tabular}{|l|} -\hline -typedef struct \{ \\ -\hspace{3mm}int used, alloc, sign;\\ -\hspace{3mm}mp\_digit *dp;\\ -\} \textbf{mp\_int}; \\ -\hline -\end{tabular} -%\end{verbatim} -\end{small} -\caption{The mp\_int Structure} -\label{fig:mpint} -\end{center} -\end{figure} - -The mp\_int structure (fig. \ref{fig:mpint}) can be broken down as follows. - -\begin{enumerate} -\item The \textbf{used} parameter denotes how many digits of the array \textbf{dp} contain the digits used to represent -a given integer. The \textbf{used} count must be positive (or zero) and may not exceed the \textbf{alloc} count. - -\item The \textbf{alloc} parameter denotes how -many digits are available in the array to use by functions before it has to increase in size. When the \textbf{used} count -of a result would exceed the \textbf{alloc} count all of the algorithms will automatically increase the size of the -array to accommodate the precision of the result. - -\item The pointer \textbf{dp} points to a dynamically allocated array of digits that represent the given multiple -precision integer. It is padded with $(\textbf{alloc} - \textbf{used})$ zero digits. The array is maintained in a least -significant digit order. As a pencil and paper analogy the array is organized such that the right most digits are stored -first starting at the location indexed by zero\footnote{In C all arrays begin at zero.} in the array. For example, -if \textbf{dp} contains $\lbrace a, b, c, \ldots \rbrace$ where \textbf{dp}$_0 = a$, \textbf{dp}$_1 = b$, \textbf{dp}$_2 = c$, $\ldots$ then -it would represent the integer $a + b\beta + c\beta^2 + \ldots$ - -\index{MP\_ZPOS} \index{MP\_NEG} -\item The \textbf{sign} parameter denotes the sign as either zero/positive (\textbf{MP\_ZPOS}) or negative (\textbf{MP\_NEG}). -\end{enumerate} - -\subsubsection{Valid mp\_int Structures} -Several rules are placed on the state of an mp\_int structure and are assumed to be followed for reasons of efficiency. -The only exceptions are when the structure is passed to initialization functions such as mp\_init() and mp\_init\_copy(). - -\begin{enumerate} -\item The value of \textbf{alloc} may not be less than one. That is \textbf{dp} always points to a previously allocated -array of digits. -\item The value of \textbf{used} may not exceed \textbf{alloc} and must be greater than or equal to zero. -\item The value of \textbf{used} implies the digit at index $(used - 1)$ of the \textbf{dp} array is non-zero. That is, -leading zero digits in the most significant positions must be trimmed. - \begin{enumerate} - \item Digits in the \textbf{dp} array at and above the \textbf{used} location must be zero. - \end{enumerate} -\item The value of \textbf{sign} must be \textbf{MP\_ZPOS} if \textbf{used} is zero; -this represents the mp\_int value of zero. -\end{enumerate} - -\section{Argument Passing} -A convention of argument passing must be adopted early on in the development of any library. Making the function -prototypes consistent will help eliminate many headaches in the future as the library grows to significant complexity. -In LibTomMath the multiple precision integer functions accept parameters from left to right as pointers to mp\_int -structures. That means that the source (input) operands are placed on the left and the destination (output) on the right. -Consider the following examples. - -\begin{verbatim} - mp_mul(&a, &b, &c); /* c = a * b */ - mp_add(&a, &b, &a); /* a = a + b */ - mp_sqr(&a, &b); /* b = a * a */ -\end{verbatim} - -The left to right order is a fairly natural way to implement the functions since it lets the developer read aloud the -functions and make sense of them. For example, the first function would read ``multiply a and b and store in c''. - -Certain libraries (\textit{LIP by Lenstra for instance}) accept parameters the other way around, to mimic the order -of assignment expressions. That is, the destination (output) is on the left and arguments (inputs) are on the right. In -truth, it is entirely a matter of preference. In the case of LibTomMath the convention from the MPI library has been -adopted. - -Another very useful design consideration, provided for in LibTomMath, is whether to allow argument sources to also be a -destination. For example, the second example (\textit{mp\_add}) adds $a$ to $b$ and stores in $a$. This is an important -feature to implement since it allows the calling functions to cut down on the number of variables it must maintain. -However, to implement this feature specific care has to be given to ensure the destination is not modified before the -source is fully read. - -\section{Return Values} -A well implemented application, no matter what its purpose, should trap as many runtime errors as possible and return them -to the caller. By catching runtime errors a library can be guaranteed to prevent undefined behaviour. However, the end -developer can still manage to cause a library to crash. For example, by passing an invalid pointer an application may -fault by dereferencing memory not owned by the application. - -In the case of LibTomMath the only errors that are checked for are related to inappropriate inputs (division by zero for -instance) and memory allocation errors. It will not check that the mp\_int passed to any function is valid nor -will it check pointers for validity. Any function that can cause a runtime error will return an error code as an -\textbf{int} data type with one of the following values (fig \ref{fig:errcodes}). - -\index{MP\_OKAY} \index{MP\_VAL} \index{MP\_MEM} -\begin{figure}[here] -\begin{center} -\begin{tabular}{|l|l|} -\hline \textbf{Value} & \textbf{Meaning} \\ -\hline \textbf{MP\_OKAY} & The function was successful \\ -\hline \textbf{MP\_VAL} & One of the input value(s) was invalid \\ -\hline \textbf{MP\_MEM} & The function ran out of heap memory \\ -\hline -\end{tabular} -\end{center} -\caption{LibTomMath Error Codes} -\label{fig:errcodes} -\end{figure} - -When an error is detected within a function it should free any memory it allocated, often during the initialization of -temporary mp\_ints, and return as soon as possible. The goal is to leave the system in the same state it was when the -function was called. Error checking with this style of API is fairly simple. - -\begin{verbatim} - int err; - if ((err = mp_add(&a, &b, &c)) != MP_OKAY) { - printf("Error: %s\n", mp_error_to_string(err)); - exit(EXIT_FAILURE); - } -\end{verbatim} - -The GMP \cite{GMP} library uses C style \textit{signals} to flag errors which is of questionable use. Not all errors are fatal -and it was not deemed ideal by the author of LibTomMath to force developers to have signal handlers for such cases. - -\section{Initialization and Clearing} -The logical starting point when actually writing multiple precision integer functions is the initialization and -clearing of the mp\_int structures. These two algorithms will be used by the majority of the higher level algorithms. - -Given the basic mp\_int structure an initialization routine must first allocate memory to hold the digits of -the integer. Often it is optimal to allocate a sufficiently large pre-set number of digits even though -the initial integer will represent zero. If only a single digit were allocated quite a few subsequent re-allocations -would occur when operations are performed on the integers. There is a tradeoff between how many default digits to allocate -and how many re-allocations are tolerable. Obviously allocating an excessive amount of digits initially will waste -memory and become unmanageable. - -If the memory for the digits has been successfully allocated then the rest of the members of the structure must -be initialized. Since the initial state of an mp\_int is to represent the zero integer, the allocated digits must be set -to zero. The \textbf{used} count set to zero and \textbf{sign} set to \textbf{MP\_ZPOS}. - -\subsection{Initializing an mp\_int} -An mp\_int is said to be initialized if it is set to a valid, preferably default, state such that all of the members of the -structure are set to valid values. The mp\_init algorithm will perform such an action. - -\index{mp\_init} -\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_init}. \\ -\textbf{Input}. An mp\_int $a$ \\ -\textbf{Output}. Allocate memory and initialize $a$ to a known valid mp\_int state. \\ -\hline \\ -1. Allocate memory for \textbf{MP\_PREC} digits. \\ -2. If the allocation failed return(\textit{MP\_MEM}) \\ -3. for $n$ from $0$ to $MP\_PREC - 1$ do \\ -\hspace{3mm}3.1 $a_n \leftarrow 0$\\ -4. $a.sign \leftarrow MP\_ZPOS$\\ -5. $a.used \leftarrow 0$\\ -6. $a.alloc \leftarrow MP\_PREC$\\ -7. Return(\textit{MP\_OKAY})\\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_init} -\end{figure} - -\textbf{Algorithm mp\_init.} -The purpose of this function is to initialize an mp\_int structure so that the rest of the library can properly -manipulte it. It is assumed that the input may not have had any of its members previously initialized which is certainly -a valid assumption if the input resides on the stack. - -Before any of the members such as \textbf{sign}, \textbf{used} or \textbf{alloc} are initialized the memory for -the digits is allocated. If this fails the function returns before setting any of the other members. The \textbf{MP\_PREC} -name represents a constant\footnote{Defined in the ``tommath.h'' header file within LibTomMath.} -used to dictate the minimum precision of newly initialized mp\_int integers. Ideally, it is at least equal to the smallest -precision number you'll be working with. - -Allocating a block of digits at first instead of a single digit has the benefit of lowering the number of usually slow -heap operations later functions will have to perform in the future. If \textbf{MP\_PREC} is set correctly the slack -memory and the number of heap operations will be trivial. - -Once the allocation has been made the digits have to be set to zero as well as the \textbf{used}, \textbf{sign} and -\textbf{alloc} members initialized. This ensures that the mp\_int will always represent the default state of zero regardless -of the original condition of the input. - -\textbf{Remark.} -This function introduces the idiosyncrasy that all iterative loops, commonly initiated with the ``for'' keyword, iterate incrementally -when the ``to'' keyword is placed between two expressions. For example, ``for $a$ from $b$ to $c$ do'' means that -a subsequent expression (or body of expressions) are to be evaluated upto $c - b$ times so long as $b \le c$. In each -iteration the variable $a$ is substituted for a new integer that lies inclusively between $b$ and $c$. If $b > c$ occured -the loop would not iterate. By contrast if the ``downto'' keyword were used in place of ``to'' the loop would iterate -decrementally. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_init.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* init a new mp_int */ -018 int mp_init (mp_int * a) -019 \{ -020 int i; -021 -022 /* allocate memory required and clear it */ -023 a->dp = OPT_CAST(mp_digit) XMALLOC (sizeof (mp_digit) * MP_PREC); -024 if (a->dp == NULL) \{ -025 return MP_MEM; -026 \} -027 -028 /* set the digits to zero */ -029 for (i = 0; i < MP_PREC; i++) \{ -030 a->dp[i] = 0; -031 \} -032 -033 /* set the used to zero, allocated digits to the default precision -034 * and sign to positive */ -035 a->used = 0; -036 a->alloc = MP_PREC; -037 a->sign = MP_ZPOS; -038 -039 return MP_OKAY; -040 \} -041 #endif -042 -\end{alltt} -\end{small} - -One immediate observation of this initializtion function is that it does not return a pointer to a mp\_int structure. It -is assumed that the caller has already allocated memory for the mp\_int structure, typically on the application stack. The -call to mp\_init() is used only to initialize the members of the structure to a known default state. - -Here we see (line 23) the memory allocation is performed first. This allows us to exit cleanly and quickly -if there is an error. If the allocation fails the routine will return \textbf{MP\_MEM} to the caller to indicate there -was a memory error. The function XMALLOC is what actually allocates the memory. Technically XMALLOC is not a function -but a macro defined in ``tommath.h``. By default, XMALLOC will evaluate to malloc() which is the C library's built--in -memory allocation routine. - -In order to assure the mp\_int is in a known state the digits must be set to zero. On most platforms this could have been -accomplished by using calloc() instead of malloc(). However, to correctly initialize a integer type to a given value in a -portable fashion you have to actually assign the value. The for loop (line 29) performs this required -operation. - -After the memory has been successfully initialized the remainder of the members are initialized -(lines 33 through 34) to their respective default states. At this point the algorithm has succeeded and -a success code is returned to the calling function. If this function returns \textbf{MP\_OKAY} it is safe to assume the -mp\_int structure has been properly initialized and is safe to use with other functions within the library. - -\subsection{Clearing an mp\_int} -When an mp\_int is no longer required by the application, the memory that has been allocated for its digits must be -returned to the application's memory pool with the mp\_clear algorithm. - -\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_clear}. \\ -\textbf{Input}. An mp\_int $a$ \\ -\textbf{Output}. The memory for $a$ shall be deallocated. \\ -\hline \\ -1. If $a$ has been previously freed then return(\textit{MP\_OKAY}). \\ -2. for $n$ from 0 to $a.used - 1$ do \\ -\hspace{3mm}2.1 $a_n \leftarrow 0$ \\ -3. Free the memory allocated for the digits of $a$. \\ -4. $a.used \leftarrow 0$ \\ -5. $a.alloc \leftarrow 0$ \\ -6. $a.sign \leftarrow MP\_ZPOS$ \\ -7. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_clear} -\end{figure} - -\textbf{Algorithm mp\_clear.} -This algorithm accomplishes two goals. First, it clears the digits and the other mp\_int members. This ensures that -if a developer accidentally re-uses a cleared structure it is less likely to cause problems. The second goal -is to free the allocated memory. - -The logic behind the algorithm is extended by marking cleared mp\_int structures so that subsequent calls to this -algorithm will not try to free the memory multiple times. Cleared mp\_ints are detectable by having a pre-defined invalid -digit pointer \textbf{dp} setting. - -Once an mp\_int has been cleared the mp\_int structure is no longer in a valid state for any other algorithm -with the exception of algorithms mp\_init, mp\_init\_copy, mp\_init\_size and mp\_clear. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_clear.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* clear one (frees) */ -018 void -019 mp_clear (mp_int * a) -020 \{ -021 int i; -022 -023 /* only do anything if a hasn't been freed previously */ -024 if (a->dp != NULL) \{ -025 /* first zero the digits */ -026 for (i = 0; i < a->used; i++) \{ -027 a->dp[i] = 0; -028 \} -029 -030 /* free ram */ -031 XFREE(a->dp); -032 -033 /* reset members to make debugging easier */ -034 a->dp = NULL; -035 a->alloc = a->used = 0; -036 a->sign = MP_ZPOS; -037 \} -038 \} -039 #endif -040 -\end{alltt} -\end{small} - -The algorithm only operates on the mp\_int if it hasn't been previously cleared. The if statement (line 24) -checks to see if the \textbf{dp} member is not \textbf{NULL}. If the mp\_int is a valid mp\_int then \textbf{dp} cannot be -\textbf{NULL} in which case the if statement will evaluate to true. - -The digits of the mp\_int are cleared by the for loop (line 26) which assigns a zero to every digit. Similar to mp\_init() -the digits are assigned zero instead of using block memory operations (such as memset()) since this is more portable. - -The digits are deallocated off the heap via the XFREE macro. Similar to XMALLOC the XFREE macro actually evaluates to -a standard C library function. In this case the free() function. Since free() only deallocates the memory the pointer -still has to be reset to \textbf{NULL} manually (line 34). - -Now that the digits have been cleared and deallocated the other members are set to their final values (lines 35 and 36). - -\section{Maintenance Algorithms} - -The previous sections describes how to initialize and clear an mp\_int structure. To further support operations -that are to be performed on mp\_int structures (such as addition and multiplication) the dependent algorithms must be -able to augment the precision of an mp\_int and -initialize mp\_ints with differing initial conditions. - -These algorithms complete the set of low level algorithms required to work with mp\_int structures in the higher level -algorithms such as addition, multiplication and modular exponentiation. - -\subsection{Augmenting an mp\_int's Precision} -When storing a value in an mp\_int structure, a sufficient number of digits must be available to accomodate the entire -result of an operation without loss of precision. Quite often the size of the array given by the \textbf{alloc} member -is large enough to simply increase the \textbf{used} digit count. However, when the size of the array is too small it -must be re-sized appropriately to accomodate the result. The mp\_grow algorithm will provide this functionality. - -\newpage\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_grow}. \\ -\textbf{Input}. An mp\_int $a$ and an integer $b$. \\ -\textbf{Output}. $a$ is expanded to accomodate $b$ digits. \\ -\hline \\ -1. if $a.alloc \ge b$ then return(\textit{MP\_OKAY}) \\ -2. $u \leftarrow b\mbox{ (mod }MP\_PREC\mbox{)}$ \\ -3. $v \leftarrow b + 2 \cdot MP\_PREC - u$ \\ -4. Re-allocate the array of digits $a$ to size $v$ \\ -5. If the allocation failed then return(\textit{MP\_MEM}). \\ -6. for n from a.alloc to $v - 1$ do \\ -\hspace{+3mm}6.1 $a_n \leftarrow 0$ \\ -7. $a.alloc \leftarrow v$ \\ -8. Return(\textit{MP\_OKAY}) \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_grow} -\end{figure} - -\textbf{Algorithm mp\_grow.} -It is ideal to prevent re-allocations from being performed if they are not required (step one). This is useful to -prevent mp\_ints from growing excessively in code that erroneously calls mp\_grow. - -The requested digit count is padded up to next multiple of \textbf{MP\_PREC} plus an additional \textbf{MP\_PREC} (steps two and three). -This helps prevent many trivial reallocations that would grow an mp\_int by trivially small values. - -It is assumed that the reallocation (step four) leaves the lower $a.alloc$ digits of the mp\_int intact. This is much -akin to how the \textit{realloc} function from the standard C library works. Since the newly allocated digits are -assumed to contain undefined values they are initially set to zero. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_grow.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* grow as required */ -018 int mp_grow (mp_int * a, int size) -019 \{ -020 int i; -021 mp_digit *tmp; -022 -023 /* if the alloc size is smaller alloc more ram */ -024 if (a->alloc < size) \{ -025 /* ensure there are always at least MP_PREC digits extra on top */ -026 size += (MP_PREC * 2) - (size % MP_PREC); -027 -028 /* reallocate the array a->dp -029 * -030 * We store the return in a temporary variable -031 * in case the operation failed we don't want -032 * to overwrite the dp member of a. -033 */ -034 tmp = OPT_CAST(mp_digit) XREALLOC (a->dp, sizeof (mp_digit) * size); -035 if (tmp == NULL) \{ -036 /* reallocation failed but "a" is still valid [can be freed] */ -037 return MP_MEM; -038 \} -039 -040 /* reallocation succeeded so set a->dp */ -041 a->dp = tmp; -042 -043 /* zero excess digits */ -044 i = a->alloc; -045 a->alloc = size; -046 for (; i < a->alloc; i++) \{ -047 a->dp[i] = 0; -048 \} -049 \} -050 return MP_OKAY; -051 \} -052 #endif -053 -\end{alltt} -\end{small} - -A quick optimization is to first determine if a memory re-allocation is required at all. The if statement (line 24) checks -if the \textbf{alloc} member of the mp\_int is smaller than the requested digit count. If the count is not larger than \textbf{alloc} -the function skips the re-allocation part thus saving time. - -When a re-allocation is performed it is turned into an optimal request to save time in the future. The requested digit count is -padded upwards to 2nd multiple of \textbf{MP\_PREC} larger than \textbf{alloc} (line 26). The XREALLOC function is used -to re-allocate the memory. As per the other functions XREALLOC is actually a macro which evaluates to realloc by default. The realloc -function leaves the base of the allocation intact which means the first \textbf{alloc} digits of the mp\_int are the same as before -the re-allocation. All that is left is to clear the newly allocated digits and return. - -Note that the re-allocation result is actually stored in a temporary pointer $tmp$. This is to allow this function to return -an error with a valid pointer. Earlier releases of the library stored the result of XREALLOC into the mp\_int $a$. That would -result in a memory leak if XREALLOC ever failed. - -\subsection{Initializing Variable Precision mp\_ints} -Occasionally the number of digits required will be known in advance of an initialization, based on, for example, the size -of input mp\_ints to a given algorithm. The purpose of algorithm mp\_init\_size is similar to mp\_init except that it -will allocate \textit{at least} a specified number of digits. - -\begin{figure}[here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_init\_size}. \\ -\textbf{Input}. An mp\_int $a$ and the requested number of digits $b$. \\ -\textbf{Output}. $a$ is initialized to hold at least $b$ digits. \\ -\hline \\ -1. $u \leftarrow b \mbox{ (mod }MP\_PREC\mbox{)}$ \\ -2. $v \leftarrow b + 2 \cdot MP\_PREC - u$ \\ -3. Allocate $v$ digits. \\ -4. for $n$ from $0$ to $v - 1$ do \\ -\hspace{3mm}4.1 $a_n \leftarrow 0$ \\ -5. $a.sign \leftarrow MP\_ZPOS$\\ -6. $a.used \leftarrow 0$\\ -7. $a.alloc \leftarrow v$\\ -8. Return(\textit{MP\_OKAY})\\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_init\_size} -\end{figure} - -\textbf{Algorithm mp\_init\_size.} -This algorithm will initialize an mp\_int structure $a$ like algorithm mp\_init with the exception that the number of -digits allocated can be controlled by the second input argument $b$. The input size is padded upwards so it is a -multiple of \textbf{MP\_PREC} plus an additional \textbf{MP\_PREC} digits. This padding is used to prevent trivial -allocations from becoming a bottleneck in the rest of the algorithms. - -Like algorithm mp\_init, the mp\_int structure is initialized to a default state representing the integer zero. This -particular algorithm is useful if it is known ahead of time the approximate size of the input. If the approximation is -correct no further memory re-allocations are required to work with the mp\_int. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_init\_size.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* init an mp_init for a given size */ -018 int mp_init_size (mp_int * a, int size) -019 \{ -020 int x; -021 -022 /* pad size so there are always extra digits */ -023 size += (MP_PREC * 2) - (size % MP_PREC); -024 -025 /* alloc mem */ -026 a->dp = OPT_CAST(mp_digit) XMALLOC (sizeof (mp_digit) * size); -027 if (a->dp == NULL) \{ -028 return MP_MEM; -029 \} -030 -031 /* set the members */ -032 a->used = 0; -033 a->alloc = size; -034 a->sign = MP_ZPOS; -035 -036 /* zero the digits */ -037 for (x = 0; x < size; x++) \{ -038 a->dp[x] = 0; -039 \} -040 -041 return MP_OKAY; -042 \} -043 #endif -044 -\end{alltt} -\end{small} - -The number of digits $b$ requested is padded (line 23) by first augmenting it to the next multiple of -\textbf{MP\_PREC} and then adding \textbf{MP\_PREC} to the result. If the memory can be successfully allocated the -mp\_int is placed in a default state representing the integer zero. Otherwise, the error code \textbf{MP\_MEM} will be -returned (line 28). - -The digits are allocated with the malloc() function (line 26) and set to zero afterwards (line 37). The -\textbf{used} count is set to zero, the \textbf{alloc} count set to the padded digit count and the \textbf{sign} flag set -to \textbf{MP\_ZPOS} to achieve a default valid mp\_int state (lines 32, 33 and 34). If the function -returns succesfully then it is correct to assume that the mp\_int structure is in a valid state for the remainder of the -functions to work with. - -\subsection{Multiple Integer Initializations and Clearings} -Occasionally a function will require a series of mp\_int data types to be made available simultaneously. -The purpose of algorithm mp\_init\_multi is to initialize a variable length array of mp\_int structures in a single -statement. It is essentially a shortcut to multiple initializations. - -\newpage\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_init\_multi}. \\ -\textbf{Input}. Variable length array $V_k$ of mp\_int variables of length $k$. \\ -\textbf{Output}. The array is initialized such that each mp\_int of $V_k$ is ready to use. \\ -\hline \\ -1. for $n$ from 0 to $k - 1$ do \\ -\hspace{+3mm}1.1. Initialize the mp\_int $V_n$ (\textit{mp\_init}) \\ -\hspace{+3mm}1.2. If initialization failed then do \\ -\hspace{+6mm}1.2.1. for $j$ from $0$ to $n$ do \\ -\hspace{+9mm}1.2.1.1. Free the mp\_int $V_j$ (\textit{mp\_clear}) \\ -\hspace{+6mm}1.2.2. Return(\textit{MP\_MEM}) \\ -2. Return(\textit{MP\_OKAY}) \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_init\_multi} -\end{figure} - -\textbf{Algorithm mp\_init\_multi.} -The algorithm will initialize the array of mp\_int variables one at a time. If a runtime error has been detected -(\textit{step 1.2}) all of the previously initialized variables are cleared. The goal is an ``all or nothing'' -initialization which allows for quick recovery from runtime errors. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_init\_multi.c -\vspace{-3mm} -\begin{alltt} -016 #include <stdarg.h> -017 -018 int mp_init_multi(mp_int *mp, ...) -019 \{ -020 mp_err res = MP_OKAY; /* Assume ok until proven otherwise */ -021 int n = 0; /* Number of ok inits */ -022 mp_int* cur_arg = mp; -023 va_list args; -024 -025 va_start(args, mp); /* init args to next argument from caller */ -026 while (cur_arg != NULL) \{ -027 if (mp_init(cur_arg) != MP_OKAY) \{ -028 /* Oops - error! Back-track and mp_clear what we already -029 succeeded in init-ing, then return error. -030 */ -031 va_list clean_args; -032 -033 /* end the current list */ -034 va_end(args); -035 -036 /* now start cleaning up */ -037 cur_arg = mp; -038 va_start(clean_args, mp); -039 while (n-- != 0) \{ -040 mp_clear(cur_arg); -041 cur_arg = va_arg(clean_args, mp_int*); -042 \} -043 va_end(clean_args); -044 res = MP_MEM; -045 break; -046 \} -047 n++; -048 cur_arg = va_arg(args, mp_int*); -049 \} -050 va_end(args); -051 return res; /* Assumed ok, if error flagged above. */ -052 \} -053 -054 #endif -055 -\end{alltt} -\end{small} - -This function intializes a variable length list of mp\_int structure pointers. However, instead of having the mp\_int -structures in an actual C array they are simply passed as arguments to the function. This function makes use of the -``...'' argument syntax of the C programming language. The list is terminated with a final \textbf{NULL} argument -appended on the right. - -The function uses the ``stdarg.h'' \textit{va} functions to step portably through the arguments to the function. A count -$n$ of succesfully initialized mp\_int structures is maintained (line 47) such that if a failure does occur, -the algorithm can backtrack and free the previously initialized structures (lines 27 to 46). - - -\subsection{Clamping Excess Digits} -When a function anticipates a result will be $n$ digits it is simpler to assume this is true within the body of -the function instead of checking during the computation. For example, a multiplication of a $i$ digit number by a -$j$ digit produces a result of at most $i + j$ digits. It is entirely possible that the result is $i + j - 1$ -though, with no final carry into the last position. However, suppose the destination had to be first expanded -(\textit{via mp\_grow}) to accomodate $i + j - 1$ digits than further expanded to accomodate the final carry. -That would be a considerable waste of time since heap operations are relatively slow. - -The ideal solution is to always assume the result is $i + j$ and fix up the \textbf{used} count after the function -terminates. This way a single heap operation (\textit{at most}) is required. However, if the result was not checked -there would be an excess high order zero digit. - -For example, suppose the product of two integers was $x_n = (0x_{n-1}x_{n-2}...x_0)_{\beta}$. The leading zero digit -will not contribute to the precision of the result. In fact, through subsequent operations more leading zero digits would -accumulate to the point the size of the integer would be prohibitive. As a result even though the precision is very -low the representation is excessively large. - -The mp\_clamp algorithm is designed to solve this very problem. It will trim high-order zeros by decrementing the -\textbf{used} count until a non-zero most significant digit is found. Also in this system, zero is considered to be a -positive number which means that if the \textbf{used} count is decremented to zero, the sign must be set to -\textbf{MP\_ZPOS}. - -\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_clamp}. \\ -\textbf{Input}. An mp\_int $a$ \\ -\textbf{Output}. Any excess leading zero digits of $a$ are removed \\ -\hline \\ -1. while $a.used > 0$ and $a_{a.used - 1} = 0$ do \\ -\hspace{+3mm}1.1 $a.used \leftarrow a.used - 1$ \\ -2. if $a.used = 0$ then do \\ -\hspace{+3mm}2.1 $a.sign \leftarrow MP\_ZPOS$ \\ -\hline \\ -\end{tabular} -\end{center} -\caption{Algorithm mp\_clamp} -\end{figure} - -\textbf{Algorithm mp\_clamp.} -As can be expected this algorithm is very simple. The loop on step one is expected to iterate only once or twice at -the most. For example, this will happen in cases where there is not a carry to fill the last position. Step two fixes the sign for -when all of the digits are zero to ensure that the mp\_int is valid at all times. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_clamp.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* trim unused digits -018 * -019 * This is used to ensure that leading zero digits are -020 * trimed and the leading "used" digit will be non-zero -021 * Typically very fast. Also fixes the sign if there -022 * are no more leading digits -023 */ -024 void -025 mp_clamp (mp_int * a) -026 \{ -027 /* decrease used while the most significant digit is -028 * zero. -029 */ -030 while ((a->used > 0) && (a->dp[a->used - 1] == 0)) \{ -031 --(a->used); -032 \} -033 -034 /* reset the sign flag if used == 0 */ -035 if (a->used == 0) \{ -036 a->sign = MP_ZPOS; -037 \} -038 \} -039 #endif -040 -\end{alltt} -\end{small} - -Note on line 27 how to test for the \textbf{used} count is made on the left of the \&\& operator. In the C programming -language the terms to \&\& are evaluated left to right with a boolean short-circuit if any condition fails. This is -important since if the \textbf{used} is zero the test on the right would fetch below the array. That is obviously -undesirable. The parenthesis on line 30 is used to make sure the \textbf{used} count is decremented and not -the pointer ``a''. - -\section*{Exercises} -\begin{tabular}{cl} -$\left [ 1 \right ]$ & Discuss the relevance of the \textbf{used} member of the mp\_int structure. \\ - & \\ -$\left [ 1 \right ]$ & Discuss the consequences of not using padding when performing allocations. \\ - & \\ -$\left [ 2 \right ]$ & Estimate an ideal value for \textbf{MP\_PREC} when performing 1024-bit RSA \\ - & encryption when $\beta = 2^{28}$. \\ - & \\ -$\left [ 1 \right ]$ & Discuss the relevance of the algorithm mp\_clamp. What does it prevent? \\ - & \\ -$\left [ 1 \right ]$ & Give an example of when the algorithm mp\_init\_copy might be useful. \\ - & \\ -\end{tabular} - - -%%% -% CHAPTER FOUR -%%% - -\chapter{Basic Operations} - -\section{Introduction} -In the previous chapter a series of low level algorithms were established that dealt with initializing and maintaining -mp\_int structures. This chapter will discuss another set of seemingly non-algebraic algorithms which will form the low -level basis of the entire library. While these algorithm are relatively trivial it is important to understand how they -work before proceeding since these algorithms will be used almost intrinsically in the following chapters. - -The algorithms in this chapter deal primarily with more ``programmer'' related tasks such as creating copies of -mp\_int structures, assigning small values to mp\_int structures and comparisons of the values mp\_int structures -represent. - -\section{Assigning Values to mp\_int Structures} -\subsection{Copying an mp\_int} -Assigning the value that a given mp\_int structure represents to another mp\_int structure shall be known as making -a copy for the purposes of this text. The copy of the mp\_int will be a separate entity that represents the same -value as the mp\_int it was copied from. The mp\_copy algorithm provides this functionality. - -\newpage\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_copy}. \\ -\textbf{Input}. An mp\_int $a$ and $b$. \\ -\textbf{Output}. Store a copy of $a$ in $b$. \\ -\hline \\ -1. If $b.alloc < a.used$ then grow $b$ to $a.used$ digits. (\textit{mp\_grow}) \\ -2. for $n$ from 0 to $a.used - 1$ do \\ -\hspace{3mm}2.1 $b_{n} \leftarrow a_{n}$ \\ -3. for $n$ from $a.used$ to $b.used - 1$ do \\ -\hspace{3mm}3.1 $b_{n} \leftarrow 0$ \\ -4. $b.used \leftarrow a.used$ \\ -5. $b.sign \leftarrow a.sign$ \\ -6. return(\textit{MP\_OKAY}) \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_copy} -\end{figure} - -\textbf{Algorithm mp\_copy.} -This algorithm copies the mp\_int $a$ such that upon succesful termination of the algorithm the mp\_int $b$ will -represent the same integer as the mp\_int $a$. The mp\_int $b$ shall be a complete and distinct copy of the -mp\_int $a$ meaing that the mp\_int $a$ can be modified and it shall not affect the value of the mp\_int $b$. - -If $b$ does not have enough room for the digits of $a$ it must first have its precision augmented via the mp\_grow -algorithm. The digits of $a$ are copied over the digits of $b$ and any excess digits of $b$ are set to zero (step two -and three). The \textbf{used} and \textbf{sign} members of $a$ are finally copied over the respective members of -$b$. - -\textbf{Remark.} This algorithm also introduces a new idiosyncrasy that will be used throughout the rest of the -text. The error return codes of other algorithms are not explicitly checked in the pseudo-code presented. For example, in -step one of the mp\_copy algorithm the return of mp\_grow is not explicitly checked to ensure it succeeded. Text space is -limited so it is assumed that if a algorithm fails it will clear all temporarily allocated mp\_ints and return -the error code itself. However, the C code presented will demonstrate all of the error handling logic required to -implement the pseudo-code. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_copy.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* copy, b = a */ -018 int -019 mp_copy (mp_int * a, mp_int * b) -020 \{ -021 int res, n; -022 -023 /* if dst == src do nothing */ -024 if (a == b) \{ -025 return MP_OKAY; -026 \} -027 -028 /* grow dest */ -029 if (b->alloc < a->used) \{ -030 if ((res = mp_grow (b, a->used)) != MP_OKAY) \{ -031 return res; -032 \} -033 \} -034 -035 /* zero b and copy the parameters over */ -036 \{ -037 mp_digit *tmpa, *tmpb; -038 -039 /* pointer aliases */ -040 -041 /* source */ -042 tmpa = a->dp; -043 -044 /* destination */ -045 tmpb = b->dp; -046 -047 /* copy all the digits */ -048 for (n = 0; n < a->used; n++) \{ -049 *tmpb++ = *tmpa++; -050 \} -051 -052 /* clear high digits */ -053 for (; n < b->used; n++) \{ -054 *tmpb++ = 0; -055 \} -056 \} -057 -058 /* copy used count and sign */ -059 b->used = a->used; -060 b->sign = a->sign; -061 return MP_OKAY; -062 \} -063 #endif -064 -\end{alltt} -\end{small} - -Occasionally a dependent algorithm may copy an mp\_int effectively into itself such as when the input and output -mp\_int structures passed to a function are one and the same. For this case it is optimal to return immediately without -copying digits (line 24). - -The mp\_int $b$ must have enough digits to accomodate the used digits of the mp\_int $a$. If $b.alloc$ is less than -$a.used$ the algorithm mp\_grow is used to augment the precision of $b$ (lines 29 to 33). In order to -simplify the inner loop that copies the digits from $a$ to $b$, two aliases $tmpa$ and $tmpb$ point directly at the digits -of the mp\_ints $a$ and $b$ respectively. These aliases (lines 42 and 45) allow the compiler to access the digits without first dereferencing the -mp\_int pointers and then subsequently the pointer to the digits. - -After the aliases are established the digits from $a$ are copied into $b$ (lines 48 to 50) and then the excess -digits of $b$ are set to zero (lines 53 to 55). Both ``for'' loops make use of the pointer aliases and in -fact the alias for $b$ is carried through into the second ``for'' loop to clear the excess digits. This optimization -allows the alias to stay in a machine register fairly easy between the two loops. - -\textbf{Remarks.} The use of pointer aliases is an implementation methodology first introduced in this function that will -be used considerably in other functions. Technically, a pointer alias is simply a short hand alias used to lower the -number of pointer dereferencing operations required to access data. For example, a for loop may resemble - -\begin{alltt} -for (x = 0; x < 100; x++) \{ - a->num[4]->dp[x] = 0; -\} -\end{alltt} - -This could be re-written using aliases as - -\begin{alltt} -mp_digit *tmpa; -a = a->num[4]->dp; -for (x = 0; x < 100; x++) \{ - *a++ = 0; -\} -\end{alltt} - -In this case an alias is used to access the -array of digits within an mp\_int structure directly. It may seem that a pointer alias is strictly not required -as a compiler may optimize out the redundant pointer operations. However, there are two dominant reasons to use aliases. - -The first reason is that most compilers will not effectively optimize pointer arithmetic. For example, some optimizations -may work for the Microsoft Visual C++ compiler (MSVC) and not for the GNU C Compiler (GCC). Also some optimizations may -work for GCC and not MSVC. As such it is ideal to find a common ground for as many compilers as possible. Pointer -aliases optimize the code considerably before the compiler even reads the source code which means the end compiled code -stands a better chance of being faster. - -The second reason is that pointer aliases often can make an algorithm simpler to read. Consider the first ``for'' -loop of the function mp\_copy() re-written to not use pointer aliases. - -\begin{alltt} - /* copy all the digits */ - for (n = 0; n < a->used; n++) \{ - b->dp[n] = a->dp[n]; - \} -\end{alltt} - -Whether this code is harder to read depends strongly on the individual. However, it is quantifiably slightly more -complicated as there are four variables within the statement instead of just two. - -\subsubsection{Nested Statements} -Another commonly used technique in the source routines is that certain sections of code are nested. This is used in -particular with the pointer aliases to highlight code phases. For example, a Comba multiplier (discussed in chapter six) -will typically have three different phases. First the temporaries are initialized, then the columns calculated and -finally the carries are propagated. In this example the middle column production phase will typically be nested as it -uses temporary variables and aliases the most. - -The nesting also simplies the source code as variables that are nested are only valid for their scope. As a result -the various temporary variables required do not propagate into other sections of code. - - -\subsection{Creating a Clone} -Another common operation is to make a local temporary copy of an mp\_int argument. To initialize an mp\_int -and then copy another existing mp\_int into the newly intialized mp\_int will be known as creating a clone. This is -useful within functions that need to modify an argument but do not wish to actually modify the original copy. The -mp\_init\_copy algorithm has been designed to help perform this task. - -\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_init\_copy}. \\ -\textbf{Input}. An mp\_int $a$ and $b$\\ -\textbf{Output}. $a$ is initialized to be a copy of $b$. \\ -\hline \\ -1. Init $a$. (\textit{mp\_init}) \\ -2. Copy $b$ to $a$. (\textit{mp\_copy}) \\ -3. Return the status of the copy operation. \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_init\_copy} -\end{figure} - -\textbf{Algorithm mp\_init\_copy.} -This algorithm will initialize an mp\_int variable and copy another previously initialized mp\_int variable into it. As -such this algorithm will perform two operations in one step. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_init\_copy.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* creates "a" then copies b into it */ -018 int mp_init_copy (mp_int * a, mp_int * b) -019 \{ -020 int res; -021 -022 if ((res = mp_init_size (a, b->used)) != MP_OKAY) \{ -023 return res; -024 \} -025 return mp_copy (b, a); -026 \} -027 #endif -028 -\end{alltt} -\end{small} - -This will initialize \textbf{a} and make it a verbatim copy of the contents of \textbf{b}. Note that -\textbf{a} will have its own memory allocated which means that \textbf{b} may be cleared after the call -and \textbf{a} will be left intact. - -\section{Zeroing an Integer} -Reseting an mp\_int to the default state is a common step in many algorithms. The mp\_zero algorithm will be the algorithm used to -perform this task. - -\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_zero}. \\ -\textbf{Input}. An mp\_int $a$ \\ -\textbf{Output}. Zero the contents of $a$ \\ -\hline \\ -1. $a.used \leftarrow 0$ \\ -2. $a.sign \leftarrow$ MP\_ZPOS \\ -3. for $n$ from 0 to $a.alloc - 1$ do \\ -\hspace{3mm}3.1 $a_n \leftarrow 0$ \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_zero} -\end{figure} - -\textbf{Algorithm mp\_zero.} -This algorithm simply resets a mp\_int to the default state. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_zero.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* set to zero */ -018 void mp_zero (mp_int * a) -019 \{ -020 int n; -021 mp_digit *tmp; -022 -023 a->sign = MP_ZPOS; -024 a->used = 0; -025 -026 tmp = a->dp; -027 for (n = 0; n < a->alloc; n++) \{ -028 *tmp++ = 0; -029 \} -030 \} -031 #endif -032 -\end{alltt} -\end{small} - -After the function is completed, all of the digits are zeroed, the \textbf{used} count is zeroed and the -\textbf{sign} variable is set to \textbf{MP\_ZPOS}. - -\section{Sign Manipulation} -\subsection{Absolute Value} -With the mp\_int representation of an integer, calculating the absolute value is trivial. The mp\_abs algorithm will compute -the absolute value of an mp\_int. - -\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_abs}. \\ -\textbf{Input}. An mp\_int $a$ \\ -\textbf{Output}. Computes $b = \vert a \vert$ \\ -\hline \\ -1. Copy $a$ to $b$. (\textit{mp\_copy}) \\ -2. If the copy failed return(\textit{MP\_MEM}). \\ -3. $b.sign \leftarrow MP\_ZPOS$ \\ -4. Return(\textit{MP\_OKAY}) \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_abs} -\end{figure} - -\textbf{Algorithm mp\_abs.} -This algorithm computes the absolute of an mp\_int input. First it copies $a$ over $b$. This is an example of an -algorithm where the check in mp\_copy that determines if the source and destination are equal proves useful. This allows, -for instance, the developer to pass the same mp\_int as the source and destination to this function without addition -logic to handle it. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_abs.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* b = |a| -018 * -019 * Simple function copies the input and fixes the sign to positive -020 */ -021 int -022 mp_abs (mp_int * a, mp_int * b) -023 \{ -024 int res; -025 -026 /* copy a to b */ -027 if (a != b) \{ -028 if ((res = mp_copy (a, b)) != MP_OKAY) \{ -029 return res; -030 \} -031 \} -032 -033 /* force the sign of b to positive */ -034 b->sign = MP_ZPOS; -035 -036 return MP_OKAY; -037 \} -038 #endif -039 -\end{alltt} -\end{small} - -This fairly trivial algorithm first eliminates non--required duplications (line 27) and then sets the -\textbf{sign} flag to \textbf{MP\_ZPOS}. - -\subsection{Integer Negation} -With the mp\_int representation of an integer, calculating the negation is also trivial. The mp\_neg algorithm will compute -the negative of an mp\_int input. - -\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_neg}. \\ -\textbf{Input}. An mp\_int $a$ \\ -\textbf{Output}. Computes $b = -a$ \\ -\hline \\ -1. Copy $a$ to $b$. (\textit{mp\_copy}) \\ -2. If the copy failed return(\textit{MP\_MEM}). \\ -3. If $a.used = 0$ then return(\textit{MP\_OKAY}). \\ -4. If $a.sign = MP\_ZPOS$ then do \\ -\hspace{3mm}4.1 $b.sign = MP\_NEG$. \\ -5. else do \\ -\hspace{3mm}5.1 $b.sign = MP\_ZPOS$. \\ -6. Return(\textit{MP\_OKAY}) \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_neg} -\end{figure} - -\textbf{Algorithm mp\_neg.} -This algorithm computes the negation of an input. First it copies $a$ over $b$. If $a$ has no used digits then -the algorithm returns immediately. Otherwise it flips the sign flag and stores the result in $b$. Note that if -$a$ had no digits then it must be positive by definition. Had step three been omitted then the algorithm would return -zero as negative. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_neg.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* b = -a */ -018 int mp_neg (mp_int * a, mp_int * b) -019 \{ -020 int res; -021 if (a != b) \{ -022 if ((res = mp_copy (a, b)) != MP_OKAY) \{ -023 return res; -024 \} -025 \} -026 -027 if (mp_iszero(b) != MP_YES) \{ -028 b->sign = (a->sign == MP_ZPOS) ? MP_NEG : MP_ZPOS; -029 \} else \{ -030 b->sign = MP_ZPOS; -031 \} -032 -033 return MP_OKAY; -034 \} -035 #endif -036 -\end{alltt} -\end{small} - -Like mp\_abs() this function avoids non--required duplications (line 21) and then sets the sign. We -have to make sure that only non--zero values get a \textbf{sign} of \textbf{MP\_NEG}. If the mp\_int is zero -than the \textbf{sign} is hard--coded to \textbf{MP\_ZPOS}. - -\section{Small Constants} -\subsection{Setting Small Constants} -Often a mp\_int must be set to a relatively small value such as $1$ or $2$. For these cases the mp\_set algorithm is useful. - -\newpage\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_set}. \\ -\textbf{Input}. An mp\_int $a$ and a digit $b$ \\ -\textbf{Output}. Make $a$ equivalent to $b$ \\ -\hline \\ -1. Zero $a$ (\textit{mp\_zero}). \\ -2. $a_0 \leftarrow b \mbox{ (mod }\beta\mbox{)}$ \\ -3. $a.used \leftarrow \left \lbrace \begin{array}{ll} - 1 & \mbox{if }a_0 > 0 \\ - 0 & \mbox{if }a_0 = 0 - \end{array} \right .$ \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_set} -\end{figure} - -\textbf{Algorithm mp\_set.} -This algorithm sets a mp\_int to a small single digit value. Step number 1 ensures that the integer is reset to the default state. The -single digit is set (\textit{modulo $\beta$}) and the \textbf{used} count is adjusted accordingly. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_set.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* set to a digit */ -018 void mp_set (mp_int * a, mp_digit b) -019 \{ -020 mp_zero (a); -021 a->dp[0] = b & MP_MASK; -022 a->used = (a->dp[0] != 0) ? 1 : 0; -023 \} -024 #endif -025 -\end{alltt} -\end{small} - -First we zero (line 20) the mp\_int to make sure that the other members are initialized for a -small positive constant. mp\_zero() ensures that the \textbf{sign} is positive and the \textbf{used} count -is zero. Next we set the digit and reduce it modulo $\beta$ (line 21). After this step we have to -check if the resulting digit is zero or not. If it is not then we set the \textbf{used} count to one, otherwise -to zero. - -We can quickly reduce modulo $\beta$ since it is of the form $2^k$ and a quick binary AND operation with -$2^k - 1$ will perform the same operation. - -One important limitation of this function is that it will only set one digit. The size of a digit is not fixed, meaning source that uses -this function should take that into account. Only trivially small constants can be set using this function. - -\subsection{Setting Large Constants} -To overcome the limitations of the mp\_set algorithm the mp\_set\_int algorithm is ideal. It accepts a ``long'' -data type as input and will always treat it as a 32-bit integer. - -\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_set\_int}. \\ -\textbf{Input}. An mp\_int $a$ and a ``long'' integer $b$ \\ -\textbf{Output}. Make $a$ equivalent to $b$ \\ -\hline \\ -1. Zero $a$ (\textit{mp\_zero}) \\ -2. for $n$ from 0 to 7 do \\ -\hspace{3mm}2.1 $a \leftarrow a \cdot 16$ (\textit{mp\_mul2d}) \\ -\hspace{3mm}2.2 $u \leftarrow \lfloor b / 2^{4(7 - n)} \rfloor \mbox{ (mod }16\mbox{)}$\\ -\hspace{3mm}2.3 $a_0 \leftarrow a_0 + u$ \\ -\hspace{3mm}2.4 $a.used \leftarrow a.used + 1$ \\ -3. Clamp excess used digits (\textit{mp\_clamp}) \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_set\_int} -\end{figure} - -\textbf{Algorithm mp\_set\_int.} -The algorithm performs eight iterations of a simple loop where in each iteration four bits from the source are added to the -mp\_int. Step 2.1 will multiply the current result by sixteen making room for four more bits in the less significant positions. In step 2.2 the -next four bits from the source are extracted and are added to the mp\_int. The \textbf{used} digit count is -incremented to reflect the addition. The \textbf{used} digit counter is incremented since if any of the leading digits were zero the mp\_int would have -zero digits used and the newly added four bits would be ignored. - -Excess zero digits are trimmed in steps 2.1 and 3 by using higher level algorithms mp\_mul2d and mp\_clamp. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_set\_int.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* set a 32-bit const */ -018 int mp_set_int (mp_int * a, unsigned long b) -019 \{ -020 int x, res; -021 -022 mp_zero (a); -023 -024 /* set four bits at a time */ -025 for (x = 0; x < 8; x++) \{ -026 /* shift the number up four bits */ -027 if ((res = mp_mul_2d (a, 4, a)) != MP_OKAY) \{ -028 return res; -029 \} -030 -031 /* OR in the top four bits of the source */ -032 a->dp[0] |= (b >> 28) & 15; -033 -034 /* shift the source up to the next four bits */ -035 b <<= 4; -036 -037 /* ensure that digits are not clamped off */ -038 a->used += 1; -039 \} -040 mp_clamp (a); -041 return MP_OKAY; -042 \} -043 #endif -044 -\end{alltt} -\end{small} - -This function sets four bits of the number at a time to handle all practical \textbf{DIGIT\_BIT} sizes. The weird -addition on line 38 ensures that the newly added in bits are added to the number of digits. While it may not -seem obvious as to why the digit counter does not grow exceedingly large it is because of the shift on line 27 -as well as the call to mp\_clamp() on line 40. Both functions will clamp excess leading digits which keeps -the number of used digits low. - -\section{Comparisons} -\subsection{Unsigned Comparisions} -Comparing a multiple precision integer is performed with the exact same algorithm used to compare two decimal numbers. For example, -to compare $1,234$ to $1,264$ the digits are extracted by their positions. That is we compare $1 \cdot 10^3 + 2 \cdot 10^2 + 3 \cdot 10^1 + 4 \cdot 10^0$ -to $1 \cdot 10^3 + 2 \cdot 10^2 + 6 \cdot 10^1 + 4 \cdot 10^0$ by comparing single digits at a time starting with the highest magnitude -positions. If any leading digit of one integer is greater than a digit in the same position of another integer then obviously it must be greater. - -The first comparision routine that will be developed is the unsigned magnitude compare which will perform a comparison based on the digits of two -mp\_int variables alone. It will ignore the sign of the two inputs. Such a function is useful when an absolute comparison is required or if the -signs are known to agree in advance. - -To facilitate working with the results of the comparison functions three constants are required. - -\begin{figure}[here] -\begin{center} -\begin{tabular}{|r|l|} -\hline \textbf{Constant} & \textbf{Meaning} \\ -\hline \textbf{MP\_GT} & Greater Than \\ -\hline \textbf{MP\_EQ} & Equal To \\ -\hline \textbf{MP\_LT} & Less Than \\ -\hline -\end{tabular} -\end{center} -\caption{Comparison Return Codes} -\end{figure} - -\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_cmp\_mag}. \\ -\textbf{Input}. Two mp\_ints $a$ and $b$. \\ -\textbf{Output}. Unsigned comparison results ($a$ to the left of $b$). \\ -\hline \\ -1. If $a.used > b.used$ then return(\textit{MP\_GT}) \\ -2. If $a.used < b.used$ then return(\textit{MP\_LT}) \\ -3. for n from $a.used - 1$ to 0 do \\ -\hspace{+3mm}3.1 if $a_n > b_n$ then return(\textit{MP\_GT}) \\ -\hspace{+3mm}3.2 if $a_n < b_n$ then return(\textit{MP\_LT}) \\ -4. Return(\textit{MP\_EQ}) \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_cmp\_mag} -\end{figure} - -\textbf{Algorithm mp\_cmp\_mag.} -By saying ``$a$ to the left of $b$'' it is meant that the comparison is with respect to $a$, that is if $a$ is greater than $b$ it will return -\textbf{MP\_GT} and similar with respect to when $a = b$ and $a < b$. The first two steps compare the number of digits used in both $a$ and $b$. -Obviously if the digit counts differ there would be an imaginary zero digit in the smaller number where the leading digit of the larger number is. -If both have the same number of digits than the actual digits themselves must be compared starting at the leading digit. - -By step three both inputs must have the same number of digits so its safe to start from either $a.used - 1$ or $b.used - 1$ and count down to -the zero'th digit. If after all of the digits have been compared, no difference is found, the algorithm returns \textbf{MP\_EQ}. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_cmp\_mag.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* compare maginitude of two ints (unsigned) */ -018 int mp_cmp_mag (mp_int * a, mp_int * b) -019 \{ -020 int n; -021 mp_digit *tmpa, *tmpb; -022 -023 /* compare based on # of non-zero digits */ -024 if (a->used > b->used) \{ -025 return MP_GT; -026 \} -027 -028 if (a->used < b->used) \{ -029 return MP_LT; -030 \} -031 -032 /* alias for a */ -033 tmpa = a->dp + (a->used - 1); -034 -035 /* alias for b */ -036 tmpb = b->dp + (a->used - 1); -037 -038 /* compare based on digits */ -039 for (n = 0; n < a->used; ++n, --tmpa, --tmpb) \{ -040 if (*tmpa > *tmpb) \{ -041 return MP_GT; -042 \} -043 -044 if (*tmpa < *tmpb) \{ -045 return MP_LT; -046 \} -047 \} -048 return MP_EQ; -049 \} -050 #endif -051 -\end{alltt} -\end{small} - -The two if statements (lines 24 and 28) compare the number of digits in the two inputs. These two are -performed before all of the digits are compared since it is a very cheap test to perform and can potentially save -considerable time. The implementation given is also not valid without those two statements. $b.alloc$ may be -smaller than $a.used$, meaning that undefined values will be read from $b$ past the end of the array of digits. - - - -\subsection{Signed Comparisons} -Comparing with sign considerations is also fairly critical in several routines (\textit{division for example}). Based on an unsigned magnitude -comparison a trivial signed comparison algorithm can be written. - -\begin{figure}[here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_cmp}. \\ -\textbf{Input}. Two mp\_ints $a$ and $b$ \\ -\textbf{Output}. Signed Comparison Results ($a$ to the left of $b$) \\ -\hline \\ -1. if $a.sign = MP\_NEG$ and $b.sign = MP\_ZPOS$ then return(\textit{MP\_LT}) \\ -2. if $a.sign = MP\_ZPOS$ and $b.sign = MP\_NEG$ then return(\textit{MP\_GT}) \\ -3. if $a.sign = MP\_NEG$ then \\ -\hspace{+3mm}3.1 Return the unsigned comparison of $b$ and $a$ (\textit{mp\_cmp\_mag}) \\ -4 Otherwise \\ -\hspace{+3mm}4.1 Return the unsigned comparison of $a$ and $b$ \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_cmp} -\end{figure} - -\textbf{Algorithm mp\_cmp.} -The first two steps compare the signs of the two inputs. If the signs do not agree then it can return right away with the appropriate -comparison code. When the signs are equal the digits of the inputs must be compared to determine the correct result. In step -three the unsigned comparision flips the order of the arguments since they are both negative. For instance, if $-a > -b$ then -$\vert a \vert < \vert b \vert$. Step number four will compare the two when they are both positive. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_cmp.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* compare two ints (signed)*/ -018 int -019 mp_cmp (mp_int * a, mp_int * b) -020 \{ -021 /* compare based on sign */ -022 if (a->sign != b->sign) \{ -023 if (a->sign == MP_NEG) \{ -024 return MP_LT; -025 \} else \{ -026 return MP_GT; -027 \} -028 \} -029 -030 /* compare digits */ -031 if (a->sign == MP_NEG) \{ -032 /* if negative compare opposite direction */ -033 return mp_cmp_mag(b, a); -034 \} else \{ -035 return mp_cmp_mag(a, b); -036 \} -037 \} -038 #endif -039 -\end{alltt} -\end{small} - -The two if statements (lines 22 and 23) perform the initial sign comparison. If the signs are not the equal then which ever -has the positive sign is larger. The inputs are compared (line 31) based on magnitudes. If the signs were both -negative then the unsigned comparison is performed in the opposite direction (line 33). Otherwise, the signs are assumed to -be both positive and a forward direction unsigned comparison is performed. - -\section*{Exercises} -\begin{tabular}{cl} -$\left [ 2 \right ]$ & Modify algorithm mp\_set\_int to accept as input a variable length array of bits. \\ - & \\ -$\left [ 3 \right ]$ & Give the probability that algorithm mp\_cmp\_mag will have to compare $k$ digits \\ - & of two random digits (of equal magnitude) before a difference is found. \\ - & \\ -$\left [ 1 \right ]$ & Suggest a simple method to speed up the implementation of mp\_cmp\_mag based \\ - & on the observations made in the previous problem. \\ - & -\end{tabular} - -\chapter{Basic Arithmetic} -\section{Introduction} -At this point algorithms for initialization, clearing, zeroing, copying, comparing and setting small constants have been -established. The next logical set of algorithms to develop are addition, subtraction and digit shifting algorithms. These -algorithms make use of the lower level algorithms and are the cruicial building block for the multiplication algorithms. It is very important -that these algorithms are highly optimized. On their own they are simple $O(n)$ algorithms but they can be called from higher level algorithms -which easily places them at $O(n^2)$ or even $O(n^3)$ work levels. - -All of the algorithms within this chapter make use of the logical bit shift operations denoted by $<<$ and $>>$ for left and right -logical shifts respectively. A logical shift is analogous to sliding the decimal point of radix-10 representations. For example, the real -number $0.9345$ is equivalent to $93.45\%$ which is found by sliding the the decimal two places to the right (\textit{multiplying by $\beta^2 = 10^2$}). -Algebraically a binary logical shift is equivalent to a division or multiplication by a power of two. -For example, $a << k = a \cdot 2^k$ while $a >> k = \lfloor a/2^k \rfloor$. - -One significant difference between a logical shift and the way decimals are shifted is that digits below the zero'th position are removed -from the number. For example, consider $1101_2 >> 1$ using decimal notation this would produce $110.1_2$. However, with a logical shift the -result is $110_2$. - -\section{Addition and Subtraction} -In common twos complement fixed precision arithmetic negative numbers are easily represented by subtraction from the modulus. For example, with 32-bit integers -$a - b\mbox{ (mod }2^{32}\mbox{)}$ is the same as $a + (2^{32} - b) \mbox{ (mod }2^{32}\mbox{)}$ since $2^{32} \equiv 0 \mbox{ (mod }2^{32}\mbox{)}$. -As a result subtraction can be performed with a trivial series of logical operations and an addition. - -However, in multiple precision arithmetic negative numbers are not represented in the same way. Instead a sign flag is used to keep track of the -sign of the integer. As a result signed addition and subtraction are actually implemented as conditional usage of lower level addition or -subtraction algorithms with the sign fixed up appropriately. - -The lower level algorithms will add or subtract integers without regard to the sign flag. That is they will add or subtract the magnitude of -the integers respectively. - -\subsection{Low Level Addition} -An unsigned addition of multiple precision integers is performed with the same long-hand algorithm used to add decimal numbers. That is to add the -trailing digits first and propagate the resulting carry upwards. Since this is a lower level algorithm the name will have a ``s\_'' prefix. -Historically that convention stems from the MPI library where ``s\_'' stood for static functions that were hidden from the developer entirely. - -\newpage -\begin{figure}[!here] -\begin{center} -\begin{small} -\begin{tabular}{l} -\hline Algorithm \textbf{s\_mp\_add}. \\ -\textbf{Input}. Two mp\_ints $a$ and $b$ \\ -\textbf{Output}. The unsigned addition $c = \vert a \vert + \vert b \vert$. \\ -\hline \\ -1. if $a.used > b.used$ then \\ -\hspace{+3mm}1.1 $min \leftarrow b.used$ \\ -\hspace{+3mm}1.2 $max \leftarrow a.used$ \\ -\hspace{+3mm}1.3 $x \leftarrow a$ \\ -2. else \\ -\hspace{+3mm}2.1 $min \leftarrow a.used$ \\ -\hspace{+3mm}2.2 $max \leftarrow b.used$ \\ -\hspace{+3mm}2.3 $x \leftarrow b$ \\ -3. If $c.alloc < max + 1$ then grow $c$ to hold at least $max + 1$ digits (\textit{mp\_grow}) \\ -4. $oldused \leftarrow c.used$ \\ -5. $c.used \leftarrow max + 1$ \\ -6. $u \leftarrow 0$ \\ -7. for $n$ from $0$ to $min - 1$ do \\ -\hspace{+3mm}7.1 $c_n \leftarrow a_n + b_n + u$ \\ -\hspace{+3mm}7.2 $u \leftarrow c_n >> lg(\beta)$ \\ -\hspace{+3mm}7.3 $c_n \leftarrow c_n \mbox{ (mod }\beta\mbox{)}$ \\ -8. if $min \ne max$ then do \\ -\hspace{+3mm}8.1 for $n$ from $min$ to $max - 1$ do \\ -\hspace{+6mm}8.1.1 $c_n \leftarrow x_n + u$ \\ -\hspace{+6mm}8.1.2 $u \leftarrow c_n >> lg(\beta)$ \\ -\hspace{+6mm}8.1.3 $c_n \leftarrow c_n \mbox{ (mod }\beta\mbox{)}$ \\ -9. $c_{max} \leftarrow u$ \\ -10. if $olduse > max$ then \\ -\hspace{+3mm}10.1 for $n$ from $max + 1$ to $oldused - 1$ do \\ -\hspace{+6mm}10.1.1 $c_n \leftarrow 0$ \\ -11. Clamp excess digits in $c$. (\textit{mp\_clamp}) \\ -12. Return(\textit{MP\_OKAY}) \\ -\hline -\end{tabular} -\end{small} -\end{center} -\caption{Algorithm s\_mp\_add} -\end{figure} - -\textbf{Algorithm s\_mp\_add.} -This algorithm is loosely based on algorithm 14.7 of HAC \cite[pp. 594]{HAC} but has been extended to allow the inputs to have different magnitudes. -Coincidentally the description of algorithm A in Knuth \cite[pp. 266]{TAOCPV2} shares the same deficiency as the algorithm from \cite{HAC}. Even the -MIX pseudo machine code presented by Knuth \cite[pp. 266-267]{TAOCPV2} is incapable of handling inputs which are of different magnitudes. - -The first thing that has to be accomplished is to sort out which of the two inputs is the largest. The addition logic -will simply add all of the smallest input to the largest input and store that first part of the result in the -destination. Then it will apply a simpler addition loop to excess digits of the larger input. - -The first two steps will handle sorting the inputs such that $min$ and $max$ hold the digit counts of the two -inputs. The variable $x$ will be an mp\_int alias for the largest input or the second input $b$ if they have the -same number of digits. After the inputs are sorted the destination $c$ is grown as required to accomodate the sum -of the two inputs. The original \textbf{used} count of $c$ is copied and set to the new used count. - -At this point the first addition loop will go through as many digit positions that both inputs have. The carry -variable $\mu$ is set to zero outside the loop. Inside the loop an ``addition'' step requires three statements to produce -one digit of the summand. First -two digits from $a$ and $b$ are added together along with the carry $\mu$. The carry of this step is extracted and stored -in $\mu$ and finally the digit of the result $c_n$ is truncated within the range $0 \le c_n < \beta$. - -Now all of the digit positions that both inputs have in common have been exhausted. If $min \ne max$ then $x$ is an alias -for one of the inputs that has more digits. A simplified addition loop is then used to essentially copy the remaining digits -and the carry to the destination. - -The final carry is stored in $c_{max}$ and digits above $max$ upto $oldused$ are zeroed which completes the addition. - - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_s\_mp\_add.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* low level addition, based on HAC pp.594, Algorithm 14.7 */ -018 int -019 s_mp_add (mp_int * a, mp_int * b, mp_int * c) -020 \{ -021 mp_int *x; -022 int olduse, res, min, max; -023 -024 /* find sizes, we let |a| <= |b| which means we have to sort -025 * them. "x" will point to the input with the most digits -026 */ -027 if (a->used > b->used) \{ -028 min = b->used; -029 max = a->used; -030 x = a; -031 \} else \{ -032 min = a->used; -033 max = b->used; -034 x = b; -035 \} -036 -037 /* init result */ -038 if (c->alloc < (max + 1)) \{ -039 if ((res = mp_grow (c, max + 1)) != MP_OKAY) \{ -040 return res; -041 \} -042 \} -043 -044 /* get old used digit count and set new one */ -045 olduse = c->used; -046 c->used = max + 1; -047 -048 \{ -049 mp_digit u, *tmpa, *tmpb, *tmpc; -050 int i; -051 -052 /* alias for digit pointers */ -053 -054 /* first input */ -055 tmpa = a->dp; -056 -057 /* second input */ -058 tmpb = b->dp; -059 -060 /* destination */ -061 tmpc = c->dp; -062 -063 /* zero the carry */ -064 u = 0; -065 for (i = 0; i < min; i++) \{ -066 /* Compute the sum at one digit, T[i] = A[i] + B[i] + U */ -067 *tmpc = *tmpa++ + *tmpb++ + u; -068 -069 /* U = carry bit of T[i] */ -070 u = *tmpc >> ((mp_digit)DIGIT_BIT); -071 -072 /* take away carry bit from T[i] */ -073 *tmpc++ &= MP_MASK; -074 \} -075 -076 /* now copy higher words if any, that is in A+B -077 * if A or B has more digits add those in -078 */ -079 if (min != max) \{ -080 for (; i < max; i++) \{ -081 /* T[i] = X[i] + U */ -082 *tmpc = x->dp[i] + u; -083 -084 /* U = carry bit of T[i] */ -085 u = *tmpc >> ((mp_digit)DIGIT_BIT); -086 -087 /* take away carry bit from T[i] */ -088 *tmpc++ &= MP_MASK; -089 \} -090 \} -091 -092 /* add carry */ -093 *tmpc++ = u; -094 -095 /* clear digits above oldused */ -096 for (i = c->used; i < olduse; i++) \{ -097 *tmpc++ = 0; -098 \} -099 \} -100 -101 mp_clamp (c); -102 return MP_OKAY; -103 \} -104 #endif -105 -\end{alltt} -\end{small} - -We first sort (lines 27 to 35) the inputs based on magnitude and determine the $min$ and $max$ variables. -Note that $x$ is a pointer to an mp\_int assigned to the largest input, in effect it is a local alias. Next we -grow the destination (37 to 42) ensure that it can accomodate the result of the addition. - -Similar to the implementation of mp\_copy this function uses the braced code and local aliases coding style. The three aliases that are on -lines 55, 58 and 61 represent the two inputs and destination variables respectively. These aliases are used to ensure the -compiler does not have to dereference $a$, $b$ or $c$ (respectively) to access the digits of the respective mp\_int. - -The initial carry $u$ will be cleared (line 64), note that $u$ is of type mp\_digit which ensures type -compatibility within the implementation. The initial addition (line 65 to 74) adds digits from -both inputs until the smallest input runs out of digits. Similarly the conditional addition loop -(line 80 to 90) adds the remaining digits from the larger of the two inputs. The addition is finished -with the final carry being stored in $tmpc$ (line 93). Note the ``++'' operator within the same expression. -After line 93, $tmpc$ will point to the $c.used$'th digit of the mp\_int $c$. This is useful -for the next loop (line 96 to 99) which set any old upper digits to zero. - -\subsection{Low Level Subtraction} -The low level unsigned subtraction algorithm is very similar to the low level unsigned addition algorithm. The principle difference is that the -unsigned subtraction algorithm requires the result to be positive. That is when computing $a - b$ the condition $\vert a \vert \ge \vert b\vert$ must -be met for this algorithm to function properly. Keep in mind this low level algorithm is not meant to be used in higher level algorithms directly. -This algorithm as will be shown can be used to create functional signed addition and subtraction algorithms. - - -For this algorithm a new variable is required to make the description simpler. Recall from section 1.3.1 that a mp\_digit must be able to represent -the range $0 \le x < 2\beta$ for the algorithms to work correctly. However, it is allowable that a mp\_digit represent a larger range of values. For -this algorithm we will assume that the variable $\gamma$ represents the number of bits available in a -mp\_digit (\textit{this implies $2^{\gamma} > \beta$}). - -For example, the default for LibTomMath is to use a ``unsigned long'' for the mp\_digit ``type'' while $\beta = 2^{28}$. In ISO C an ``unsigned long'' -data type must be able to represent $0 \le x < 2^{32}$ meaning that in this case $\gamma \ge 32$. - -\newpage\begin{figure}[!here] -\begin{center} -\begin{small} -\begin{tabular}{l} -\hline Algorithm \textbf{s\_mp\_sub}. \\ -\textbf{Input}. Two mp\_ints $a$ and $b$ ($\vert a \vert \ge \vert b \vert$) \\ -\textbf{Output}. The unsigned subtraction $c = \vert a \vert - \vert b \vert$. \\ -\hline \\ -1. $min \leftarrow b.used$ \\ -2. $max \leftarrow a.used$ \\ -3. If $c.alloc < max$ then grow $c$ to hold at least $max$ digits. (\textit{mp\_grow}) \\ -4. $oldused \leftarrow c.used$ \\ -5. $c.used \leftarrow max$ \\ -6. $u \leftarrow 0$ \\ -7. for $n$ from $0$ to $min - 1$ do \\ -\hspace{3mm}7.1 $c_n \leftarrow a_n - b_n - u$ \\ -\hspace{3mm}7.2 $u \leftarrow c_n >> (\gamma - 1)$ \\ -\hspace{3mm}7.3 $c_n \leftarrow c_n \mbox{ (mod }\beta\mbox{)}$ \\ -8. if $min < max$ then do \\ -\hspace{3mm}8.1 for $n$ from $min$ to $max - 1$ do \\ -\hspace{6mm}8.1.1 $c_n \leftarrow a_n - u$ \\ -\hspace{6mm}8.1.2 $u \leftarrow c_n >> (\gamma - 1)$ \\ -\hspace{6mm}8.1.3 $c_n \leftarrow c_n \mbox{ (mod }\beta\mbox{)}$ \\ -9. if $oldused > max$ then do \\ -\hspace{3mm}9.1 for $n$ from $max$ to $oldused - 1$ do \\ -\hspace{6mm}9.1.1 $c_n \leftarrow 0$ \\ -10. Clamp excess digits of $c$. (\textit{mp\_clamp}). \\ -11. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{small} -\end{center} -\caption{Algorithm s\_mp\_sub} -\end{figure} - -\textbf{Algorithm s\_mp\_sub.} -This algorithm performs the unsigned subtraction of two mp\_int variables under the restriction that the result must be positive. That is when -passing variables $a$ and $b$ the condition that $\vert a \vert \ge \vert b \vert$ must be met for the algorithm to function correctly. This -algorithm is loosely based on algorithm 14.9 \cite[pp. 595]{HAC} and is similar to algorithm S in \cite[pp. 267]{TAOCPV2} as well. As was the case -of the algorithm s\_mp\_add both other references lack discussion concerning various practical details such as when the inputs differ in magnitude. - -The initial sorting of the inputs is trivial in this algorithm since $a$ is guaranteed to have at least the same magnitude of $b$. Steps 1 and 2 -set the $min$ and $max$ variables. Unlike the addition routine there is guaranteed to be no carry which means that the final result can be at -most $max$ digits in length as opposed to $max + 1$. Similar to the addition algorithm the \textbf{used} count of $c$ is copied locally and -set to the maximal count for the operation. - -The subtraction loop that begins on step seven is essentially the same as the addition loop of algorithm s\_mp\_add except single precision -subtraction is used instead. Note the use of the $\gamma$ variable to extract the carry (\textit{also known as the borrow}) within the subtraction -loops. Under the assumption that two's complement single precision arithmetic is used this will successfully extract the desired carry. - -For example, consider subtracting $0101_2$ from $0100_2$ where $\gamma = 4$ and $\beta = 2$. The least significant bit will force a carry upwards to -the third bit which will be set to zero after the borrow. After the very first bit has been subtracted $4 - 1 \equiv 0011_2$ will remain, When the -third bit of $0101_2$ is subtracted from the result it will cause another carry. In this case though the carry will be forced to propagate all the -way to the most significant bit. - -Recall that $\beta < 2^{\gamma}$. This means that if a carry does occur just before the $lg(\beta)$'th bit it will propagate all the way to the most -significant bit. Thus, the high order bits of the mp\_digit that are not part of the actual digit will either be all zero, or all one. All that -is needed is a single zero or one bit for the carry. Therefore a single logical shift right by $\gamma - 1$ positions is sufficient to extract the -carry. This method of carry extraction may seem awkward but the reason for it becomes apparent when the implementation is discussed. - -If $b$ has a smaller magnitude than $a$ then step 9 will force the carry and copy operation to propagate through the larger input $a$ into $c$. Step -10 will ensure that any leading digits of $c$ above the $max$'th position are zeroed. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_s\_mp\_sub.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* low level subtraction (assumes |a| > |b|), HAC pp.595 Algorithm 14.9 */ -018 int -019 s_mp_sub (mp_int * a, mp_int * b, mp_int * c) -020 \{ -021 int olduse, res, min, max; -022 -023 /* find sizes */ -024 min = b->used; -025 max = a->used; -026 -027 /* init result */ -028 if (c->alloc < max) \{ -029 if ((res = mp_grow (c, max)) != MP_OKAY) \{ -030 return res; -031 \} -032 \} -033 olduse = c->used; -034 c->used = max; -035 -036 \{ -037 mp_digit u, *tmpa, *tmpb, *tmpc; -038 int i; -039 -040 /* alias for digit pointers */ -041 tmpa = a->dp; -042 tmpb = b->dp; -043 tmpc = c->dp; -044 -045 /* set carry to zero */ -046 u = 0; -047 for (i = 0; i < min; i++) \{ -048 /* T[i] = A[i] - B[i] - U */ -049 *tmpc = (*tmpa++ - *tmpb++) - u; -050 -051 /* U = carry bit of T[i] -052 * Note this saves performing an AND operation since -053 * if a carry does occur it will propagate all the way to the -054 * MSB. As a result a single shift is enough to get the carry -055 */ -056 u = *tmpc >> ((mp_digit)((CHAR_BIT * sizeof(mp_digit)) - 1)); -057 -058 /* Clear carry from T[i] */ -059 *tmpc++ &= MP_MASK; -060 \} -061 -062 /* now copy higher words if any, e.g. if A has more digits than B */ -063 for (; i < max; i++) \{ -064 /* T[i] = A[i] - U */ -065 *tmpc = *tmpa++ - u; -066 -067 /* U = carry bit of T[i] */ -068 u = *tmpc >> ((mp_digit)((CHAR_BIT * sizeof(mp_digit)) - 1)); -069 -070 /* Clear carry from T[i] */ -071 *tmpc++ &= MP_MASK; -072 \} -073 -074 /* clear digits above used (since we may not have grown result above) */ - -075 for (i = c->used; i < olduse; i++) \{ -076 *tmpc++ = 0; -077 \} -078 \} -079 -080 mp_clamp (c); -081 return MP_OKAY; -082 \} -083 -084 #endif -085 -\end{alltt} -\end{small} - -Like low level addition we ``sort'' the inputs. Except in this case the sorting is hardcoded -(lines 24 and 25). In reality the $min$ and $max$ variables are only aliases and are only -used to make the source code easier to read. Again the pointer alias optimization is used -within this algorithm. The aliases $tmpa$, $tmpb$ and $tmpc$ are initialized -(lines 41, 42 and 43) for $a$, $b$ and $c$ respectively. - -The first subtraction loop (lines 46 through 60) subtract digits from both inputs until the smaller of -the two inputs has been exhausted. As remarked earlier there is an implementation reason for using the ``awkward'' -method of extracting the carry (line 56). The traditional method for extracting the carry would be to shift -by $lg(\beta)$ positions and logically AND the least significant bit. The AND operation is required because all of -the bits above the $\lg(\beta)$'th bit will be set to one after a carry occurs from subtraction. This carry -extraction requires two relatively cheap operations to extract the carry. The other method is to simply shift the -most significant bit to the least significant bit thus extracting the carry with a single cheap operation. This -optimization only works on twos compliment machines which is a safe assumption to make. - -If $a$ has a larger magnitude than $b$ an additional loop (lines 63 through 72) is required to propagate -the carry through $a$ and copy the result to $c$. - -\subsection{High Level Addition} -Now that both lower level addition and subtraction algorithms have been established an effective high level signed addition algorithm can be -established. This high level addition algorithm will be what other algorithms and developers will use to perform addition of mp\_int data -types. - -Recall from section 5.2 that an mp\_int represents an integer with an unsigned mantissa (\textit{the array of digits}) and a \textbf{sign} -flag. A high level addition is actually performed as a series of eight separate cases which can be optimized down to three unique cases. - -\begin{figure}[!here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_add}. \\ -\textbf{Input}. Two mp\_ints $a$ and $b$ \\ -\textbf{Output}. The signed addition $c = a + b$. \\ -\hline \\ -1. if $a.sign = b.sign$ then do \\ -\hspace{3mm}1.1 $c.sign \leftarrow a.sign$ \\ -\hspace{3mm}1.2 $c \leftarrow \vert a \vert + \vert b \vert$ (\textit{s\_mp\_add})\\ -2. else do \\ -\hspace{3mm}2.1 if $\vert a \vert < \vert b \vert$ then do (\textit{mp\_cmp\_mag}) \\ -\hspace{6mm}2.1.1 $c.sign \leftarrow b.sign$ \\ -\hspace{6mm}2.1.2 $c \leftarrow \vert b \vert - \vert a \vert$ (\textit{s\_mp\_sub}) \\ -\hspace{3mm}2.2 else do \\ -\hspace{6mm}2.2.1 $c.sign \leftarrow a.sign$ \\ -\hspace{6mm}2.2.2 $c \leftarrow \vert a \vert - \vert b \vert$ \\ -3. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_add} -\end{figure} - -\textbf{Algorithm mp\_add.} -This algorithm performs the signed addition of two mp\_int variables. There is no reference algorithm to draw upon from -either \cite{TAOCPV2} or \cite{HAC} since they both only provide unsigned operations. The algorithm is fairly -straightforward but restricted since subtraction can only produce positive results. - -\begin{figure}[here] -\begin{small} -\begin{center} -\begin{tabular}{|c|c|c|c|c|} -\hline \textbf{Sign of $a$} & \textbf{Sign of $b$} & \textbf{$\vert a \vert > \vert b \vert $} & \textbf{Unsigned Operation} & \textbf{Result Sign Flag} \\ -\hline $+$ & $+$ & Yes & $c = a + b$ & $a.sign$ \\ -\hline $+$ & $+$ & No & $c = a + b$ & $a.sign$ \\ -\hline $-$ & $-$ & Yes & $c = a + b$ & $a.sign$ \\ -\hline $-$ & $-$ & No & $c = a + b$ & $a.sign$ \\ -\hline &&&&\\ - -\hline $+$ & $-$ & No & $c = b - a$ & $b.sign$ \\ -\hline $-$ & $+$ & No & $c = b - a$ & $b.sign$ \\ - -\hline &&&&\\ - -\hline $+$ & $-$ & Yes & $c = a - b$ & $a.sign$ \\ -\hline $-$ & $+$ & Yes & $c = a - b$ & $a.sign$ \\ - -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Addition Guide Chart} -\label{fig:AddChart} -\end{figure} - -Figure~\ref{fig:AddChart} lists all of the eight possible input combinations and is sorted to show that only three -specific cases need to be handled. The return code of the unsigned operations at step 1.2, 2.1.2 and 2.2.2 are -forwarded to step three to check for errors. This simplifies the description of the algorithm considerably and best -follows how the implementation actually was achieved. - -Also note how the \textbf{sign} is set before the unsigned addition or subtraction is performed. Recall from the descriptions of algorithms -s\_mp\_add and s\_mp\_sub that the mp\_clamp function is used at the end to trim excess digits. The mp\_clamp algorithm will set the \textbf{sign} -to \textbf{MP\_ZPOS} when the \textbf{used} digit count reaches zero. - -For example, consider performing $-a + a$ with algorithm mp\_add. By the description of the algorithm the sign is set to \textbf{MP\_NEG} which would -produce a result of $-0$. However, since the sign is set first then the unsigned addition is performed the subsequent usage of algorithm mp\_clamp -within algorithm s\_mp\_add will force $-0$ to become $0$. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_add.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* high level addition (handles signs) */ -018 int mp_add (mp_int * a, mp_int * b, mp_int * c) -019 \{ -020 int sa, sb, res; -021 -022 /* get sign of both inputs */ -023 sa = a->sign; -024 sb = b->sign; -025 -026 /* handle two cases, not four */ -027 if (sa == sb) \{ -028 /* both positive or both negative */ -029 /* add their magnitudes, copy the sign */ -030 c->sign = sa; -031 res = s_mp_add (a, b, c); -032 \} else \{ -033 /* one positive, the other negative */ -034 /* subtract the one with the greater magnitude from */ -035 /* the one of the lesser magnitude. The result gets */ -036 /* the sign of the one with the greater magnitude. */ -037 if (mp_cmp_mag (a, b) == MP_LT) \{ -038 c->sign = sb; -039 res = s_mp_sub (b, a, c); -040 \} else \{ -041 c->sign = sa; -042 res = s_mp_sub (a, b, c); -043 \} -044 \} -045 return res; -046 \} -047 -048 #endif -049 -\end{alltt} -\end{small} - -The source code follows the algorithm fairly closely. The most notable new source code addition is the usage of the $res$ integer variable which -is used to pass result of the unsigned operations forward. Unlike in the algorithm, the variable $res$ is merely returned as is without -explicitly checking it and returning the constant \textbf{MP\_OKAY}. The observation is this algorithm will succeed or fail only if the lower -level functions do so. Returning their return code is sufficient. - -\subsection{High Level Subtraction} -The high level signed subtraction algorithm is essentially the same as the high level signed addition algorithm. - -\newpage\begin{figure}[!here] -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_sub}. \\ -\textbf{Input}. Two mp\_ints $a$ and $b$ \\ -\textbf{Output}. The signed subtraction $c = a - b$. \\ -\hline \\ -1. if $a.sign \ne b.sign$ then do \\ -\hspace{3mm}1.1 $c.sign \leftarrow a.sign$ \\ -\hspace{3mm}1.2 $c \leftarrow \vert a \vert + \vert b \vert$ (\textit{s\_mp\_add}) \\ -2. else do \\ -\hspace{3mm}2.1 if $\vert a \vert \ge \vert b \vert$ then do (\textit{mp\_cmp\_mag}) \\ -\hspace{6mm}2.1.1 $c.sign \leftarrow a.sign$ \\ -\hspace{6mm}2.1.2 $c \leftarrow \vert a \vert - \vert b \vert$ (\textit{s\_mp\_sub}) \\ -\hspace{3mm}2.2 else do \\ -\hspace{6mm}2.2.1 $c.sign \leftarrow \left \lbrace \begin{array}{ll} - MP\_ZPOS & \mbox{if }a.sign = MP\_NEG \\ - MP\_NEG & \mbox{otherwise} \\ - \end{array} \right .$ \\ -\hspace{6mm}2.2.2 $c \leftarrow \vert b \vert - \vert a \vert$ \\ -3. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\caption{Algorithm mp\_sub} -\end{figure} - -\textbf{Algorithm mp\_sub.} -This algorithm performs the signed subtraction of two inputs. Similar to algorithm mp\_add there is no reference in either \cite{TAOCPV2} or -\cite{HAC}. Also this algorithm is restricted by algorithm s\_mp\_sub. Chart \ref{fig:SubChart} lists the eight possible inputs and -the operations required. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{|c|c|c|c|c|} -\hline \textbf{Sign of $a$} & \textbf{Sign of $b$} & \textbf{$\vert a \vert \ge \vert b \vert $} & \textbf{Unsigned Operation} & \textbf{Result Sign Flag} \\ -\hline $+$ & $-$ & Yes & $c = a + b$ & $a.sign$ \\ -\hline $+$ & $-$ & No & $c = a + b$ & $a.sign$ \\ -\hline $-$ & $+$ & Yes & $c = a + b$ & $a.sign$ \\ -\hline $-$ & $+$ & No & $c = a + b$ & $a.sign$ \\ -\hline &&&& \\ -\hline $+$ & $+$ & Yes & $c = a - b$ & $a.sign$ \\ -\hline $-$ & $-$ & Yes & $c = a - b$ & $a.sign$ \\ -\hline &&&& \\ -\hline $+$ & $+$ & No & $c = b - a$ & $\mbox{opposite of }a.sign$ \\ -\hline $-$ & $-$ & No & $c = b - a$ & $\mbox{opposite of }a.sign$ \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Subtraction Guide Chart} -\label{fig:SubChart} -\end{figure} - -Similar to the case of algorithm mp\_add the \textbf{sign} is set first before the unsigned addition or subtraction. That is to prevent the -algorithm from producing $-a - -a = -0$ as a result. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_sub.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* high level subtraction (handles signs) */ -018 int -019 mp_sub (mp_int * a, mp_int * b, mp_int * c) -020 \{ -021 int sa, sb, res; -022 -023 sa = a->sign; -024 sb = b->sign; -025 -026 if (sa != sb) \{ -027 /* subtract a negative from a positive, OR */ -028 /* subtract a positive from a negative. */ -029 /* In either case, ADD their magnitudes, */ -030 /* and use the sign of the first number. */ -031 c->sign = sa; -032 res = s_mp_add (a, b, c); -033 \} else \{ -034 /* subtract a positive from a positive, OR */ -035 /* subtract a negative from a negative. */ -036 /* First, take the difference between their */ -037 /* magnitudes, then... */ -038 if (mp_cmp_mag (a, b) != MP_LT) \{ -039 /* Copy the sign from the first */ -040 c->sign = sa; -041 /* The first has a larger or equal magnitude */ -042 res = s_mp_sub (a, b, c); -043 \} else \{ -044 /* The result has the *opposite* sign from */ -045 /* the first number. */ -046 c->sign = (sa == MP_ZPOS) ? MP_NEG : MP_ZPOS; -047 /* The second has a larger magnitude */ -048 res = s_mp_sub (b, a, c); -049 \} -050 \} -051 return res; -052 \} -053 -054 #endif -055 -\end{alltt} -\end{small} - -Much like the implementation of algorithm mp\_add the variable $res$ is used to catch the return code of the unsigned addition or subtraction operations -and forward it to the end of the function. On line 38 the ``not equal to'' \textbf{MP\_LT} expression is used to emulate a -``greater than or equal to'' comparison. - -\section{Bit and Digit Shifting} -It is quite common to think of a multiple precision integer as a polynomial in $x$, that is $y = f(\beta)$ where $f(x) = \sum_{i=0}^{n-1} a_i x^i$. -This notation arises within discussion of Montgomery and Diminished Radix Reduction as well as Karatsuba multiplication and squaring. - -In order to facilitate operations on polynomials in $x$ as above a series of simple ``digit'' algorithms have to be established. That is to shift -the digits left or right as well to shift individual bits of the digits left and right. It is important to note that not all ``shift'' operations -are on radix-$\beta$ digits. - -\subsection{Multiplication by Two} - -In a binary system where the radix is a power of two multiplication by two not only arises often in other algorithms it is a fairly efficient -operation to perform. A single precision logical shift left is sufficient to multiply a single digit by two. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_mul\_2}. \\ -\textbf{Input}. One mp\_int $a$ \\ -\textbf{Output}. $b = 2a$. \\ -\hline \\ -1. If $b.alloc < a.used + 1$ then grow $b$ to hold $a.used + 1$ digits. (\textit{mp\_grow}) \\ -2. $oldused \leftarrow b.used$ \\ -3. $b.used \leftarrow a.used$ \\ -4. $r \leftarrow 0$ \\ -5. for $n$ from 0 to $a.used - 1$ do \\ -\hspace{3mm}5.1 $rr \leftarrow a_n >> (lg(\beta) - 1)$ \\ -\hspace{3mm}5.2 $b_n \leftarrow (a_n << 1) + r \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{3mm}5.3 $r \leftarrow rr$ \\ -6. If $r \ne 0$ then do \\ -\hspace{3mm}6.1 $b_{n + 1} \leftarrow r$ \\ -\hspace{3mm}6.2 $b.used \leftarrow b.used + 1$ \\ -7. If $b.used < oldused - 1$ then do \\ -\hspace{3mm}7.1 for $n$ from $b.used$ to $oldused - 1$ do \\ -\hspace{6mm}7.1.1 $b_n \leftarrow 0$ \\ -8. $b.sign \leftarrow a.sign$ \\ -9. Return(\textit{MP\_OKAY}).\\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_mul\_2} -\end{figure} - -\textbf{Algorithm mp\_mul\_2.} -This algorithm will quickly multiply a mp\_int by two provided $\beta$ is a power of two. Neither \cite{TAOCPV2} nor \cite{HAC} describe such -an algorithm despite the fact it arises often in other algorithms. The algorithm is setup much like the lower level algorithm s\_mp\_add since -it is for all intents and purposes equivalent to the operation $b = \vert a \vert + \vert a \vert$. - -Step 1 and 2 grow the input as required to accomodate the maximum number of \textbf{used} digits in the result. The initial \textbf{used} count -is set to $a.used$ at step 4. Only if there is a final carry will the \textbf{used} count require adjustment. - -Step 6 is an optimization implementation of the addition loop for this specific case. That is since the two values being added together -are the same there is no need to perform two reads from the digits of $a$. Step 6.1 performs a single precision shift on the current digit $a_n$ to -obtain what will be the carry for the next iteration. Step 6.2 calculates the $n$'th digit of the result as single precision shift of $a_n$ plus -the previous carry. Recall from section 4.1 that $a_n << 1$ is equivalent to $a_n \cdot 2$. An iteration of the addition loop is finished with -forwarding the carry to the next iteration. - -Step 7 takes care of any final carry by setting the $a.used$'th digit of the result to the carry and augmenting the \textbf{used} count of $b$. -Step 8 clears any leading digits of $b$ in case it originally had a larger magnitude than $a$. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_mul\_2.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* b = a*2 */ -018 int mp_mul_2(mp_int * a, mp_int * b) -019 \{ -020 int x, res, oldused; -021 -022 /* grow to accomodate result */ -023 if (b->alloc < (a->used + 1)) \{ -024 if ((res = mp_grow (b, a->used + 1)) != MP_OKAY) \{ -025 return res; -026 \} -027 \} -028 -029 oldused = b->used; -030 b->used = a->used; -031 -032 \{ -033 mp_digit r, rr, *tmpa, *tmpb; -034 -035 /* alias for source */ -036 tmpa = a->dp; -037 -038 /* alias for dest */ -039 tmpb = b->dp; -040 -041 /* carry */ -042 r = 0; -043 for (x = 0; x < a->used; x++) \{ -044 -045 /* get what will be the *next* carry bit from the -046 * MSB of the current digit -047 */ -048 rr = *tmpa >> ((mp_digit)(DIGIT_BIT - 1)); -049 -050 /* now shift up this digit, add in the carry [from the previous] */ -051 *tmpb++ = ((*tmpa++ << ((mp_digit)1)) | r) & MP_MASK; -052 -053 /* copy the carry that would be from the source -054 * digit into the next iteration -055 */ -056 r = rr; -057 \} -058 -059 /* new leading digit? */ -060 if (r != 0) \{ -061 /* add a MSB which is always 1 at this point */ -062 *tmpb = 1; -063 ++(b->used); -064 \} -065 -066 /* now zero any excess digits on the destination -067 * that we didn't write to -068 */ -069 tmpb = b->dp + b->used; -070 for (x = b->used; x < oldused; x++) \{ -071 *tmpb++ = 0; -072 \} -073 \} -074 b->sign = a->sign; -075 return MP_OKAY; -076 \} -077 #endif -078 -\end{alltt} -\end{small} - -This implementation is essentially an optimized implementation of s\_mp\_add for the case of doubling an input. The only noteworthy difference -is the use of the logical shift operator on line 51 to perform a single precision doubling. - -\subsection{Division by Two} -A division by two can just as easily be accomplished with a logical shift right as multiplication by two can be with a logical shift left. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_div\_2}. \\ -\textbf{Input}. One mp\_int $a$ \\ -\textbf{Output}. $b = a/2$. \\ -\hline \\ -1. If $b.alloc < a.used$ then grow $b$ to hold $a.used$ digits. (\textit{mp\_grow}) \\ -2. If the reallocation failed return(\textit{MP\_MEM}). \\ -3. $oldused \leftarrow b.used$ \\ -4. $b.used \leftarrow a.used$ \\ -5. $r \leftarrow 0$ \\ -6. for $n$ from $b.used - 1$ to $0$ do \\ -\hspace{3mm}6.1 $rr \leftarrow a_n \mbox{ (mod }2\mbox{)}$\\ -\hspace{3mm}6.2 $b_n \leftarrow (a_n >> 1) + (r << (lg(\beta) - 1)) \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{3mm}6.3 $r \leftarrow rr$ \\ -7. If $b.used < oldused - 1$ then do \\ -\hspace{3mm}7.1 for $n$ from $b.used$ to $oldused - 1$ do \\ -\hspace{6mm}7.1.1 $b_n \leftarrow 0$ \\ -8. $b.sign \leftarrow a.sign$ \\ -9. Clamp excess digits of $b$. (\textit{mp\_clamp}) \\ -10. Return(\textit{MP\_OKAY}).\\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_div\_2} -\end{figure} - -\textbf{Algorithm mp\_div\_2.} -This algorithm will divide an mp\_int by two using logical shifts to the right. Like mp\_mul\_2 it uses a modified low level addition -core as the basis of the algorithm. Unlike mp\_mul\_2 the shift operations work from the leading digit to the trailing digit. The algorithm -could be written to work from the trailing digit to the leading digit however, it would have to stop one short of $a.used - 1$ digits to prevent -reading past the end of the array of digits. - -Essentially the loop at step 6 is similar to that of mp\_mul\_2 except the logical shifts go in the opposite direction and the carry is at the -least significant bit not the most significant bit. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_div\_2.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* b = a/2 */ -018 int mp_div_2(mp_int * a, mp_int * b) -019 \{ -020 int x, res, oldused; -021 -022 /* copy */ -023 if (b->alloc < a->used) \{ -024 if ((res = mp_grow (b, a->used)) != MP_OKAY) \{ -025 return res; -026 \} -027 \} -028 -029 oldused = b->used; -030 b->used = a->used; -031 \{ -032 mp_digit r, rr, *tmpa, *tmpb; -033 -034 /* source alias */ -035 tmpa = a->dp + b->used - 1; -036 -037 /* dest alias */ -038 tmpb = b->dp + b->used - 1; -039 -040 /* carry */ -041 r = 0; -042 for (x = b->used - 1; x >= 0; x--) \{ -043 /* get the carry for the next iteration */ -044 rr = *tmpa & 1; -045 -046 /* shift the current digit, add in carry and store */ -047 *tmpb-- = (*tmpa-- >> 1) | (r << (DIGIT_BIT - 1)); -048 -049 /* forward carry to next iteration */ -050 r = rr; -051 \} -052 -053 /* zero excess digits */ -054 tmpb = b->dp + b->used; -055 for (x = b->used; x < oldused; x++) \{ -056 *tmpb++ = 0; -057 \} -058 \} -059 b->sign = a->sign; -060 mp_clamp (b); -061 return MP_OKAY; -062 \} -063 #endif -064 -\end{alltt} -\end{small} - -\section{Polynomial Basis Operations} -Recall from section 4.3 that any integer can be represented as a polynomial in $x$ as $y = f(\beta)$. Such a representation is also known as -the polynomial basis \cite[pp. 48]{ROSE}. Given such a notation a multiplication or division by $x$ amounts to shifting whole digits a single -place. The need for such operations arises in several other higher level algorithms such as Barrett and Montgomery reduction, integer -division and Karatsuba multiplication. - -Converting from an array of digits to polynomial basis is very simple. Consider the integer $y \equiv (a_2, a_1, a_0)_{\beta}$ and recall that -$y = \sum_{i=0}^{2} a_i \beta^i$. Simply replace $\beta$ with $x$ and the expression is in polynomial basis. For example, $f(x) = 8x + 9$ is the -polynomial basis representation for $89$ using radix ten. That is, $f(10) = 8(10) + 9 = 89$. - -\subsection{Multiplication by $x$} - -Given a polynomial in $x$ such as $f(x) = a_n x^n + a_{n-1} x^{n-1} + ... + a_0$ multiplying by $x$ amounts to shifting the coefficients up one -degree. In this case $f(x) \cdot x = a_n x^{n+1} + a_{n-1} x^n + ... + a_0 x$. From a scalar basis point of view multiplying by $x$ is equivalent to -multiplying by the integer $\beta$. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_lshd}. \\ -\textbf{Input}. One mp\_int $a$ and an integer $b$ \\ -\textbf{Output}. $a \leftarrow a \cdot \beta^b$ (equivalent to multiplication by $x^b$). \\ -\hline \\ -1. If $b \le 0$ then return(\textit{MP\_OKAY}). \\ -2. If $a.alloc < a.used + b$ then grow $a$ to at least $a.used + b$ digits. (\textit{mp\_grow}). \\ -3. If the reallocation failed return(\textit{MP\_MEM}). \\ -4. $a.used \leftarrow a.used + b$ \\ -5. $i \leftarrow a.used - 1$ \\ -6. $j \leftarrow a.used - 1 - b$ \\ -7. for $n$ from $a.used - 1$ to $b$ do \\ -\hspace{3mm}7.1 $a_{i} \leftarrow a_{j}$ \\ -\hspace{3mm}7.2 $i \leftarrow i - 1$ \\ -\hspace{3mm}7.3 $j \leftarrow j - 1$ \\ -8. for $n$ from 0 to $b - 1$ do \\ -\hspace{3mm}8.1 $a_n \leftarrow 0$ \\ -9. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_lshd} -\end{figure} - -\textbf{Algorithm mp\_lshd.} -This algorithm multiplies an mp\_int by the $b$'th power of $x$. This is equivalent to multiplying by $\beta^b$. The algorithm differs -from the other algorithms presented so far as it performs the operation in place instead storing the result in a separate location. The -motivation behind this change is due to the way this function is typically used. Algorithms such as mp\_add store the result in an optionally -different third mp\_int because the original inputs are often still required. Algorithm mp\_lshd (\textit{and similarly algorithm mp\_rshd}) is -typically used on values where the original value is no longer required. The algorithm will return success immediately if -$b \le 0$ since the rest of algorithm is only valid when $b > 0$. - -First the destination $a$ is grown as required to accomodate the result. The counters $i$ and $j$ are used to form a \textit{sliding window} over -the digits of $a$ of length $b$. The head of the sliding window is at $i$ (\textit{the leading digit}) and the tail at $j$ (\textit{the trailing digit}). -The loop on step 7 copies the digit from the tail to the head. In each iteration the window is moved down one digit. The last loop on -step 8 sets the lower $b$ digits to zero. - -\newpage -\begin{center} -\begin{figure}[here] -\includegraphics{pics/sliding_window.ps} -\caption{Sliding Window Movement} -\label{pic:sliding_window} -\end{figure} -\end{center} - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_lshd.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* shift left a certain amount of digits */ -018 int mp_lshd (mp_int * a, int b) -019 \{ -020 int x, res; -021 -022 /* if its less than zero return */ -023 if (b <= 0) \{ -024 return MP_OKAY; -025 \} -026 -027 /* grow to fit the new digits */ -028 if (a->alloc < (a->used + b)) \{ -029 if ((res = mp_grow (a, a->used + b)) != MP_OKAY) \{ -030 return res; -031 \} -032 \} -033 -034 \{ -035 mp_digit *top, *bottom; -036 -037 /* increment the used by the shift amount then copy upwards */ -038 a->used += b; -039 -040 /* top */ -041 top = a->dp + a->used - 1; -042 -043 /* base */ -044 bottom = (a->dp + a->used - 1) - b; -045 -046 /* much like mp_rshd this is implemented using a sliding window -047 * except the window goes the otherway around. Copying from -048 * the bottom to the top. see bn_mp_rshd.c for more info. -049 */ -050 for (x = a->used - 1; x >= b; x--) \{ -051 *top-- = *bottom--; -052 \} -053 -054 /* zero the lower digits */ -055 top = a->dp; -056 for (x = 0; x < b; x++) \{ -057 *top++ = 0; -058 \} -059 \} -060 return MP_OKAY; -061 \} -062 #endif -063 -\end{alltt} -\end{small} - -The if statement (line 23) ensures that the $b$ variable is greater than zero since we do not interpret negative -shift counts properly. The \textbf{used} count is incremented by $b$ before the copy loop begins. This elminates -the need for an additional variable in the for loop. The variable $top$ (line 41) is an alias -for the leading digit while $bottom$ (line 44) is an alias for the trailing edge. The aliases form a -window of exactly $b$ digits over the input. - -\subsection{Division by $x$} - -Division by powers of $x$ is easily achieved by shifting the digits right and removing any that will end up to the right of the zero'th digit. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_rshd}. \\ -\textbf{Input}. One mp\_int $a$ and an integer $b$ \\ -\textbf{Output}. $a \leftarrow a / \beta^b$ (Divide by $x^b$). \\ -\hline \\ -1. If $b \le 0$ then return. \\ -2. If $a.used \le b$ then do \\ -\hspace{3mm}2.1 Zero $a$. (\textit{mp\_zero}). \\ -\hspace{3mm}2.2 Return. \\ -3. $i \leftarrow 0$ \\ -4. $j \leftarrow b$ \\ -5. for $n$ from 0 to $a.used - b - 1$ do \\ -\hspace{3mm}5.1 $a_i \leftarrow a_j$ \\ -\hspace{3mm}5.2 $i \leftarrow i + 1$ \\ -\hspace{3mm}5.3 $j \leftarrow j + 1$ \\ -6. for $n$ from $a.used - b$ to $a.used - 1$ do \\ -\hspace{3mm}6.1 $a_n \leftarrow 0$ \\ -7. $a.used \leftarrow a.used - b$ \\ -8. Return. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_rshd} -\end{figure} - -\textbf{Algorithm mp\_rshd.} -This algorithm divides the input in place by the $b$'th power of $x$. It is analogous to dividing by a $\beta^b$ but much quicker since -it does not require single precision division. This algorithm does not actually return an error code as it cannot fail. - -If the input $b$ is less than one the algorithm quickly returns without performing any work. If the \textbf{used} count is less than or equal -to the shift count $b$ then it will simply zero the input and return. - -After the trivial cases of inputs have been handled the sliding window is setup. Much like the case of algorithm mp\_lshd a sliding window that -is $b$ digits wide is used to copy the digits. Unlike mp\_lshd the window slides in the opposite direction from the trailing to the leading digit. -Also the digits are copied from the leading to the trailing edge. - -Once the window copy is complete the upper digits must be zeroed and the \textbf{used} count decremented. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_rshd.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* shift right a certain amount of digits */ -018 void mp_rshd (mp_int * a, int b) -019 \{ -020 int x; -021 -022 /* if b <= 0 then ignore it */ -023 if (b <= 0) \{ -024 return; -025 \} -026 -027 /* if b > used then simply zero it and return */ -028 if (a->used <= b) \{ -029 mp_zero (a); -030 return; -031 \} -032 -033 \{ -034 mp_digit *bottom, *top; -035 -036 /* shift the digits down */ -037 -038 /* bottom */ -039 bottom = a->dp; -040 -041 /* top [offset into digits] */ -042 top = a->dp + b; -043 -044 /* this is implemented as a sliding window where -045 * the window is b-digits long and digits from -046 * the top of the window are copied to the bottom -047 * -048 * e.g. -049 -050 b-2 | b-1 | b0 | b1 | b2 | ... | bb | ----> -051 /\symbol{92} | ----> -052 \symbol{92}-------------------/ ----> -053 */ -054 for (x = 0; x < (a->used - b); x++) \{ -055 *bottom++ = *top++; -056 \} -057 -058 /* zero the top digits */ -059 for (; x < a->used; x++) \{ -060 *bottom++ = 0; -061 \} -062 \} -063 -064 /* remove excess digits */ -065 a->used -= b; -066 \} -067 #endif -068 -\end{alltt} -\end{small} - -The only noteworthy element of this routine is the lack of a return type since it cannot fail. Like mp\_lshd() we -form a sliding window except we copy in the other direction. After the window (line 59) we then zero -the upper digits of the input to make sure the result is correct. - -\section{Powers of Two} - -Now that algorithms for moving single bits as well as whole digits exist algorithms for moving the ``in between'' distances are required. For -example, to quickly multiply by $2^k$ for any $k$ without using a full multiplier algorithm would prove useful. Instead of performing single -shifts $k$ times to achieve a multiplication by $2^{\pm k}$ a mixture of whole digit shifting and partial digit shifting is employed. - -\subsection{Multiplication by Power of Two} - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_mul\_2d}. \\ -\textbf{Input}. One mp\_int $a$ and an integer $b$ \\ -\textbf{Output}. $c \leftarrow a \cdot 2^b$. \\ -\hline \\ -1. $c \leftarrow a$. (\textit{mp\_copy}) \\ -2. If $c.alloc < c.used + \lfloor b / lg(\beta) \rfloor + 2$ then grow $c$ accordingly. \\ -3. If the reallocation failed return(\textit{MP\_MEM}). \\ -4. If $b \ge lg(\beta)$ then \\ -\hspace{3mm}4.1 $c \leftarrow c \cdot \beta^{\lfloor b / lg(\beta) \rfloor}$ (\textit{mp\_lshd}). \\ -\hspace{3mm}4.2 If step 4.1 failed return(\textit{MP\_MEM}). \\ -5. $d \leftarrow b \mbox{ (mod }lg(\beta)\mbox{)}$ \\ -6. If $d \ne 0$ then do \\ -\hspace{3mm}6.1 $mask \leftarrow 2^d$ \\ -\hspace{3mm}6.2 $r \leftarrow 0$ \\ -\hspace{3mm}6.3 for $n$ from $0$ to $c.used - 1$ do \\ -\hspace{6mm}6.3.1 $rr \leftarrow c_n >> (lg(\beta) - d) \mbox{ (mod }mask\mbox{)}$ \\ -\hspace{6mm}6.3.2 $c_n \leftarrow (c_n << d) + r \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{6mm}6.3.3 $r \leftarrow rr$ \\ -\hspace{3mm}6.4 If $r > 0$ then do \\ -\hspace{6mm}6.4.1 $c_{c.used} \leftarrow r$ \\ -\hspace{6mm}6.4.2 $c.used \leftarrow c.used + 1$ \\ -7. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_mul\_2d} -\end{figure} - -\textbf{Algorithm mp\_mul\_2d.} -This algorithm multiplies $a$ by $2^b$ and stores the result in $c$. The algorithm uses algorithm mp\_lshd and a derivative of algorithm mp\_mul\_2 to -quickly compute the product. - -First the algorithm will multiply $a$ by $x^{\lfloor b / lg(\beta) \rfloor}$ which will ensure that the remainder multiplicand is less than -$\beta$. For example, if $b = 37$ and $\beta = 2^{28}$ then this step will multiply by $x$ leaving a multiplication by $2^{37 - 28} = 2^{9}$ -left. - -After the digits have been shifted appropriately at most $lg(\beta) - 1$ shifts are left to perform. Step 5 calculates the number of remaining shifts -required. If it is non-zero a modified shift loop is used to calculate the remaining product. -Essentially the loop is a generic version of algorithm mp\_mul\_2 designed to handle any shift count in the range $1 \le x < lg(\beta)$. The $mask$ -variable is used to extract the upper $d$ bits to form the carry for the next iteration. - -This algorithm is loosely measured as a $O(2n)$ algorithm which means that if the input is $n$-digits that it takes $2n$ ``time'' to -complete. It is possible to optimize this algorithm down to a $O(n)$ algorithm at a cost of making the algorithm slightly harder to follow. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_mul\_2d.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* shift left by a certain bit count */ -018 int mp_mul_2d (mp_int * a, int b, mp_int * c) -019 \{ -020 mp_digit d; -021 int res; -022 -023 /* copy */ -024 if (a != c) \{ -025 if ((res = mp_copy (a, c)) != MP_OKAY) \{ -026 return res; -027 \} -028 \} -029 -030 if (c->alloc < (int)(c->used + (b / DIGIT_BIT) + 1)) \{ -031 if ((res = mp_grow (c, c->used + (b / DIGIT_BIT) + 1)) != MP_OKAY) \{ -032 return res; -033 \} -034 \} -035 -036 /* shift by as many digits in the bit count */ -037 if (b >= (int)DIGIT_BIT) \{ -038 if ((res = mp_lshd (c, b / DIGIT_BIT)) != MP_OKAY) \{ -039 return res; -040 \} -041 \} -042 -043 /* shift any bit count < DIGIT_BIT */ -044 d = (mp_digit) (b % DIGIT_BIT); -045 if (d != 0) \{ -046 mp_digit *tmpc, shift, mask, r, rr; -047 int x; -048 -049 /* bitmask for carries */ -050 mask = (((mp_digit)1) << d) - 1; -051 -052 /* shift for msbs */ -053 shift = DIGIT_BIT - d; -054 -055 /* alias */ -056 tmpc = c->dp; -057 -058 /* carry */ -059 r = 0; -060 for (x = 0; x < c->used; x++) \{ -061 /* get the higher bits of the current word */ -062 rr = (*tmpc >> shift) & mask; -063 -064 /* shift the current word and OR in the carry */ -065 *tmpc = ((*tmpc << d) | r) & MP_MASK; -066 ++tmpc; -067 -068 /* set the carry to the carry bits of the current word */ -069 r = rr; -070 \} -071 -072 /* set final carry */ -073 if (r != 0) \{ -074 c->dp[(c->used)++] = r; -075 \} -076 \} -077 mp_clamp (c); -078 return MP_OKAY; -079 \} -080 #endif -081 -\end{alltt} -\end{small} - -The shifting is performed in--place which means the first step (line 24) is to copy the input to the -destination. We avoid calling mp\_copy() by making sure the mp\_ints are different. The destination then -has to be grown (line 31) to accomodate the result. - -If the shift count $b$ is larger than $lg(\beta)$ then a call to mp\_lshd() is used to handle all of the multiples -of $lg(\beta)$. Leaving only a remaining shift of $lg(\beta) - 1$ or fewer bits left. Inside the actual shift -loop (lines 45 to 76) we make use of pre--computed values $shift$ and $mask$. These are used to -extract the carry bit(s) to pass into the next iteration of the loop. The $r$ and $rr$ variables form a -chain between consecutive iterations to propagate the carry. - -\subsection{Division by Power of Two} - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_div\_2d}. \\ -\textbf{Input}. One mp\_int $a$ and an integer $b$ \\ -\textbf{Output}. $c \leftarrow \lfloor a / 2^b \rfloor, d \leftarrow a \mbox{ (mod }2^b\mbox{)}$. \\ -\hline \\ -1. If $b \le 0$ then do \\ -\hspace{3mm}1.1 $c \leftarrow a$ (\textit{mp\_copy}) \\ -\hspace{3mm}1.2 $d \leftarrow 0$ (\textit{mp\_zero}) \\ -\hspace{3mm}1.3 Return(\textit{MP\_OKAY}). \\ -2. $c \leftarrow a$ \\ -3. $d \leftarrow a \mbox{ (mod }2^b\mbox{)}$ (\textit{mp\_mod\_2d}) \\ -4. If $b \ge lg(\beta)$ then do \\ -\hspace{3mm}4.1 $c \leftarrow \lfloor c/\beta^{\lfloor b/lg(\beta) \rfloor} \rfloor$ (\textit{mp\_rshd}). \\ -5. $k \leftarrow b \mbox{ (mod }lg(\beta)\mbox{)}$ \\ -6. If $k \ne 0$ then do \\ -\hspace{3mm}6.1 $mask \leftarrow 2^k$ \\ -\hspace{3mm}6.2 $r \leftarrow 0$ \\ -\hspace{3mm}6.3 for $n$ from $c.used - 1$ to $0$ do \\ -\hspace{6mm}6.3.1 $rr \leftarrow c_n \mbox{ (mod }mask\mbox{)}$ \\ -\hspace{6mm}6.3.2 $c_n \leftarrow (c_n >> k) + (r << (lg(\beta) - k))$ \\ -\hspace{6mm}6.3.3 $r \leftarrow rr$ \\ -7. Clamp excess digits of $c$. (\textit{mp\_clamp}) \\ -8. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_div\_2d} -\end{figure} - -\textbf{Algorithm mp\_div\_2d.} -This algorithm will divide an input $a$ by $2^b$ and produce the quotient and remainder. The algorithm is designed much like algorithm -mp\_mul\_2d by first using whole digit shifts then single precision shifts. This algorithm will also produce the remainder of the division -by using algorithm mp\_mod\_2d. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_div\_2d.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* shift right by a certain bit count (store quotient in c, optional remaind - er in d) */ -018 int mp_div_2d (mp_int * a, int b, mp_int * c, mp_int * d) -019 \{ -020 mp_digit D, r, rr; -021 int x, res; -022 mp_int t; -023 -024 -025 /* if the shift count is <= 0 then we do no work */ -026 if (b <= 0) \{ -027 res = mp_copy (a, c); -028 if (d != NULL) \{ -029 mp_zero (d); -030 \} -031 return res; -032 \} -033 -034 if ((res = mp_init (&t)) != MP_OKAY) \{ -035 return res; -036 \} -037 -038 /* get the remainder */ -039 if (d != NULL) \{ -040 if ((res = mp_mod_2d (a, b, &t)) != MP_OKAY) \{ -041 mp_clear (&t); -042 return res; -043 \} -044 \} -045 -046 /* copy */ -047 if ((res = mp_copy (a, c)) != MP_OKAY) \{ -048 mp_clear (&t); -049 return res; -050 \} -051 -052 /* shift by as many digits in the bit count */ -053 if (b >= (int)DIGIT_BIT) \{ -054 mp_rshd (c, b / DIGIT_BIT); -055 \} -056 -057 /* shift any bit count < DIGIT_BIT */ -058 D = (mp_digit) (b % DIGIT_BIT); -059 if (D != 0) \{ -060 mp_digit *tmpc, mask, shift; -061 -062 /* mask */ -063 mask = (((mp_digit)1) << D) - 1; -064 -065 /* shift for lsb */ -066 shift = DIGIT_BIT - D; -067 -068 /* alias */ -069 tmpc = c->dp + (c->used - 1); -070 -071 /* carry */ -072 r = 0; -073 for (x = c->used - 1; x >= 0; x--) \{ -074 /* get the lower bits of this word in a temp */ -075 rr = *tmpc & mask; -076 -077 /* shift the current word and mix in the carry bits from the previous - word */ -078 *tmpc = (*tmpc >> D) | (r << shift); -079 --tmpc; -080 -081 /* set the carry to the carry bits of the current word found above */ -082 r = rr; -083 \} -084 \} -085 mp_clamp (c); -086 if (d != NULL) \{ -087 mp_exch (&t, d); -088 \} -089 mp_clear (&t); -090 return MP_OKAY; -091 \} -092 #endif -093 -\end{alltt} -\end{small} - -The implementation of algorithm mp\_div\_2d is slightly different than the algorithm specifies. The remainder $d$ may be optionally -ignored by passing \textbf{NULL} as the pointer to the mp\_int variable. The temporary mp\_int variable $t$ is used to hold the -result of the remainder operation until the end. This allows $d$ and $a$ to represent the same mp\_int without modifying $a$ before -the quotient is obtained. - -The remainder of the source code is essentially the same as the source code for mp\_mul\_2d. The only significant difference is -the direction of the shifts. - -\subsection{Remainder of Division by Power of Two} - -The last algorithm in the series of polynomial basis power of two algorithms is calculating the remainder of division by $2^b$. This -algorithm benefits from the fact that in twos complement arithmetic $a \mbox{ (mod }2^b\mbox{)}$ is the same as $a$ AND $2^b - 1$. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_mod\_2d}. \\ -\textbf{Input}. One mp\_int $a$ and an integer $b$ \\ -\textbf{Output}. $c \leftarrow a \mbox{ (mod }2^b\mbox{)}$. \\ -\hline \\ -1. If $b \le 0$ then do \\ -\hspace{3mm}1.1 $c \leftarrow 0$ (\textit{mp\_zero}) \\ -\hspace{3mm}1.2 Return(\textit{MP\_OKAY}). \\ -2. If $b > a.used \cdot lg(\beta)$ then do \\ -\hspace{3mm}2.1 $c \leftarrow a$ (\textit{mp\_copy}) \\ -\hspace{3mm}2.2 Return the result of step 2.1. \\ -3. $c \leftarrow a$ \\ -4. If step 3 failed return(\textit{MP\_MEM}). \\ -5. for $n$ from $\lceil b / lg(\beta) \rceil$ to $c.used$ do \\ -\hspace{3mm}5.1 $c_n \leftarrow 0$ \\ -6. $k \leftarrow b \mbox{ (mod }lg(\beta)\mbox{)}$ \\ -7. $c_{\lfloor b / lg(\beta) \rfloor} \leftarrow c_{\lfloor b / lg(\beta) \rfloor} \mbox{ (mod }2^{k}\mbox{)}$. \\ -8. Clamp excess digits of $c$. (\textit{mp\_clamp}) \\ -9. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_mod\_2d} -\end{figure} - -\textbf{Algorithm mp\_mod\_2d.} -This algorithm will quickly calculate the value of $a \mbox{ (mod }2^b\mbox{)}$. First if $b$ is less than or equal to zero the -result is set to zero. If $b$ is greater than the number of bits in $a$ then it simply copies $a$ to $c$ and returns. Otherwise, $a$ -is copied to $b$, leading digits are removed and the remaining leading digit is trimed to the exact bit count. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_mod\_2d.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* calc a value mod 2**b */ -018 int -019 mp_mod_2d (mp_int * a, int b, mp_int * c) -020 \{ -021 int x, res; -022 -023 /* if b is <= 0 then zero the int */ -024 if (b <= 0) \{ -025 mp_zero (c); -026 return MP_OKAY; -027 \} -028 -029 /* if the modulus is larger than the value than return */ -030 if (b >= (int) (a->used * DIGIT_BIT)) \{ -031 res = mp_copy (a, c); -032 return res; -033 \} -034 -035 /* copy */ -036 if ((res = mp_copy (a, c)) != MP_OKAY) \{ -037 return res; -038 \} -039 -040 /* zero digits above the last digit of the modulus */ -041 for (x = (b / DIGIT_BIT) + (((b % DIGIT_BIT) == 0) ? 0 : 1); x < c->used; - x++) \{ -042 c->dp[x] = 0; -043 \} -044 /* clear the digit that is not completely outside/inside the modulus */ -045 c->dp[b / DIGIT_BIT] &= -046 (mp_digit) ((((mp_digit) 1) << (((mp_digit) b) % DIGIT_BIT)) - ((mp_digi - t) 1)); -047 mp_clamp (c); -048 return MP_OKAY; -049 \} -050 #endif -051 -\end{alltt} -\end{small} - -We first avoid cases of $b \le 0$ by simply mp\_zero()'ing the destination in such cases. Next if $2^b$ is larger -than the input we just mp\_copy() the input and return right away. After this point we know we must actually -perform some work to produce the remainder. - -Recalling that reducing modulo $2^k$ and a binary ``and'' with $2^k - 1$ are numerically equivalent we can quickly reduce -the number. First we zero any digits above the last digit in $2^b$ (line 41). Next we reduce the -leading digit of both (line 45) and then mp\_clamp(). - -\section*{Exercises} -\begin{tabular}{cl} -$\left [ 3 \right ] $ & Devise an algorithm that performs $a \cdot 2^b$ for generic values of $b$ \\ - & in $O(n)$ time. \\ - &\\ -$\left [ 3 \right ] $ & Devise an efficient algorithm to multiply by small low hamming \\ - & weight values such as $3$, $5$ and $9$. Extend it to handle all values \\ - & upto $64$ with a hamming weight less than three. \\ - &\\ -$\left [ 2 \right ] $ & Modify the preceding algorithm to handle values of the form \\ - & $2^k - 1$ as well. \\ - &\\ -$\left [ 3 \right ] $ & Using only algorithms mp\_mul\_2, mp\_div\_2 and mp\_add create an \\ - & algorithm to multiply two integers in roughly $O(2n^2)$ time for \\ - & any $n$-bit input. Note that the time of addition is ignored in the \\ - & calculation. \\ - & \\ -$\left [ 5 \right ] $ & Improve the previous algorithm to have a working time of at most \\ - & $O \left (2^{(k-1)}n + \left ({2n^2 \over k} \right ) \right )$ for an appropriate choice of $k$. Again ignore \\ - & the cost of addition. \\ - & \\ -$\left [ 2 \right ] $ & Devise a chart to find optimal values of $k$ for the previous problem \\ - & for $n = 64 \ldots 1024$ in steps of $64$. \\ - & \\ -$\left [ 2 \right ] $ & Using only algorithms mp\_abs and mp\_sub devise another method for \\ - & calculating the result of a signed comparison. \\ - & -\end{tabular} - -\chapter{Multiplication and Squaring} -\section{The Multipliers} -For most number theoretic problems including certain public key cryptographic algorithms, the ``multipliers'' form the most important subset of -algorithms of any multiple precision integer package. The set of multiplier algorithms include integer multiplication, squaring and modular reduction -where in each of the algorithms single precision multiplication is the dominant operation performed. This chapter will discuss integer multiplication -and squaring, leaving modular reductions for the subsequent chapter. - -The importance of the multiplier algorithms is for the most part driven by the fact that certain popular public key algorithms are based on modular -exponentiation, that is computing $d \equiv a^b \mbox{ (mod }c\mbox{)}$ for some arbitrary choice of $a$, $b$, $c$ and $d$. During a modular -exponentiation the majority\footnote{Roughly speaking a modular exponentiation will spend about 40\% of the time performing modular reductions, -35\% of the time performing squaring and 25\% of the time performing multiplications.} of the processor time is spent performing single precision -multiplications. - -For centuries general purpose multiplication has required a lengthly $O(n^2)$ process, whereby each digit of one multiplicand has to be multiplied -against every digit of the other multiplicand. Traditional long-hand multiplication is based on this process; while the techniques can differ the -overall algorithm used is essentially the same. Only ``recently'' have faster algorithms been studied. First Karatsuba multiplication was discovered in -1962. This algorithm can multiply two numbers with considerably fewer single precision multiplications when compared to the long-hand approach. -This technique led to the discovery of polynomial basis algorithms (\textit{good reference?}) and subquently Fourier Transform based solutions. - -\section{Multiplication} -\subsection{The Baseline Multiplication} -\label{sec:basemult} -\index{baseline multiplication} -Computing the product of two integers in software can be achieved using a trivial adaptation of the standard $O(n^2)$ long-hand multiplication -algorithm that school children are taught. The algorithm is considered an $O(n^2)$ algorithm since for two $n$-digit inputs $n^2$ single precision -multiplications are required. More specifically for a $m$ and $n$ digit input $m \cdot n$ single precision multiplications are required. To -simplify most discussions, it will be assumed that the inputs have comparable number of digits. - -The ``baseline multiplication'' algorithm is designed to act as the ``catch-all'' algorithm, only to be used when the faster algorithms cannot be -used. This algorithm does not use any particularly interesting optimizations and should ideally be avoided if possible. One important -facet of this algorithm, is that it has been modified to only produce a certain amount of output digits as resolution. The importance of this -modification will become evident during the discussion of Barrett modular reduction. Recall that for a $n$ and $m$ digit input the product -will be at most $n + m$ digits. Therefore, this algorithm can be reduced to a full multiplier by having it produce $n + m$ digits of the product. - -Recall from sub-section 4.2.2 the definition of $\gamma$ as the number of bits in the type \textbf{mp\_digit}. We shall now extend the variable set to -include $\alpha$ which shall represent the number of bits in the type \textbf{mp\_word}. This implies that $2^{\alpha} > 2 \cdot \beta^2$. The -constant $\delta = 2^{\alpha - 2lg(\beta)}$ will represent the maximal weight of any column in a product (\textit{see sub-section 5.2.2 for more information}). - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{s\_mp\_mul\_digs}. \\ -\textbf{Input}. mp\_int $a$, mp\_int $b$ and an integer $digs$ \\ -\textbf{Output}. $c \leftarrow \vert a \vert \cdot \vert b \vert \mbox{ (mod }\beta^{digs}\mbox{)}$. \\ -\hline \\ -1. If min$(a.used, b.used) < \delta$ then do \\ -\hspace{3mm}1.1 Calculate $c = \vert a \vert \cdot \vert b \vert$ by the Comba method (\textit{see algorithm~\ref{fig:COMBAMULT}}). \\ -\hspace{3mm}1.2 Return the result of step 1.1 \\ -\\ -Allocate and initialize a temporary mp\_int. \\ -2. Init $t$ to be of size $digs$ \\ -3. If step 2 failed return(\textit{MP\_MEM}). \\ -4. $t.used \leftarrow digs$ \\ -\\ -Compute the product. \\ -5. for $ix$ from $0$ to $a.used - 1$ do \\ -\hspace{3mm}5.1 $u \leftarrow 0$ \\ -\hspace{3mm}5.2 $pb \leftarrow \mbox{min}(b.used, digs - ix)$ \\ -\hspace{3mm}5.3 If $pb < 1$ then goto step 6. \\ -\hspace{3mm}5.4 for $iy$ from $0$ to $pb - 1$ do \\ -\hspace{6mm}5.4.1 $\hat r \leftarrow t_{iy + ix} + a_{ix} \cdot b_{iy} + u$ \\ -\hspace{6mm}5.4.2 $t_{iy + ix} \leftarrow \hat r \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{6mm}5.4.3 $u \leftarrow \lfloor \hat r / \beta \rfloor$ \\ -\hspace{3mm}5.5 if $ix + pb < digs$ then do \\ -\hspace{6mm}5.5.1 $t_{ix + pb} \leftarrow u$ \\ -6. Clamp excess digits of $t$. \\ -7. Swap $c$ with $t$ \\ -8. Clear $t$ \\ -9. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm s\_mp\_mul\_digs} -\end{figure} - -\textbf{Algorithm s\_mp\_mul\_digs.} -This algorithm computes the unsigned product of two inputs $a$ and $b$, limited to an output precision of $digs$ digits. While it may seem -a bit awkward to modify the function from its simple $O(n^2)$ description, the usefulness of partial multipliers will arise in a subsequent -algorithm. The algorithm is loosely based on algorithm 14.12 from \cite[pp. 595]{HAC} and is similar to Algorithm M of Knuth \cite[pp. 268]{TAOCPV2}. -Algorithm s\_mp\_mul\_digs differs from these cited references since it can produce a variable output precision regardless of the precision of the -inputs. - -The first thing this algorithm checks for is whether a Comba multiplier can be used instead. If the minimum digit count of either -input is less than $\delta$, then the Comba method may be used instead. After the Comba method is ruled out, the baseline algorithm begins. A -temporary mp\_int variable $t$ is used to hold the intermediate result of the product. This allows the algorithm to be used to -compute products when either $a = c$ or $b = c$ without overwriting the inputs. - -All of step 5 is the infamous $O(n^2)$ multiplication loop slightly modified to only produce upto $digs$ digits of output. The $pb$ variable -is given the count of digits to read from $b$ inside the nested loop. If $pb \le 1$ then no more output digits can be produced and the algorithm -will exit the loop. The best way to think of the loops are as a series of $pb \times 1$ multiplications. That is, in each pass of the -innermost loop $a_{ix}$ is multiplied against $b$ and the result is added (\textit{with an appropriate shift}) to $t$. - -For example, consider multiplying $576$ by $241$. That is equivalent to computing $10^0(1)(576) + 10^1(4)(576) + 10^2(2)(576)$ which is best -visualized in the following table. - -\begin{figure}[here] -\begin{center} -\begin{tabular}{|c|c|c|c|c|c|l|} -\hline && & 5 & 7 & 6 & \\ -\hline $\times$&& & 2 & 4 & 1 & \\ -\hline &&&&&&\\ - && & 5 & 7 & 6 & $10^0(1)(576)$ \\ - &2 & 3 & 6 & 1 & 6 & $10^1(4)(576) + 10^0(1)(576)$ \\ - 1 & 3 & 8 & 8 & 1 & 6 & $10^2(2)(576) + 10^1(4)(576) + 10^0(1)(576)$ \\ -\hline -\end{tabular} -\end{center} -\caption{Long-Hand Multiplication Diagram} -\end{figure} - -Each row of the product is added to the result after being shifted to the left (\textit{multiplied by a power of the radix}) by the appropriate -count. That is in pass $ix$ of the inner loop the product is added starting at the $ix$'th digit of the reult. - -Step 5.4.1 introduces the hat symbol (\textit{e.g. $\hat r$}) which represents a double precision variable. The multiplication on that step -is assumed to be a double wide output single precision multiplication. That is, two single precision variables are multiplied to produce a -double precision result. The step is somewhat optimized from a long-hand multiplication algorithm because the carry from the addition in step -5.4.1 is propagated through the nested loop. If the carry was not propagated immediately it would overflow the single precision digit -$t_{ix+iy}$ and the result would be lost. - -At step 5.5 the nested loop is finished and any carry that was left over should be forwarded. The carry does not have to be added to the $ix+pb$'th -digit since that digit is assumed to be zero at this point. However, if $ix + pb \ge digs$ the carry is not set as it would make the result -exceed the precision requested. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_s\_mp\_mul\_digs.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* multiplies |a| * |b| and only computes upto digs digits of result -018 * HAC pp. 595, Algorithm 14.12 Modified so you can control how -019 * many digits of output are created. -020 */ -021 int s_mp_mul_digs (mp_int * a, mp_int * b, mp_int * c, int digs) -022 \{ -023 mp_int t; -024 int res, pa, pb, ix, iy; -025 mp_digit u; -026 mp_word r; -027 mp_digit tmpx, *tmpt, *tmpy; -028 -029 /* can we use the fast multiplier? */ -030 if (((digs) < MP_WARRAY) && -031 (MIN (a->used, b->used) < -032 (1 << ((CHAR_BIT * sizeof(mp_word)) - (2 * DIGIT_BIT))))) \{ -033 return fast_s_mp_mul_digs (a, b, c, digs); -034 \} -035 -036 if ((res = mp_init_size (&t, digs)) != MP_OKAY) \{ -037 return res; -038 \} -039 t.used = digs; -040 -041 /* compute the digits of the product directly */ -042 pa = a->used; -043 for (ix = 0; ix < pa; ix++) \{ -044 /* set the carry to zero */ -045 u = 0; -046 -047 /* limit ourselves to making digs digits of output */ -048 pb = MIN (b->used, digs - ix); -049 -050 /* setup some aliases */ -051 /* copy of the digit from a used within the nested loop */ -052 tmpx = a->dp[ix]; -053 -054 /* an alias for the destination shifted ix places */ -055 tmpt = t.dp + ix; -056 -057 /* an alias for the digits of b */ -058 tmpy = b->dp; -059 -060 /* compute the columns of the output and propagate the carry */ -061 for (iy = 0; iy < pb; iy++) \{ -062 /* compute the column as a mp_word */ -063 r = (mp_word)*tmpt + -064 ((mp_word)tmpx * (mp_word)*tmpy++) + -065 (mp_word)u; -066 -067 /* the new column is the lower part of the result */ -068 *tmpt++ = (mp_digit) (r & ((mp_word) MP_MASK)); -069 -070 /* get the carry word from the result */ -071 u = (mp_digit) (r >> ((mp_word) DIGIT_BIT)); -072 \} -073 /* set carry if it is placed below digs */ -074 if ((ix + iy) < digs) \{ -075 *tmpt = u; -076 \} -077 \} -078 -079 mp_clamp (&t); -080 mp_exch (&t, c); -081 -082 mp_clear (&t); -083 return MP_OKAY; -084 \} -085 #endif -086 -\end{alltt} -\end{small} - -First we determine (line 30) if the Comba method can be used first since it's faster. The conditions for -sing the Comba routine are that min$(a.used, b.used) < \delta$ and the number of digits of output is less than -\textbf{MP\_WARRAY}. This new constant is used to control the stack usage in the Comba routines. By default it is -set to $\delta$ but can be reduced when memory is at a premium. - -If we cannot use the Comba method we proceed to setup the baseline routine. We allocate the the destination mp\_int -$t$ (line 36) to the exact size of the output to avoid further re--allocations. At this point we now -begin the $O(n^2)$ loop. - -This implementation of multiplication has the caveat that it can be trimmed to only produce a variable number of -digits as output. In each iteration of the outer loop the $pb$ variable is set (line 48) to the maximum -number of inner loop iterations. - -Inside the inner loop we calculate $\hat r$ as the mp\_word product of the two mp\_digits and the addition of the -carry from the previous iteration. A particularly important observation is that most modern optimizing -C compilers (GCC for instance) can recognize that a $N \times N \rightarrow 2N$ multiplication is all that -is required for the product. In x86 terms for example, this means using the MUL instruction. - -Each digit of the product is stored in turn (line 68) and the carry propagated (line 71) to the -next iteration. - -\subsection{Faster Multiplication by the ``Comba'' Method} - -One of the huge drawbacks of the ``baseline'' algorithms is that at the $O(n^2)$ level the carry must be -computed and propagated upwards. This makes the nested loop very sequential and hard to unroll and implement -in parallel. The ``Comba'' \cite{COMBA} method is named after little known (\textit{in cryptographic venues}) Paul G. -Comba who described a method of implementing fast multipliers that do not require nested carry fixup operations. As an -interesting aside it seems that Paul Barrett describes a similar technique in his 1986 paper \cite{BARRETT} written -five years before. - -At the heart of the Comba technique is once again the long-hand algorithm. Except in this case a slight -twist is placed on how the columns of the result are produced. In the standard long-hand algorithm rows of products -are produced then added together to form the final result. In the baseline algorithm the columns are added together -after each iteration to get the result instantaneously. - -In the Comba algorithm the columns of the result are produced entirely independently of each other. That is at -the $O(n^2)$ level a simple multiplication and addition step is performed. The carries of the columns are propagated -after the nested loop to reduce the amount of work requiored. Succintly the first step of the algorithm is to compute -the product vector $\vec x$ as follows. - -\begin{equation} -\vec x_n = \sum_{i+j = n} a_ib_j, \forall n \in \lbrace 0, 1, 2, \ldots, i + j \rbrace -\end{equation} - -Where $\vec x_n$ is the $n'th$ column of the output vector. Consider the following example which computes the vector $\vec x$ for the multiplication -of $576$ and $241$. - -\newpage\begin{figure}[here] -\begin{small} -\begin{center} -\begin{tabular}{|c|c|c|c|c|c|} - \hline & & 5 & 7 & 6 & First Input\\ - \hline $\times$ & & 2 & 4 & 1 & Second Input\\ -\hline & & $1 \cdot 5 = 5$ & $1 \cdot 7 = 7$ & $1 \cdot 6 = 6$ & First pass \\ - & $4 \cdot 5 = 20$ & $4 \cdot 7+5=33$ & $4 \cdot 6+7=31$ & 6 & Second pass \\ - $2 \cdot 5 = 10$ & $2 \cdot 7 + 20 = 34$ & $2 \cdot 6+33=45$ & 31 & 6 & Third pass \\ -\hline 10 & 34 & 45 & 31 & 6 & Final Result \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Comba Multiplication Diagram} -\end{figure} - -At this point the vector $x = \left < 10, 34, 45, 31, 6 \right >$ is the result of the first step of the Comba multipler. -Now the columns must be fixed by propagating the carry upwards. The resultant vector will have one extra dimension over the input vector which is -congruent to adding a leading zero digit. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{Comba Fixup}. \\ -\textbf{Input}. Vector $\vec x$ of dimension $k$ \\ -\textbf{Output}. Vector $\vec x$ such that the carries have been propagated. \\ -\hline \\ -1. for $n$ from $0$ to $k - 1$ do \\ -\hspace{3mm}1.1 $\vec x_{n+1} \leftarrow \vec x_{n+1} + \lfloor \vec x_{n}/\beta \rfloor$ \\ -\hspace{3mm}1.2 $\vec x_{n} \leftarrow \vec x_{n} \mbox{ (mod }\beta\mbox{)}$ \\ -2. Return($\vec x$). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm Comba Fixup} -\end{figure} - -With that algorithm and $k = 5$ and $\beta = 10$ the following vector is produced $\vec x= \left < 1, 3, 8, 8, 1, 6 \right >$. In this case -$241 \cdot 576$ is in fact $138816$ and the procedure succeeded. If the algorithm is correct and as will be demonstrated shortly more -efficient than the baseline algorithm why not simply always use this algorithm? - -\subsubsection{Column Weight.} -At the nested $O(n^2)$ level the Comba method adds the product of two single precision variables to each column of the output -independently. A serious obstacle is if the carry is lost, due to lack of precision before the algorithm has a chance to fix -the carries. For example, in the multiplication of two three-digit numbers the third column of output will be the sum of -three single precision multiplications. If the precision of the accumulator for the output digits is less then $3 \cdot (\beta - 1)^2$ then -an overflow can occur and the carry information will be lost. For any $m$ and $n$ digit inputs the maximum weight of any column is -min$(m, n)$ which is fairly obvious. - -The maximum number of terms in any column of a product is known as the ``column weight'' and strictly governs when the algorithm can be used. Recall -from earlier that a double precision type has $\alpha$ bits of resolution and a single precision digit has $lg(\beta)$ bits of precision. Given these -two quantities we must not violate the following - -\begin{equation} -k \cdot \left (\beta - 1 \right )^2 < 2^{\alpha} -\end{equation} - -Which reduces to - -\begin{equation} -k \cdot \left ( \beta^2 - 2\beta + 1 \right ) < 2^{\alpha} -\end{equation} - -Let $\rho = lg(\beta)$ represent the number of bits in a single precision digit. By further re-arrangement of the equation the final solution is -found. - -\begin{equation} -k < {{2^{\alpha}} \over {\left (2^{2\rho} - 2^{\rho + 1} + 1 \right )}} -\end{equation} - -The defaults for LibTomMath are $\beta = 2^{28}$ and $\alpha = 2^{64}$ which means that $k$ is bounded by $k < 257$. In this configuration -the smaller input may not have more than $256$ digits if the Comba method is to be used. This is quite satisfactory for most applications since -$256$ digits would allow for numbers in the range of $0 \le x < 2^{7168}$ which, is much larger than most public key cryptographic algorithms require. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{fast\_s\_mp\_mul\_digs}. \\ -\textbf{Input}. mp\_int $a$, mp\_int $b$ and an integer $digs$ \\ -\textbf{Output}. $c \leftarrow \vert a \vert \cdot \vert b \vert \mbox{ (mod }\beta^{digs}\mbox{)}$. \\ -\hline \\ -Place an array of \textbf{MP\_WARRAY} single precision digits named $W$ on the stack. \\ -1. If $c.alloc < digs$ then grow $c$ to $digs$ digits. (\textit{mp\_grow}) \\ -2. If step 1 failed return(\textit{MP\_MEM}).\\ -\\ -3. $pa \leftarrow \mbox{MIN}(digs, a.used + b.used)$ \\ -\\ -4. $\_ \hat W \leftarrow 0$ \\ -5. for $ix$ from 0 to $pa - 1$ do \\ -\hspace{3mm}5.1 $ty \leftarrow \mbox{MIN}(b.used - 1, ix)$ \\ -\hspace{3mm}5.2 $tx \leftarrow ix - ty$ \\ -\hspace{3mm}5.3 $iy \leftarrow \mbox{MIN}(a.used - tx, ty + 1)$ \\ -\hspace{3mm}5.4 for $iz$ from 0 to $iy - 1$ do \\ -\hspace{6mm}5.4.1 $\_ \hat W \leftarrow \_ \hat W + a_{tx+iy}b_{ty-iy}$ \\ -\hspace{3mm}5.5 $W_{ix} \leftarrow \_ \hat W (\mbox{mod }\beta)$\\ -\hspace{3mm}5.6 $\_ \hat W \leftarrow \lfloor \_ \hat W / \beta \rfloor$ \\ -\\ -6. $oldused \leftarrow c.used$ \\ -7. $c.used \leftarrow digs$ \\ -8. for $ix$ from $0$ to $pa$ do \\ -\hspace{3mm}8.1 $c_{ix} \leftarrow W_{ix}$ \\ -9. for $ix$ from $pa + 1$ to $oldused - 1$ do \\ -\hspace{3mm}9.1 $c_{ix} \leftarrow 0$ \\ -\\ -10. Clamp $c$. \\ -11. Return MP\_OKAY. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm fast\_s\_mp\_mul\_digs} -\label{fig:COMBAMULT} -\end{figure} - -\textbf{Algorithm fast\_s\_mp\_mul\_digs.} -This algorithm performs the unsigned multiplication of $a$ and $b$ using the Comba method limited to $digs$ digits of precision. - -The outer loop of this algorithm is more complicated than that of the baseline multiplier. This is because on the inside of the -loop we want to produce one column per pass. This allows the accumulator $\_ \hat W$ to be placed in CPU registers and -reduce the memory bandwidth to two \textbf{mp\_digit} reads per iteration. - -The $ty$ variable is set to the minimum count of $ix$ or the number of digits in $b$. That way if $a$ has more digits than -$b$ this will be limited to $b.used - 1$. The $tx$ variable is set to the to the distance past $b.used$ the variable -$ix$ is. This is used for the immediately subsequent statement where we find $iy$. - -The variable $iy$ is the minimum digits we can read from either $a$ or $b$ before running out. Computing one column at a time -means we have to scan one integer upwards and the other downwards. $a$ starts at $tx$ and $b$ starts at $ty$. In each -pass we are producing the $ix$'th output column and we note that $tx + ty = ix$. As we move $tx$ upwards we have to -move $ty$ downards so the equality remains valid. The $iy$ variable is the number of iterations until -$tx \ge a.used$ or $ty < 0$ occurs. - -After every inner pass we store the lower half of the accumulator into $W_{ix}$ and then propagate the carry of the accumulator -into the next round by dividing $\_ \hat W$ by $\beta$. - -To measure the benefits of the Comba method over the baseline method consider the number of operations that are required. If the -cost in terms of time of a multiply and addition is $p$ and the cost of a carry propagation is $q$ then a baseline multiplication would require -$O \left ((p + q)n^2 \right )$ time to multiply two $n$-digit numbers. The Comba method requires only $O(pn^2 + qn)$ time, however in practice, -the speed increase is actually much more. With $O(n)$ space the algorithm can be reduced to $O(pn + qn)$ time by implementing the $n$ multiply -and addition operations in the nested loop in parallel. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_fast\_s\_mp\_mul\_digs.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* Fast (comba) multiplier -018 * -019 * This is the fast column-array [comba] multiplier. It is -020 * designed to compute the columns of the product first -021 * then handle the carries afterwards. This has the effect -022 * of making the nested loops that compute the columns very -023 * simple and schedulable on super-scalar processors. -024 * -025 * This has been modified to produce a variable number of -026 * digits of output so if say only a half-product is required -027 * you don't have to compute the upper half (a feature -028 * required for fast Barrett reduction). -029 * -030 * Based on Algorithm 14.12 on pp.595 of HAC. -031 * -032 */ -033 int fast_s_mp_mul_digs (mp_int * a, mp_int * b, mp_int * c, int digs) -034 \{ -035 int olduse, res, pa, ix, iz; -036 mp_digit W[MP_WARRAY]; -037 mp_word _W; -038 -039 /* grow the destination as required */ -040 if (c->alloc < digs) \{ -041 if ((res = mp_grow (c, digs)) != MP_OKAY) \{ -042 return res; -043 \} -044 \} -045 -046 /* number of output digits to produce */ -047 pa = MIN(digs, a->used + b->used); -048 -049 /* clear the carry */ -050 _W = 0; -051 for (ix = 0; ix < pa; ix++) \{ -052 int tx, ty; -053 int iy; -054 mp_digit *tmpx, *tmpy; -055 -056 /* get offsets into the two bignums */ -057 ty = MIN(b->used-1, ix); -058 tx = ix - ty; -059 -060 /* setup temp aliases */ -061 tmpx = a->dp + tx; -062 tmpy = b->dp + ty; -063 -064 /* this is the number of times the loop will iterrate, essentially -065 while (tx++ < a->used && ty-- >= 0) \{ ... \} -066 */ -067 iy = MIN(a->used-tx, ty+1); -068 -069 /* execute loop */ -070 for (iz = 0; iz < iy; ++iz) \{ -071 _W += ((mp_word)*tmpx++)*((mp_word)*tmpy--); -072 -073 \} -074 -075 /* store term */ -076 W[ix] = ((mp_digit)_W) & MP_MASK; -077 -078 /* make next carry */ -079 _W = _W >> ((mp_word)DIGIT_BIT); -080 \} -081 -082 /* setup dest */ -083 olduse = c->used; -084 c->used = pa; -085 -086 \{ -087 mp_digit *tmpc; -088 tmpc = c->dp; -089 for (ix = 0; ix < (pa + 1); ix++) \{ -090 /* now extract the previous digit [below the carry] */ -091 *tmpc++ = W[ix]; -092 \} -093 -094 /* clear unused digits [that existed in the old copy of c] */ -095 for (; ix < olduse; ix++) \{ -096 *tmpc++ = 0; -097 \} -098 \} -099 mp_clamp (c); -100 return MP_OKAY; -101 \} -102 #endif -103 -\end{alltt} -\end{small} - -As per the pseudo--code we first calculate $pa$ (line 47) as the number of digits to output. Next we begin the outer loop -to produce the individual columns of the product. We use the two aliases $tmpx$ and $tmpy$ (lines 61, 62) to point -inside the two multiplicands quickly. - -The inner loop (lines 70 to 73) of this implementation is where the tradeoff come into play. Originally this comba -implementation was ``row--major'' which means it adds to each of the columns in each pass. After the outer loop it would then fix -the carries. This was very fast except it had an annoying drawback. You had to read a mp\_word and two mp\_digits and write -one mp\_word per iteration. On processors such as the Athlon XP and P4 this did not matter much since the cache bandwidth -is very high and it can keep the ALU fed with data. It did, however, matter on older and embedded cpus where cache is often -slower and also often doesn't exist. This new algorithm only performs two reads per iteration under the assumption that the -compiler has aliased $\_ \hat W$ to a CPU register. - -After the inner loop we store the current accumulator in $W$ and shift $\_ \hat W$ (lines 76, 79) to forward it as -a carry for the next pass. After the outer loop we use the final carry (line 76) as the last digit of the product. - -\subsection{Polynomial Basis Multiplication} -To break the $O(n^2)$ barrier in multiplication requires a completely different look at integer multiplication. In the following algorithms -the use of polynomial basis representation for two integers $a$ and $b$ as $f(x) = \sum_{i=0}^{n} a_i x^i$ and -$g(x) = \sum_{i=0}^{n} b_i x^i$ respectively, is required. In this system both $f(x)$ and $g(x)$ have $n + 1$ terms and are of the $n$'th degree. - -The product $a \cdot b \equiv f(x)g(x)$ is the polynomial $W(x) = \sum_{i=0}^{2n} w_i x^i$. The coefficients $w_i$ will -directly yield the desired product when $\beta$ is substituted for $x$. The direct solution to solve for the $2n + 1$ coefficients -requires $O(n^2)$ time and would in practice be slower than the Comba technique. - -However, numerical analysis theory indicates that only $2n + 1$ distinct points in $W(x)$ are required to determine the values of the $2n + 1$ unknown -coefficients. This means by finding $\zeta_y = W(y)$ for $2n + 1$ small values of $y$ the coefficients of $W(x)$ can be found with -Gaussian elimination. This technique is also occasionally refered to as the \textit{interpolation technique} (\textit{references please...}) since in -effect an interpolation based on $2n + 1$ points will yield a polynomial equivalent to $W(x)$. - -The coefficients of the polynomial $W(x)$ are unknown which makes finding $W(y)$ for any value of $y$ impossible. However, since -$W(x) = f(x)g(x)$ the equivalent $\zeta_y = f(y) g(y)$ can be used in its place. The benefit of this technique stems from the -fact that $f(y)$ and $g(y)$ are much smaller than either $a$ or $b$ respectively. As a result finding the $2n + 1$ relations required -by multiplying $f(y)g(y)$ involves multiplying integers that are much smaller than either of the inputs. - -When picking points to gather relations there are always three obvious points to choose, $y = 0, 1$ and $ \infty$. The $\zeta_0$ term -is simply the product $W(0) = w_0 = a_0 \cdot b_0$. The $\zeta_1$ term is the product -$W(1) = \left (\sum_{i = 0}^{n} a_i \right ) \left (\sum_{i = 0}^{n} b_i \right )$. The third point $\zeta_{\infty}$ is less obvious but rather -simple to explain. The $2n + 1$'th coefficient of $W(x)$ is numerically equivalent to the most significant column in an integer multiplication. -The point at $\infty$ is used symbolically to represent the most significant column, that is $W(\infty) = w_{2n} = a_nb_n$. Note that the -points at $y = 0$ and $\infty$ yield the coefficients $w_0$ and $w_{2n}$ directly. - -If more points are required they should be of small values and powers of two such as $2^q$ and the related \textit{mirror points} -$\left (2^q \right )^{2n} \cdot \zeta_{2^{-q}}$ for small values of $q$. The term ``mirror point'' stems from the fact that -$\left (2^q \right )^{2n} \cdot \zeta_{2^{-q}}$ can be calculated in the exact opposite fashion as $\zeta_{2^q}$. For -example, when $n = 2$ and $q = 1$ then following two equations are equivalent to the point $\zeta_{2}$ and its mirror. - -\begin{eqnarray} -\zeta_{2} = f(2)g(2) = (4a_2 + 2a_1 + a_0)(4b_2 + 2b_1 + b_0) \nonumber \\ -16 \cdot \zeta_{1 \over 2} = 4f({1\over 2}) \cdot 4g({1 \over 2}) = (a_2 + 2a_1 + 4a_0)(b_2 + 2b_1 + 4b_0) -\end{eqnarray} - -Using such points will allow the values of $f(y)$ and $g(y)$ to be independently calculated using only left shifts. For example, when $n = 2$ the -polynomial $f(2^q)$ is equal to $2^q((2^qa_2) + a_1) + a_0$. This technique of polynomial representation is known as Horner's method. - -As a general rule of the algorithm when the inputs are split into $n$ parts each there are $2n - 1$ multiplications. Each multiplication is of -multiplicands that have $n$ times fewer digits than the inputs. The asymptotic running time of this algorithm is -$O \left ( k^{lg_n(2n - 1)} \right )$ for $k$ digit inputs (\textit{assuming they have the same number of digits}). Figure~\ref{fig:exponent} -summarizes the exponents for various values of $n$. - -\begin{figure} -\begin{center} -\begin{tabular}{|c|c|c|} -\hline \textbf{Split into $n$ Parts} & \textbf{Exponent} & \textbf{Notes}\\ -\hline $2$ & $1.584962501$ & This is Karatsuba Multiplication. \\ -\hline $3$ & $1.464973520$ & This is Toom-Cook Multiplication. \\ -\hline $4$ & $1.403677461$ &\\ -\hline $5$ & $1.365212389$ &\\ -\hline $10$ & $1.278753601$ &\\ -\hline $100$ & $1.149426538$ &\\ -\hline $1000$ & $1.100270931$ &\\ -\hline $10000$ & $1.075252070$ &\\ -\hline -\end{tabular} -\end{center} -\caption{Asymptotic Running Time of Polynomial Basis Multiplication} -\label{fig:exponent} -\end{figure} - -At first it may seem like a good idea to choose $n = 1000$ since the exponent is approximately $1.1$. However, the overhead -of solving for the 2001 terms of $W(x)$ will certainly consume any savings the algorithm could offer for all but exceedingly large -numbers. - -\subsubsection{Cutoff Point} -The polynomial basis multiplication algorithms all require fewer single precision multiplications than a straight Comba approach. However, -the algorithms incur an overhead (\textit{at the $O(n)$ work level}) since they require a system of equations to be solved. This makes the -polynomial basis approach more costly to use with small inputs. - -Let $m$ represent the number of digits in the multiplicands (\textit{assume both multiplicands have the same number of digits}). There exists a -point $y$ such that when $m < y$ the polynomial basis algorithms are more costly than Comba, when $m = y$ they are roughly the same cost and -when $m > y$ the Comba methods are slower than the polynomial basis algorithms. - -The exact location of $y$ depends on several key architectural elements of the computer platform in question. - -\begin{enumerate} -\item The ratio of clock cycles for single precision multiplication versus other simpler operations such as addition, shifting, etc. For example -on the AMD Athlon the ratio is roughly $17 : 1$ while on the Intel P4 it is $29 : 1$. The higher the ratio in favour of multiplication the lower -the cutoff point $y$ will be. - -\item The complexity of the linear system of equations (\textit{for the coefficients of $W(x)$}) is. Generally speaking as the number of splits -grows the complexity grows substantially. Ideally solving the system will only involve addition, subtraction and shifting of integers. This -directly reflects on the ratio previous mentioned. - -\item To a lesser extent memory bandwidth and function call overheads. Provided the values are in the processor cache this is less of an -influence over the cutoff point. - -\end{enumerate} - -A clean cutoff point separation occurs when a point $y$ is found such that all of the cutoff point conditions are met. For example, if the point -is too low then there will be values of $m$ such that $m > y$ and the Comba method is still faster. Finding the cutoff points is fairly simple when -a high resolution timer is available. - -\subsection{Karatsuba Multiplication} -Karatsuba \cite{KARA} multiplication when originally proposed in 1962 was among the first set of algorithms to break the $O(n^2)$ barrier for -general purpose multiplication. Given two polynomial basis representations $f(x) = ax + b$ and $g(x) = cx + d$, Karatsuba proved with -light algebra \cite{KARAP} that the following polynomial is equivalent to multiplication of the two integers the polynomials represent. - -\begin{equation} -f(x) \cdot g(x) = acx^2 + ((a + b)(c + d) - (ac + bd))x + bd -\end{equation} - -Using the observation that $ac$ and $bd$ could be re-used only three half sized multiplications would be required to produce the product. Applying -this algorithm recursively, the work factor becomes $O(n^{lg(3)})$ which is substantially better than the work factor $O(n^2)$ of the Comba technique. It turns -out what Karatsuba did not know or at least did not publish was that this is simply polynomial basis multiplication with the points -$\zeta_0$, $\zeta_{\infty}$ and $\zeta_{1}$. Consider the resultant system of equations. - -\begin{center} -\begin{tabular}{rcrcrcrc} -$\zeta_{0}$ & $=$ & & & & & $w_0$ \\ -$\zeta_{1}$ & $=$ & $w_2$ & $+$ & $w_1$ & $+$ & $w_0$ \\ -$\zeta_{\infty}$ & $=$ & $w_2$ & & & & \\ -\end{tabular} -\end{center} - -By adding the first and last equation to the equation in the middle the term $w_1$ can be isolated and all three coefficients solved for. The simplicity -of this system of equations has made Karatsuba fairly popular. In fact the cutoff point is often fairly low\footnote{With LibTomMath 0.18 it is 70 and 109 digits for the Intel P4 and AMD Athlon respectively.} -making it an ideal algorithm to speed up certain public key cryptosystems such as RSA and Diffie-Hellman. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_karatsuba\_mul}. \\ -\textbf{Input}. mp\_int $a$ and mp\_int $b$ \\ -\textbf{Output}. $c \leftarrow \vert a \vert \cdot \vert b \vert$ \\ -\hline \\ -1. Init the following mp\_int variables: $x0$, $x1$, $y0$, $y1$, $t1$, $x0y0$, $x1y1$.\\ -2. If step 2 failed then return(\textit{MP\_MEM}). \\ -\\ -Split the input. e.g. $a = x1 \cdot \beta^B + x0$ \\ -3. $B \leftarrow \mbox{min}(a.used, b.used)/2$ \\ -4. $x0 \leftarrow a \mbox{ (mod }\beta^B\mbox{)}$ (\textit{mp\_mod\_2d}) \\ -5. $y0 \leftarrow b \mbox{ (mod }\beta^B\mbox{)}$ \\ -6. $x1 \leftarrow \lfloor a / \beta^B \rfloor$ (\textit{mp\_rshd}) \\ -7. $y1 \leftarrow \lfloor b / \beta^B \rfloor$ \\ -\\ -Calculate the three products. \\ -8. $x0y0 \leftarrow x0 \cdot y0$ (\textit{mp\_mul}) \\ -9. $x1y1 \leftarrow x1 \cdot y1$ \\ -10. $t1 \leftarrow x1 + x0$ (\textit{mp\_add}) \\ -11. $x0 \leftarrow y1 + y0$ \\ -12. $t1 \leftarrow t1 \cdot x0$ \\ -\\ -Calculate the middle term. \\ -13. $x0 \leftarrow x0y0 + x1y1$ \\ -14. $t1 \leftarrow t1 - x0$ (\textit{s\_mp\_sub}) \\ -\\ -Calculate the final product. \\ -15. $t1 \leftarrow t1 \cdot \beta^B$ (\textit{mp\_lshd}) \\ -16. $x1y1 \leftarrow x1y1 \cdot \beta^{2B}$ \\ -17. $t1 \leftarrow x0y0 + t1$ \\ -18. $c \leftarrow t1 + x1y1$ \\ -19. Clear all of the temporary variables. \\ -20. Return(\textit{MP\_OKAY}).\\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_karatsuba\_mul} -\end{figure} - -\textbf{Algorithm mp\_karatsuba\_mul.} -This algorithm computes the unsigned product of two inputs using the Karatsuba multiplication algorithm. It is loosely based on the description -from Knuth \cite[pp. 294-295]{TAOCPV2}. - -\index{radix point} -In order to split the two inputs into their respective halves, a suitable \textit{radix point} must be chosen. The radix point chosen must -be used for both of the inputs meaning that it must be smaller than the smallest input. Step 3 chooses the radix point $B$ as half of the -smallest input \textbf{used} count. After the radix point is chosen the inputs are split into lower and upper halves. Step 4 and 5 -compute the lower halves. Step 6 and 7 computer the upper halves. - -After the halves have been computed the three intermediate half-size products must be computed. Step 8 and 9 compute the trivial products -$x0 \cdot y0$ and $x1 \cdot y1$. The mp\_int $x0$ is used as a temporary variable after $x1 + x0$ has been computed. By using $x0$ instead -of an additional temporary variable, the algorithm can avoid an addition memory allocation operation. - -The remaining steps 13 through 18 compute the Karatsuba polynomial through a variety of digit shifting and addition operations. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_karatsuba\_mul.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* c = |a| * |b| using Karatsuba Multiplication using -018 * three half size multiplications -019 * -020 * Let B represent the radix [e.g. 2**DIGIT_BIT] and -021 * let n represent half of the number of digits in -022 * the min(a,b) -023 * -024 * a = a1 * B**n + a0 -025 * b = b1 * B**n + b0 -026 * -027 * Then, a * b => -028 a1b1 * B**2n + ((a1 + a0)(b1 + b0) - (a0b0 + a1b1)) * B + a0b0 -029 * -030 * Note that a1b1 and a0b0 are used twice and only need to be -031 * computed once. So in total three half size (half # of -032 * digit) multiplications are performed, a0b0, a1b1 and -033 * (a1+b1)(a0+b0) -034 * -035 * Note that a multiplication of half the digits requires -036 * 1/4th the number of single precision multiplications so in -037 * total after one call 25% of the single precision multiplications -038 * are saved. Note also that the call to mp_mul can end up back -039 * in this function if the a0, a1, b0, or b1 are above the threshold. -040 * This is known as divide-and-conquer and leads to the famous -041 * O(N**lg(3)) or O(N**1.584) work which is asymptopically lower than -042 * the standard O(N**2) that the baseline/comba methods use. -043 * Generally though the overhead of this method doesn't pay off -044 * until a certain size (N ~ 80) is reached. -045 */ -046 int mp_karatsuba_mul (mp_int * a, mp_int * b, mp_int * c) -047 \{ -048 mp_int x0, x1, y0, y1, t1, x0y0, x1y1; -049 int B, err; -050 -051 /* default the return code to an error */ -052 err = MP_MEM; -053 -054 /* min # of digits */ -055 B = MIN (a->used, b->used); -056 -057 /* now divide in two */ -058 B = B >> 1; -059 -060 /* init copy all the temps */ -061 if (mp_init_size (&x0, B) != MP_OKAY) -062 goto ERR; -063 if (mp_init_size (&x1, a->used - B) != MP_OKAY) -064 goto X0; -065 if (mp_init_size (&y0, B) != MP_OKAY) -066 goto X1; -067 if (mp_init_size (&y1, b->used - B) != MP_OKAY) -068 goto Y0; -069 -070 /* init temps */ -071 if (mp_init_size (&t1, B * 2) != MP_OKAY) -072 goto Y1; -073 if (mp_init_size (&x0y0, B * 2) != MP_OKAY) -074 goto T1; -075 if (mp_init_size (&x1y1, B * 2) != MP_OKAY) -076 goto X0Y0; -077 -078 /* now shift the digits */ -079 x0.used = y0.used = B; -080 x1.used = a->used - B; -081 y1.used = b->used - B; -082 -083 \{ -084 int x; -085 mp_digit *tmpa, *tmpb, *tmpx, *tmpy; -086 -087 /* we copy the digits directly instead of using higher level functions -088 * since we also need to shift the digits -089 */ -090 tmpa = a->dp; -091 tmpb = b->dp; -092 -093 tmpx = x0.dp; -094 tmpy = y0.dp; -095 for (x = 0; x < B; x++) \{ -096 *tmpx++ = *tmpa++; -097 *tmpy++ = *tmpb++; -098 \} -099 -100 tmpx = x1.dp; -101 for (x = B; x < a->used; x++) \{ -102 *tmpx++ = *tmpa++; -103 \} -104 -105 tmpy = y1.dp; -106 for (x = B; x < b->used; x++) \{ -107 *tmpy++ = *tmpb++; -108 \} -109 \} -110 -111 /* only need to clamp the lower words since by definition the -112 * upper words x1/y1 must have a known number of digits -113 */ -114 mp_clamp (&x0); -115 mp_clamp (&y0); -116 -117 /* now calc the products x0y0 and x1y1 */ -118 /* after this x0 is no longer required, free temp [x0==t2]! */ -119 if (mp_mul (&x0, &y0, &x0y0) != MP_OKAY) -120 goto X1Y1; /* x0y0 = x0*y0 */ -121 if (mp_mul (&x1, &y1, &x1y1) != MP_OKAY) -122 goto X1Y1; /* x1y1 = x1*y1 */ -123 -124 /* now calc x1+x0 and y1+y0 */ -125 if (s_mp_add (&x1, &x0, &t1) != MP_OKAY) -126 goto X1Y1; /* t1 = x1 - x0 */ -127 if (s_mp_add (&y1, &y0, &x0) != MP_OKAY) -128 goto X1Y1; /* t2 = y1 - y0 */ -129 if (mp_mul (&t1, &x0, &t1) != MP_OKAY) -130 goto X1Y1; /* t1 = (x1 + x0) * (y1 + y0) */ -131 -132 /* add x0y0 */ -133 if (mp_add (&x0y0, &x1y1, &x0) != MP_OKAY) -134 goto X1Y1; /* t2 = x0y0 + x1y1 */ -135 if (s_mp_sub (&t1, &x0, &t1) != MP_OKAY) -136 goto X1Y1; /* t1 = (x1+x0)*(y1+y0) - (x1y1 + x0y0) */ -137 -138 /* shift by B */ -139 if (mp_lshd (&t1, B) != MP_OKAY) -140 goto X1Y1; /* t1 = (x0y0 + x1y1 - (x1-x0)*(y1-y0))<<B */ -141 if (mp_lshd (&x1y1, B * 2) != MP_OKAY) -142 goto X1Y1; /* x1y1 = x1y1 << 2*B */ -143 -144 if (mp_add (&x0y0, &t1, &t1) != MP_OKAY) -145 goto X1Y1; /* t1 = x0y0 + t1 */ -146 if (mp_add (&t1, &x1y1, c) != MP_OKAY) -147 goto X1Y1; /* t1 = x0y0 + t1 + x1y1 */ -148 -149 /* Algorithm succeeded set the return code to MP_OKAY */ -150 err = MP_OKAY; -151 -152 X1Y1:mp_clear (&x1y1); -153 X0Y0:mp_clear (&x0y0); -154 T1:mp_clear (&t1); -155 Y1:mp_clear (&y1); -156 Y0:mp_clear (&y0); -157 X1:mp_clear (&x1); -158 X0:mp_clear (&x0); -159 ERR: -160 return err; -161 \} -162 #endif -163 -\end{alltt} -\end{small} - -The new coding element in this routine, not seen in previous routines, is the usage of goto statements. The conventional -wisdom is that goto statements should be avoided. This is generally true, however when every single function call can fail, it makes sense -to handle error recovery with a single piece of code. Lines 61 to 75 handle initializing all of the temporary variables -required. Note how each of the if statements goes to a different label in case of failure. This allows the routine to correctly free only -the temporaries that have been successfully allocated so far. - -The temporary variables are all initialized using the mp\_init\_size routine since they are expected to be large. This saves the -additional reallocation that would have been necessary. Also $x0$, $x1$, $y0$ and $y1$ have to be able to hold at least their respective -number of digits for the next section of code. - -The first algebraic portion of the algorithm is to split the two inputs into their halves. However, instead of using mp\_mod\_2d and mp\_rshd -to extract the halves, the respective code has been placed inline within the body of the function. To initialize the halves, the \textbf{used} and -\textbf{sign} members are copied first. The first for loop on line 101 copies the lower halves. Since they are both the same magnitude it -is simpler to calculate both lower halves in a single loop. The for loop on lines 106 and 106 calculate the upper halves $x1$ and -$y1$ respectively. - -By inlining the calculation of the halves, the Karatsuba multiplier has a slightly lower overhead and can be used for smaller magnitude inputs. - -When line 150 is reached, the algorithm has completed succesfully. The ``error status'' variable $err$ is set to \textbf{MP\_OKAY} so that -the same code that handles errors can be used to clear the temporary variables and return. - -\subsection{Toom-Cook $3$-Way Multiplication} -Toom-Cook $3$-Way \cite{TOOM} multiplication is essentially the polynomial basis algorithm for $n = 2$ except that the points are -chosen such that $\zeta$ is easy to compute and the resulting system of equations easy to reduce. Here, the points $\zeta_{0}$, -$16 \cdot \zeta_{1 \over 2}$, $\zeta_1$, $\zeta_2$ and $\zeta_{\infty}$ make up the five required points to solve for the coefficients -of the $W(x)$. - -With the five relations that Toom-Cook specifies, the following system of equations is formed. - -\begin{center} -\begin{tabular}{rcrcrcrcrcr} -$\zeta_0$ & $=$ & $0w_4$ & $+$ & $0w_3$ & $+$ & $0w_2$ & $+$ & $0w_1$ & $+$ & $1w_0$ \\ -$16 \cdot \zeta_{1 \over 2}$ & $=$ & $1w_4$ & $+$ & $2w_3$ & $+$ & $4w_2$ & $+$ & $8w_1$ & $+$ & $16w_0$ \\ -$\zeta_1$ & $=$ & $1w_4$ & $+$ & $1w_3$ & $+$ & $1w_2$ & $+$ & $1w_1$ & $+$ & $1w_0$ \\ -$\zeta_2$ & $=$ & $16w_4$ & $+$ & $8w_3$ & $+$ & $4w_2$ & $+$ & $2w_1$ & $+$ & $1w_0$ \\ -$\zeta_{\infty}$ & $=$ & $1w_4$ & $+$ & $0w_3$ & $+$ & $0w_2$ & $+$ & $0w_1$ & $+$ & $0w_0$ \\ -\end{tabular} -\end{center} - -A trivial solution to this matrix requires $12$ subtractions, two multiplications by a small power of two, two divisions by a small power -of two, two divisions by three and one multiplication by three. All of these $19$ sub-operations require less than quadratic time, meaning that -the algorithm can be faster than a baseline multiplication. However, the greater complexity of this algorithm places the cutoff point -(\textbf{TOOM\_MUL\_CUTOFF}) where Toom-Cook becomes more efficient much higher than the Karatsuba cutoff point. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_toom\_mul}. \\ -\textbf{Input}. mp\_int $a$ and mp\_int $b$ \\ -\textbf{Output}. $c \leftarrow a \cdot b $ \\ -\hline \\ -Split $a$ and $b$ into three pieces. E.g. $a = a_2 \beta^{2k} + a_1 \beta^{k} + a_0$ \\ -1. $k \leftarrow \lfloor \mbox{min}(a.used, b.used) / 3 \rfloor$ \\ -2. $a_0 \leftarrow a \mbox{ (mod }\beta^{k}\mbox{)}$ \\ -3. $a_1 \leftarrow \lfloor a / \beta^k \rfloor$, $a_1 \leftarrow a_1 \mbox{ (mod }\beta^{k}\mbox{)}$ \\ -4. $a_2 \leftarrow \lfloor a / \beta^{2k} \rfloor$, $a_2 \leftarrow a_2 \mbox{ (mod }\beta^{k}\mbox{)}$ \\ -5. $b_0 \leftarrow a \mbox{ (mod }\beta^{k}\mbox{)}$ \\ -6. $b_1 \leftarrow \lfloor a / \beta^k \rfloor$, $b_1 \leftarrow b_1 \mbox{ (mod }\beta^{k}\mbox{)}$ \\ -7. $b_2 \leftarrow \lfloor a / \beta^{2k} \rfloor$, $b_2 \leftarrow b_2 \mbox{ (mod }\beta^{k}\mbox{)}$ \\ -\\ -Find the five equations for $w_0, w_1, ..., w_4$. \\ -8. $w_0 \leftarrow a_0 \cdot b_0$ \\ -9. $w_4 \leftarrow a_2 \cdot b_2$ \\ -10. $tmp_1 \leftarrow 2 \cdot a_0$, $tmp_1 \leftarrow a_1 + tmp_1$, $tmp_1 \leftarrow 2 \cdot tmp_1$, $tmp_1 \leftarrow tmp_1 + a_2$ \\ -11. $tmp_2 \leftarrow 2 \cdot b_0$, $tmp_2 \leftarrow b_1 + tmp_2$, $tmp_2 \leftarrow 2 \cdot tmp_2$, $tmp_2 \leftarrow tmp_2 + b_2$ \\ -12. $w_1 \leftarrow tmp_1 \cdot tmp_2$ \\ -13. $tmp_1 \leftarrow 2 \cdot a_2$, $tmp_1 \leftarrow a_1 + tmp_1$, $tmp_1 \leftarrow 2 \cdot tmp_1$, $tmp_1 \leftarrow tmp_1 + a_0$ \\ -14. $tmp_2 \leftarrow 2 \cdot b_2$, $tmp_2 \leftarrow b_1 + tmp_2$, $tmp_2 \leftarrow 2 \cdot tmp_2$, $tmp_2 \leftarrow tmp_2 + b_0$ \\ -15. $w_3 \leftarrow tmp_1 \cdot tmp_2$ \\ -16. $tmp_1 \leftarrow a_0 + a_1$, $tmp_1 \leftarrow tmp_1 + a_2$, $tmp_2 \leftarrow b_0 + b_1$, $tmp_2 \leftarrow tmp_2 + b_2$ \\ -17. $w_2 \leftarrow tmp_1 \cdot tmp_2$ \\ -\\ -Continued on the next page.\\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_toom\_mul} -\end{figure} - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_toom\_mul} (continued). \\ -\textbf{Input}. mp\_int $a$ and mp\_int $b$ \\ -\textbf{Output}. $c \leftarrow a \cdot b $ \\ -\hline \\ -Now solve the system of equations. \\ -18. $w_1 \leftarrow w_4 - w_1$, $w_3 \leftarrow w_3 - w_0$ \\ -19. $w_1 \leftarrow \lfloor w_1 / 2 \rfloor$, $w_3 \leftarrow \lfloor w_3 / 2 \rfloor$ \\ -20. $w_2 \leftarrow w_2 - w_0$, $w_2 \leftarrow w_2 - w_4$ \\ -21. $w_1 \leftarrow w_1 - w_2$, $w_3 \leftarrow w_3 - w_2$ \\ -22. $tmp_1 \leftarrow 8 \cdot w_0$, $w_1 \leftarrow w_1 - tmp_1$, $tmp_1 \leftarrow 8 \cdot w_4$, $w_3 \leftarrow w_3 - tmp_1$ \\ -23. $w_2 \leftarrow 3 \cdot w_2$, $w_2 \leftarrow w_2 - w_1$, $w_2 \leftarrow w_2 - w_3$ \\ -24. $w_1 \leftarrow w_1 - w_2$, $w_3 \leftarrow w_3 - w_2$ \\ -25. $w_1 \leftarrow \lfloor w_1 / 3 \rfloor, w_3 \leftarrow \lfloor w_3 / 3 \rfloor$ \\ -\\ -Now substitute $\beta^k$ for $x$ by shifting $w_0, w_1, ..., w_4$. \\ -26. for $n$ from $1$ to $4$ do \\ -\hspace{3mm}26.1 $w_n \leftarrow w_n \cdot \beta^{nk}$ \\ -27. $c \leftarrow w_0 + w_1$, $c \leftarrow c + w_2$, $c \leftarrow c + w_3$, $c \leftarrow c + w_4$ \\ -28. Return(\textit{MP\_OKAY}) \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_toom\_mul (continued)} -\end{figure} - -\textbf{Algorithm mp\_toom\_mul.} -This algorithm computes the product of two mp\_int variables $a$ and $b$ using the Toom-Cook approach. Compared to the Karatsuba multiplication, this -algorithm has a lower asymptotic running time of approximately $O(n^{1.464})$ but at an obvious cost in overhead. In this -description, several statements have been compounded to save space. The intention is that the statements are executed from left to right across -any given step. - -The two inputs $a$ and $b$ are first split into three $k$-digit integers $a_0, a_1, a_2$ and $b_0, b_1, b_2$ respectively. From these smaller -integers the coefficients of the polynomial basis representations $f(x)$ and $g(x)$ are known and can be used to find the relations required. - -The first two relations $w_0$ and $w_4$ are the points $\zeta_{0}$ and $\zeta_{\infty}$ respectively. The relation $w_1, w_2$ and $w_3$ correspond -to the points $16 \cdot \zeta_{1 \over 2}, \zeta_{2}$ and $\zeta_{1}$ respectively. These are found using logical shifts to independently find -$f(y)$ and $g(y)$ which significantly speeds up the algorithm. - -After the five relations $w_0, w_1, \ldots, w_4$ have been computed, the system they represent must be solved in order for the unknown coefficients -$w_1, w_2$ and $w_3$ to be isolated. The steps 18 through 25 perform the system reduction required as previously described. Each step of -the reduction represents the comparable matrix operation that would be performed had this been performed by pencil. For example, step 18 indicates -that row $1$ must be subtracted from row $4$ and simultaneously row $0$ subtracted from row $3$. - -Once the coeffients have been isolated, the polynomial $W(x) = \sum_{i=0}^{2n} w_i x^i$ is known. By substituting $\beta^{k}$ for $x$, the integer -result $a \cdot b$ is produced. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_toom\_mul.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* multiplication using the Toom-Cook 3-way algorithm -018 * -019 * Much more complicated than Karatsuba but has a lower -020 * asymptotic running time of O(N**1.464). This algorithm is -021 * only particularly useful on VERY large inputs -022 * (we're talking 1000s of digits here...). -023 */ -024 int mp_toom_mul(mp_int *a, mp_int *b, mp_int *c) -025 \{ -026 mp_int w0, w1, w2, w3, w4, tmp1, tmp2, a0, a1, a2, b0, b1, b2; -027 int res, B; -028 -029 /* init temps */ -030 if ((res = mp_init_multi(&w0, &w1, &w2, &w3, &w4, -031 &a0, &a1, &a2, &b0, &b1, -032 &b2, &tmp1, &tmp2, NULL)) != MP_OKAY) \{ -033 return res; -034 \} -035 -036 /* B */ -037 B = MIN(a->used, b->used) / 3; -038 -039 /* a = a2 * B**2 + a1 * B + a0 */ -040 if ((res = mp_mod_2d(a, DIGIT_BIT * B, &a0)) != MP_OKAY) \{ -041 goto ERR; -042 \} -043 -044 if ((res = mp_copy(a, &a1)) != MP_OKAY) \{ -045 goto ERR; -046 \} -047 mp_rshd(&a1, B); -048 if ((res = mp_mod_2d(&a1, DIGIT_BIT * B, &a1)) != MP_OKAY) \{ -049 goto ERR; -050 \} -051 -052 if ((res = mp_copy(a, &a2)) != MP_OKAY) \{ -053 goto ERR; -054 \} -055 mp_rshd(&a2, B*2); -056 -057 /* b = b2 * B**2 + b1 * B + b0 */ -058 if ((res = mp_mod_2d(b, DIGIT_BIT * B, &b0)) != MP_OKAY) \{ -059 goto ERR; -060 \} -061 -062 if ((res = mp_copy(b, &b1)) != MP_OKAY) \{ -063 goto ERR; -064 \} -065 mp_rshd(&b1, B); -066 (void)mp_mod_2d(&b1, DIGIT_BIT * B, &b1); -067 -068 if ((res = mp_copy(b, &b2)) != MP_OKAY) \{ -069 goto ERR; -070 \} -071 mp_rshd(&b2, B*2); -072 -073 /* w0 = a0*b0 */ -074 if ((res = mp_mul(&a0, &b0, &w0)) != MP_OKAY) \{ -075 goto ERR; -076 \} -077 -078 /* w4 = a2 * b2 */ -079 if ((res = mp_mul(&a2, &b2, &w4)) != MP_OKAY) \{ -080 goto ERR; -081 \} -082 -083 /* w1 = (a2 + 2(a1 + 2a0))(b2 + 2(b1 + 2b0)) */ -084 if ((res = mp_mul_2(&a0, &tmp1)) != MP_OKAY) \{ -085 goto ERR; -086 \} -087 if ((res = mp_add(&tmp1, &a1, &tmp1)) != MP_OKAY) \{ -088 goto ERR; -089 \} -090 if ((res = mp_mul_2(&tmp1, &tmp1)) != MP_OKAY) \{ -091 goto ERR; -092 \} -093 if ((res = mp_add(&tmp1, &a2, &tmp1)) != MP_OKAY) \{ -094 goto ERR; -095 \} -096 -097 if ((res = mp_mul_2(&b0, &tmp2)) != MP_OKAY) \{ -098 goto ERR; -099 \} -100 if ((res = mp_add(&tmp2, &b1, &tmp2)) != MP_OKAY) \{ -101 goto ERR; -102 \} -103 if ((res = mp_mul_2(&tmp2, &tmp2)) != MP_OKAY) \{ -104 goto ERR; -105 \} -106 if ((res = mp_add(&tmp2, &b2, &tmp2)) != MP_OKAY) \{ -107 goto ERR; -108 \} -109 -110 if ((res = mp_mul(&tmp1, &tmp2, &w1)) != MP_OKAY) \{ -111 goto ERR; -112 \} -113 -114 /* w3 = (a0 + 2(a1 + 2a2))(b0 + 2(b1 + 2b2)) */ -115 if ((res = mp_mul_2(&a2, &tmp1)) != MP_OKAY) \{ -116 goto ERR; -117 \} -118 if ((res = mp_add(&tmp1, &a1, &tmp1)) != MP_OKAY) \{ -119 goto ERR; -120 \} -121 if ((res = mp_mul_2(&tmp1, &tmp1)) != MP_OKAY) \{ -122 goto ERR; -123 \} -124 if ((res = mp_add(&tmp1, &a0, &tmp1)) != MP_OKAY) \{ -125 goto ERR; -126 \} -127 -128 if ((res = mp_mul_2(&b2, &tmp2)) != MP_OKAY) \{ -129 goto ERR; -130 \} -131 if ((res = mp_add(&tmp2, &b1, &tmp2)) != MP_OKAY) \{ -132 goto ERR; -133 \} -134 if ((res = mp_mul_2(&tmp2, &tmp2)) != MP_OKAY) \{ -135 goto ERR; -136 \} -137 if ((res = mp_add(&tmp2, &b0, &tmp2)) != MP_OKAY) \{ -138 goto ERR; -139 \} -140 -141 if ((res = mp_mul(&tmp1, &tmp2, &w3)) != MP_OKAY) \{ -142 goto ERR; -143 \} -144 -145 -146 /* w2 = (a2 + a1 + a0)(b2 + b1 + b0) */ -147 if ((res = mp_add(&a2, &a1, &tmp1)) != MP_OKAY) \{ -148 goto ERR; -149 \} -150 if ((res = mp_add(&tmp1, &a0, &tmp1)) != MP_OKAY) \{ -151 goto ERR; -152 \} -153 if ((res = mp_add(&b2, &b1, &tmp2)) != MP_OKAY) \{ -154 goto ERR; -155 \} -156 if ((res = mp_add(&tmp2, &b0, &tmp2)) != MP_OKAY) \{ -157 goto ERR; -158 \} -159 if ((res = mp_mul(&tmp1, &tmp2, &w2)) != MP_OKAY) \{ -160 goto ERR; -161 \} -162 -163 /* now solve the matrix -164 -165 0 0 0 0 1 -166 1 2 4 8 16 -167 1 1 1 1 1 -168 16 8 4 2 1 -169 1 0 0 0 0 -170 -171 using 12 subtractions, 4 shifts, -172 2 small divisions and 1 small multiplication -173 */ -174 -175 /* r1 - r4 */ -176 if ((res = mp_sub(&w1, &w4, &w1)) != MP_OKAY) \{ -177 goto ERR; -178 \} -179 /* r3 - r0 */ -180 if ((res = mp_sub(&w3, &w0, &w3)) != MP_OKAY) \{ -181 goto ERR; -182 \} -183 /* r1/2 */ -184 if ((res = mp_div_2(&w1, &w1)) != MP_OKAY) \{ -185 goto ERR; -186 \} -187 /* r3/2 */ -188 if ((res = mp_div_2(&w3, &w3)) != MP_OKAY) \{ -189 goto ERR; -190 \} -191 /* r2 - r0 - r4 */ -192 if ((res = mp_sub(&w2, &w0, &w2)) != MP_OKAY) \{ -193 goto ERR; -194 \} -195 if ((res = mp_sub(&w2, &w4, &w2)) != MP_OKAY) \{ -196 goto ERR; -197 \} -198 /* r1 - r2 */ -199 if ((res = mp_sub(&w1, &w2, &w1)) != MP_OKAY) \{ -200 goto ERR; -201 \} -202 /* r3 - r2 */ -203 if ((res = mp_sub(&w3, &w2, &w3)) != MP_OKAY) \{ -204 goto ERR; -205 \} -206 /* r1 - 8r0 */ -207 if ((res = mp_mul_2d(&w0, 3, &tmp1)) != MP_OKAY) \{ -208 goto ERR; -209 \} -210 if ((res = mp_sub(&w1, &tmp1, &w1)) != MP_OKAY) \{ -211 goto ERR; -212 \} -213 /* r3 - 8r4 */ -214 if ((res = mp_mul_2d(&w4, 3, &tmp1)) != MP_OKAY) \{ -215 goto ERR; -216 \} -217 if ((res = mp_sub(&w3, &tmp1, &w3)) != MP_OKAY) \{ -218 goto ERR; -219 \} -220 /* 3r2 - r1 - r3 */ -221 if ((res = mp_mul_d(&w2, 3, &w2)) != MP_OKAY) \{ -222 goto ERR; -223 \} -224 if ((res = mp_sub(&w2, &w1, &w2)) != MP_OKAY) \{ -225 goto ERR; -226 \} -227 if ((res = mp_sub(&w2, &w3, &w2)) != MP_OKAY) \{ -228 goto ERR; -229 \} -230 /* r1 - r2 */ -231 if ((res = mp_sub(&w1, &w2, &w1)) != MP_OKAY) \{ -232 goto ERR; -233 \} -234 /* r3 - r2 */ -235 if ((res = mp_sub(&w3, &w2, &w3)) != MP_OKAY) \{ -236 goto ERR; -237 \} -238 /* r1/3 */ -239 if ((res = mp_div_3(&w1, &w1, NULL)) != MP_OKAY) \{ -240 goto ERR; -241 \} -242 /* r3/3 */ -243 if ((res = mp_div_3(&w3, &w3, NULL)) != MP_OKAY) \{ -244 goto ERR; -245 \} -246 -247 /* at this point shift W[n] by B*n */ -248 if ((res = mp_lshd(&w1, 1*B)) != MP_OKAY) \{ -249 goto ERR; -250 \} -251 if ((res = mp_lshd(&w2, 2*B)) != MP_OKAY) \{ -252 goto ERR; -253 \} -254 if ((res = mp_lshd(&w3, 3*B)) != MP_OKAY) \{ -255 goto ERR; -256 \} -257 if ((res = mp_lshd(&w4, 4*B)) != MP_OKAY) \{ -258 goto ERR; -259 \} -260 -261 if ((res = mp_add(&w0, &w1, c)) != MP_OKAY) \{ -262 goto ERR; -263 \} -264 if ((res = mp_add(&w2, &w3, &tmp1)) != MP_OKAY) \{ -265 goto ERR; -266 \} -267 if ((res = mp_add(&w4, &tmp1, &tmp1)) != MP_OKAY) \{ -268 goto ERR; -269 \} -270 if ((res = mp_add(&tmp1, c, c)) != MP_OKAY) \{ -271 goto ERR; -272 \} -273 -274 ERR: -275 mp_clear_multi(&w0, &w1, &w2, &w3, &w4, -276 &a0, &a1, &a2, &b0, &b1, -277 &b2, &tmp1, &tmp2, NULL); -278 return res; -279 \} -280 -281 #endif -282 -\end{alltt} -\end{small} - -The first obvious thing to note is that this algorithm is complicated. The complexity is worth it if you are multiplying very -large numbers. For example, a 10,000 digit multiplication takes approximaly 99,282,205 fewer single precision multiplications with -Toom--Cook than a Comba or baseline approach (this is a savings of more than 99$\%$). For most ``crypto'' sized numbers this -algorithm is not practical as Karatsuba has a much lower cutoff point. - -First we split $a$ and $b$ into three roughly equal portions. This has been accomplished (lines 40 to 71) with -combinations of mp\_rshd() and mp\_mod\_2d() function calls. At this point $a = a2 \cdot \beta^2 + a1 \cdot \beta + a0$ and similiarly -for $b$. - -Next we compute the five points $w0, w1, w2, w3$ and $w4$. Recall that $w0$ and $w4$ can be computed directly from the portions so -we get those out of the way first (lines 74 and 79). Next we compute $w1, w2$ and $w3$ using Horners method. - -After this point we solve for the actual values of $w1, w2$ and $w3$ by reducing the $5 \times 5$ system which is relatively -straight forward. - -\subsection{Signed Multiplication} -Now that algorithms to handle multiplications of every useful dimensions have been developed, a rather simple finishing touch is required. So far all -of the multiplication algorithms have been unsigned multiplications which leaves only a signed multiplication algorithm to be established. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_mul}. \\ -\textbf{Input}. mp\_int $a$ and mp\_int $b$ \\ -\textbf{Output}. $c \leftarrow a \cdot b$ \\ -\hline \\ -1. If $a.sign = b.sign$ then \\ -\hspace{3mm}1.1 $sign = MP\_ZPOS$ \\ -2. else \\ -\hspace{3mm}2.1 $sign = MP\_ZNEG$ \\ -3. If min$(a.used, b.used) \ge TOOM\_MUL\_CUTOFF$ then \\ -\hspace{3mm}3.1 $c \leftarrow a \cdot b$ using algorithm mp\_toom\_mul \\ -4. else if min$(a.used, b.used) \ge KARATSUBA\_MUL\_CUTOFF$ then \\ -\hspace{3mm}4.1 $c \leftarrow a \cdot b$ using algorithm mp\_karatsuba\_mul \\ -5. else \\ -\hspace{3mm}5.1 $digs \leftarrow a.used + b.used + 1$ \\ -\hspace{3mm}5.2 If $digs < MP\_ARRAY$ and min$(a.used, b.used) \le \delta$ then \\ -\hspace{6mm}5.2.1 $c \leftarrow a \cdot b \mbox{ (mod }\beta^{digs}\mbox{)}$ using algorithm fast\_s\_mp\_mul\_digs. \\ -\hspace{3mm}5.3 else \\ -\hspace{6mm}5.3.1 $c \leftarrow a \cdot b \mbox{ (mod }\beta^{digs}\mbox{)}$ using algorithm s\_mp\_mul\_digs. \\ -6. $c.sign \leftarrow sign$ \\ -7. Return the result of the unsigned multiplication performed. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_mul} -\end{figure} - -\textbf{Algorithm mp\_mul.} -This algorithm performs the signed multiplication of two inputs. It will make use of any of the three unsigned multiplication algorithms -available when the input is of appropriate size. The \textbf{sign} of the result is not set until the end of the algorithm since algorithm -s\_mp\_mul\_digs will clear it. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_mul.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* high level multiplication (handles sign) */ -018 int mp_mul (mp_int * a, mp_int * b, mp_int * c) -019 \{ -020 int res, neg; -021 neg = (a->sign == b->sign) ? MP_ZPOS : MP_NEG; -022 -023 /* use Toom-Cook? */ -024 #ifdef BN_MP_TOOM_MUL_C -025 if (MIN (a->used, b->used) >= TOOM_MUL_CUTOFF) \{ -026 res = mp_toom_mul(a, b, c); -027 \} else -028 #endif -029 #ifdef BN_MP_KARATSUBA_MUL_C -030 /* use Karatsuba? */ -031 if (MIN (a->used, b->used) >= KARATSUBA_MUL_CUTOFF) \{ -032 res = mp_karatsuba_mul (a, b, c); -033 \} else -034 #endif -035 \{ -036 /* can we use the fast multiplier? -037 * -038 * The fast multiplier can be used if the output will -039 * have less than MP_WARRAY digits and the number of -040 * digits won't affect carry propagation -041 */ -042 int digs = a->used + b->used + 1; -043 -044 #ifdef BN_FAST_S_MP_MUL_DIGS_C -045 if ((digs < MP_WARRAY) && -046 (MIN(a->used, b->used) <= -047 (1 << ((CHAR_BIT * sizeof(mp_word)) - (2 * DIGIT_BIT))))) \{ -048 res = fast_s_mp_mul_digs (a, b, c, digs); -049 \} else -050 #endif -051 \{ -052 #ifdef BN_S_MP_MUL_DIGS_C -053 res = s_mp_mul (a, b, c); /* uses s_mp_mul_digs */ -054 #else -055 res = MP_VAL; -056 #endif -057 \} -058 \} -059 c->sign = (c->used > 0) ? neg : MP_ZPOS; -060 return res; -061 \} -062 #endif -063 -\end{alltt} -\end{small} - -The implementation is rather simplistic and is not particularly noteworthy. Line 23 computes the sign of the result using the ``?'' -operator from the C programming language. Line 47 computes $\delta$ using the fact that $1 << k$ is equal to $2^k$. - -\section{Squaring} -\label{sec:basesquare} - -Squaring is a special case of multiplication where both multiplicands are equal. At first it may seem like there is no significant optimization -available but in fact there is. Consider the multiplication of $576$ against $241$. In total there will be nine single precision multiplications -performed which are $1\cdot 6$, $1 \cdot 7$, $1 \cdot 5$, $4 \cdot 6$, $4 \cdot 7$, $4 \cdot 5$, $2 \cdot 6$, $2 \cdot 7$ and $2 \cdot 5$. Now consider -the multiplication of $123$ against $123$. The nine products are $3 \cdot 3$, $3 \cdot 2$, $3 \cdot 1$, $2 \cdot 3$, $2 \cdot 2$, $2 \cdot 1$, -$1 \cdot 3$, $1 \cdot 2$ and $1 \cdot 1$. On closer inspection some of the products are equivalent. For example, $3 \cdot 2 = 2 \cdot 3$ -and $3 \cdot 1 = 1 \cdot 3$. - -For any $n$-digit input, there are ${{\left (n^2 + n \right)}\over 2}$ possible unique single precision multiplications required compared to the $n^2$ -required for multiplication. The following diagram gives an example of the operations required. - -\begin{figure}[here] -\begin{center} -\begin{tabular}{ccccc|c} -&&1&2&3&\\ -$\times$ &&1&2&3&\\ -\hline && $3 \cdot 1$ & $3 \cdot 2$ & $3 \cdot 3$ & Row 0\\ - & $2 \cdot 1$ & $2 \cdot 2$ & $2 \cdot 3$ && Row 1 \\ - $1 \cdot 1$ & $1 \cdot 2$ & $1 \cdot 3$ &&& Row 2 \\ -\end{tabular} -\end{center} -\caption{Squaring Optimization Diagram} -\end{figure} - -Starting from zero and numbering the columns from right to left a very simple pattern becomes obvious. For the purposes of this discussion let $x$ -represent the number being squared. The first observation is that in row $k$ the $2k$'th column of the product has a $\left (x_k \right)^2$ term in it. - -The second observation is that every column $j$ in row $k$ where $j \ne 2k$ is part of a double product. Every non-square term of a column will -appear twice hence the name ``double product''. Every odd column is made up entirely of double products. In fact every column is made up of double -products and at most one square (\textit{see the exercise section}). - -The third and final observation is that for row $k$ the first unique non-square term, that is, one that hasn't already appeared in an earlier row, -occurs at column $2k + 1$. For example, on row $1$ of the previous squaring, column one is part of the double product with column one from row zero. -Column two of row one is a square and column three is the first unique column. - -\subsection{The Baseline Squaring Algorithm} -The baseline squaring algorithm is meant to be a catch-all squaring algorithm. It will handle any of the input sizes that the faster routines -will not handle. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{s\_mp\_sqr}. \\ -\textbf{Input}. mp\_int $a$ \\ -\textbf{Output}. $b \leftarrow a^2$ \\ -\hline \\ -1. Init a temporary mp\_int of at least $2 \cdot a.used +1$ digits. (\textit{mp\_init\_size}) \\ -2. If step 1 failed return(\textit{MP\_MEM}) \\ -3. $t.used \leftarrow 2 \cdot a.used + 1$ \\ -4. For $ix$ from 0 to $a.used - 1$ do \\ -\hspace{3mm}Calculate the square. \\ -\hspace{3mm}4.1 $\hat r \leftarrow t_{2ix} + \left (a_{ix} \right )^2$ \\ -\hspace{3mm}4.2 $t_{2ix} \leftarrow \hat r \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{3mm}Calculate the double products after the square. \\ -\hspace{3mm}4.3 $u \leftarrow \lfloor \hat r / \beta \rfloor$ \\ -\hspace{3mm}4.4 For $iy$ from $ix + 1$ to $a.used - 1$ do \\ -\hspace{6mm}4.4.1 $\hat r \leftarrow 2 \cdot a_{ix}a_{iy} + t_{ix + iy} + u$ \\ -\hspace{6mm}4.4.2 $t_{ix + iy} \leftarrow \hat r \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{6mm}4.4.3 $u \leftarrow \lfloor \hat r / \beta \rfloor$ \\ -\hspace{3mm}Set the last carry. \\ -\hspace{3mm}4.5 While $u > 0$ do \\ -\hspace{6mm}4.5.1 $iy \leftarrow iy + 1$ \\ -\hspace{6mm}4.5.2 $\hat r \leftarrow t_{ix + iy} + u$ \\ -\hspace{6mm}4.5.3 $t_{ix + iy} \leftarrow \hat r \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{6mm}4.5.4 $u \leftarrow \lfloor \hat r / \beta \rfloor$ \\ -5. Clamp excess digits of $t$. (\textit{mp\_clamp}) \\ -6. Exchange $b$ and $t$. \\ -7. Clear $t$ (\textit{mp\_clear}) \\ -8. Return(\textit{MP\_OKAY}) \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm s\_mp\_sqr} -\end{figure} - -\textbf{Algorithm s\_mp\_sqr.} -This algorithm computes the square of an input using the three observations on squaring. It is based fairly faithfully on algorithm 14.16 of HAC -\cite[pp.596-597]{HAC}. Similar to algorithm s\_mp\_mul\_digs, a temporary mp\_int is allocated to hold the result of the squaring. This allows the -destination mp\_int to be the same as the source mp\_int. - -The outer loop of this algorithm begins on step 4. It is best to think of the outer loop as walking down the rows of the partial results, while -the inner loop computes the columns of the partial result. Step 4.1 and 4.2 compute the square term for each row, and step 4.3 and 4.4 propagate -the carry and compute the double products. - -The requirement that a mp\_word be able to represent the range $0 \le x < 2 \beta^2$ arises from this -very algorithm. The product $a_{ix}a_{iy}$ will lie in the range $0 \le x \le \beta^2 - 2\beta + 1$ which is obviously less than $\beta^2$ meaning that -when it is multiplied by two, it can be properly represented by a mp\_word. - -Similar to algorithm s\_mp\_mul\_digs, after every pass of the inner loop, the destination is correctly set to the sum of all of the partial -results calculated so far. This involves expensive carry propagation which will be eliminated in the next algorithm. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_s\_mp\_sqr.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* low level squaring, b = a*a, HAC pp.596-597, Algorithm 14.16 */ -018 int s_mp_sqr (mp_int * a, mp_int * b) -019 \{ -020 mp_int t; -021 int res, ix, iy, pa; -022 mp_word r; -023 mp_digit u, tmpx, *tmpt; -024 -025 pa = a->used; -026 if ((res = mp_init_size (&t, (2 * pa) + 1)) != MP_OKAY) \{ -027 return res; -028 \} -029 -030 /* default used is maximum possible size */ -031 t.used = (2 * pa) + 1; -032 -033 for (ix = 0; ix < pa; ix++) \{ -034 /* first calculate the digit at 2*ix */ -035 /* calculate double precision result */ -036 r = (mp_word)t.dp[2*ix] + -037 ((mp_word)a->dp[ix] * (mp_word)a->dp[ix]); -038 -039 /* store lower part in result */ -040 t.dp[ix+ix] = (mp_digit) (r & ((mp_word) MP_MASK)); -041 -042 /* get the carry */ -043 u = (mp_digit)(r >> ((mp_word) DIGIT_BIT)); -044 -045 /* left hand side of A[ix] * A[iy] */ -046 tmpx = a->dp[ix]; -047 -048 /* alias for where to store the results */ -049 tmpt = t.dp + ((2 * ix) + 1); -050 -051 for (iy = ix + 1; iy < pa; iy++) \{ -052 /* first calculate the product */ -053 r = ((mp_word)tmpx) * ((mp_word)a->dp[iy]); -054 -055 /* now calculate the double precision result, note we use -056 * addition instead of *2 since it's easier to optimize -057 */ -058 r = ((mp_word) *tmpt) + r + r + ((mp_word) u); -059 -060 /* store lower part */ -061 *tmpt++ = (mp_digit) (r & ((mp_word) MP_MASK)); -062 -063 /* get carry */ -064 u = (mp_digit)(r >> ((mp_word) DIGIT_BIT)); -065 \} -066 /* propagate upwards */ -067 while (u != ((mp_digit) 0)) \{ -068 r = ((mp_word) *tmpt) + ((mp_word) u); -069 *tmpt++ = (mp_digit) (r & ((mp_word) MP_MASK)); -070 u = (mp_digit)(r >> ((mp_word) DIGIT_BIT)); -071 \} -072 \} -073 -074 mp_clamp (&t); -075 mp_exch (&t, b); -076 mp_clear (&t); -077 return MP_OKAY; -078 \} -079 #endif -080 -\end{alltt} -\end{small} - -Inside the outer loop (line 33) the square term is calculated on line 36. The carry (line 43) has been -extracted from the mp\_word accumulator using a right shift. Aliases for $a_{ix}$ and $t_{ix+iy}$ are initialized -(lines 46 and 49) to simplify the inner loop. The doubling is performed using two -additions (line 58) since it is usually faster than shifting, if not at least as fast. - -The important observation is that the inner loop does not begin at $iy = 0$ like for multiplication. As such the inner loops -get progressively shorter as the algorithm proceeds. This is what leads to the savings compared to using a multiplication to -square a number. - -\subsection{Faster Squaring by the ``Comba'' Method} -A major drawback to the baseline method is the requirement for single precision shifting inside the $O(n^2)$ nested loop. Squaring has an additional -drawback that it must double the product inside the inner loop as well. As for multiplication, the Comba technique can be used to eliminate these -performance hazards. - -The first obvious solution is to make an array of mp\_words which will hold all of the columns. This will indeed eliminate all of the carry -propagation operations from the inner loop. However, the inner product must still be doubled $O(n^2)$ times. The solution stems from the simple fact -that $2a + 2b + 2c = 2(a + b + c)$. That is the sum of all of the double products is equal to double the sum of all the products. For example, -$ab + ba + ac + ca = 2ab + 2ac = 2(ab + ac)$. - -However, we cannot simply double all of the columns, since the squares appear only once per row. The most practical solution is to have two -mp\_word arrays. One array will hold the squares and the other array will hold the double products. With both arrays the doubling and -carry propagation can be moved to a $O(n)$ work level outside the $O(n^2)$ level. In this case, we have an even simpler solution in mind. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{fast\_s\_mp\_sqr}. \\ -\textbf{Input}. mp\_int $a$ \\ -\textbf{Output}. $b \leftarrow a^2$ \\ -\hline \\ -Place an array of \textbf{MP\_WARRAY} mp\_digits named $W$ on the stack. \\ -1. If $b.alloc < 2a.used + 1$ then grow $b$ to $2a.used + 1$ digits. (\textit{mp\_grow}). \\ -2. If step 1 failed return(\textit{MP\_MEM}). \\ -\\ -3. $pa \leftarrow 2 \cdot a.used$ \\ -4. $\hat W1 \leftarrow 0$ \\ -5. for $ix$ from $0$ to $pa - 1$ do \\ -\hspace{3mm}5.1 $\_ \hat W \leftarrow 0$ \\ -\hspace{3mm}5.2 $ty \leftarrow \mbox{MIN}(a.used - 1, ix)$ \\ -\hspace{3mm}5.3 $tx \leftarrow ix - ty$ \\ -\hspace{3mm}5.4 $iy \leftarrow \mbox{MIN}(a.used - tx, ty + 1)$ \\ -\hspace{3mm}5.5 $iy \leftarrow \mbox{MIN}(iy, \lfloor \left (ty - tx + 1 \right )/2 \rfloor)$ \\ -\hspace{3mm}5.6 for $iz$ from $0$ to $iz - 1$ do \\ -\hspace{6mm}5.6.1 $\_ \hat W \leftarrow \_ \hat W + a_{tx + iz}a_{ty - iz}$ \\ -\hspace{3mm}5.7 $\_ \hat W \leftarrow 2 \cdot \_ \hat W + \hat W1$ \\ -\hspace{3mm}5.8 if $ix$ is even then \\ -\hspace{6mm}5.8.1 $\_ \hat W \leftarrow \_ \hat W + \left ( a_{\lfloor ix/2 \rfloor}\right )^2$ \\ -\hspace{3mm}5.9 $W_{ix} \leftarrow \_ \hat W (\mbox{mod }\beta)$ \\ -\hspace{3mm}5.10 $\hat W1 \leftarrow \lfloor \_ \hat W / \beta \rfloor$ \\ -\\ -6. $oldused \leftarrow b.used$ \\ -7. $b.used \leftarrow 2 \cdot a.used$ \\ -8. for $ix$ from $0$ to $pa - 1$ do \\ -\hspace{3mm}8.1 $b_{ix} \leftarrow W_{ix}$ \\ -9. for $ix$ from $pa$ to $oldused - 1$ do \\ -\hspace{3mm}9.1 $b_{ix} \leftarrow 0$ \\ -10. Clamp excess digits from $b$. (\textit{mp\_clamp}) \\ -11. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm fast\_s\_mp\_sqr} -\end{figure} - -\textbf{Algorithm fast\_s\_mp\_sqr.} -This algorithm computes the square of an input using the Comba technique. It is designed to be a replacement for algorithm -s\_mp\_sqr when the number of input digits is less than \textbf{MP\_WARRAY} and less than $\delta \over 2$. -This algorithm is very similar to the Comba multiplier except with a few key differences we shall make note of. - -First, we have an accumulator and carry variables $\_ \hat W$ and $\hat W1$ respectively. This is because the inner loop -products are to be doubled. If we had added the previous carry in we would be doubling too much. Next we perform an -addition MIN condition on $iy$ (step 5.5) to prevent overlapping digits. For example, $a_3 \cdot a_5$ is equal -$a_5 \cdot a_3$. Whereas in the multiplication case we would have $5 < a.used$ and $3 \ge 0$ is maintained since we double the sum -of the products just outside the inner loop we have to avoid doing this. This is also a good thing since we perform -fewer multiplications and the routine ends up being faster. - -Finally the last difference is the addition of the ``square'' term outside the inner loop (step 5.8). We add in the square -only to even outputs and it is the square of the term at the $\lfloor ix / 2 \rfloor$ position. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_fast\_s\_mp\_sqr.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* the jist of squaring... -018 * you do like mult except the offset of the tmpx [one that -019 * starts closer to zero] can't equal the offset of tmpy. -020 * So basically you set up iy like before then you min it with -021 * (ty-tx) so that it never happens. You double all those -022 * you add in the inner loop -023 -024 After that loop you do the squares and add them in. -025 */ -026 -027 int fast_s_mp_sqr (mp_int * a, mp_int * b) -028 \{ -029 int olduse, res, pa, ix, iz; -030 mp_digit W[MP_WARRAY], *tmpx; -031 mp_word W1; -032 -033 /* grow the destination as required */ -034 pa = a->used + a->used; -035 if (b->alloc < pa) \{ -036 if ((res = mp_grow (b, pa)) != MP_OKAY) \{ -037 return res; -038 \} -039 \} -040 -041 /* number of output digits to produce */ -042 W1 = 0; -043 for (ix = 0; ix < pa; ix++) \{ -044 int tx, ty, iy; -045 mp_word _W; -046 mp_digit *tmpy; -047 -048 /* clear counter */ -049 _W = 0; -050 -051 /* get offsets into the two bignums */ -052 ty = MIN(a->used-1, ix); -053 tx = ix - ty; -054 -055 /* setup temp aliases */ -056 tmpx = a->dp + tx; -057 tmpy = a->dp + ty; -058 -059 /* this is the number of times the loop will iterrate, essentially -060 while (tx++ < a->used && ty-- >= 0) \{ ... \} -061 */ -062 iy = MIN(a->used-tx, ty+1); -063 -064 /* now for squaring tx can never equal ty -065 * we halve the distance since they approach at a rate of 2x -066 * and we have to round because odd cases need to be executed -067 */ -068 iy = MIN(iy, ((ty-tx)+1)>>1); -069 -070 /* execute loop */ -071 for (iz = 0; iz < iy; iz++) \{ -072 _W += ((mp_word)*tmpx++)*((mp_word)*tmpy--); -073 \} -074 -075 /* double the inner product and add carry */ -076 _W = _W + _W + W1; -077 -078 /* even columns have the square term in them */ -079 if ((ix&1) == 0) \{ -080 _W += ((mp_word)a->dp[ix>>1])*((mp_word)a->dp[ix>>1]); -081 \} -082 -083 /* store it */ -084 W[ix] = (mp_digit)(_W & MP_MASK); -085 -086 /* make next carry */ -087 W1 = _W >> ((mp_word)DIGIT_BIT); -088 \} -089 -090 /* setup dest */ -091 olduse = b->used; -092 b->used = a->used+a->used; -093 -094 \{ -095 mp_digit *tmpb; -096 tmpb = b->dp; -097 for (ix = 0; ix < pa; ix++) \{ -098 *tmpb++ = W[ix] & MP_MASK; -099 \} -100 -101 /* clear unused digits [that existed in the old copy of c] */ -102 for (; ix < olduse; ix++) \{ -103 *tmpb++ = 0; -104 \} -105 \} -106 mp_clamp (b); -107 return MP_OKAY; -108 \} -109 #endif -110 -\end{alltt} -\end{small} - -This implementation is essentially a copy of Comba multiplication with the appropriate changes added to make it faster for -the special case of squaring. - -\subsection{Polynomial Basis Squaring} -The same algorithm that performs optimal polynomial basis multiplication can be used to perform polynomial basis squaring. The minor exception -is that $\zeta_y = f(y)g(y)$ is actually equivalent to $\zeta_y = f(y)^2$ since $f(y) = g(y)$. Instead of performing $2n + 1$ -multiplications to find the $\zeta$ relations, squaring operations are performed instead. - -\subsection{Karatsuba Squaring} -Let $f(x) = ax + b$ represent the polynomial basis representation of a number to square. -Let $h(x) = \left ( f(x) \right )^2$ represent the square of the polynomial. The Karatsuba equation can be modified to square a -number with the following equation. - -\begin{equation} -h(x) = a^2x^2 + \left ((a + b)^2 - (a^2 + b^2) \right )x + b^2 -\end{equation} - -Upon closer inspection this equation only requires the calculation of three half-sized squares: $a^2$, $b^2$ and $(a + b)^2$. As in -Karatsuba multiplication, this algorithm can be applied recursively on the input and will achieve an asymptotic running time of -$O \left ( n^{lg(3)} \right )$. - -If the asymptotic times of Karatsuba squaring and multiplication are the same, why not simply use the multiplication algorithm -instead? The answer to this arises from the cutoff point for squaring. As in multiplication there exists a cutoff point, at which the -time required for a Comba based squaring and a Karatsuba based squaring meet. Due to the overhead inherent in the Karatsuba method, the cutoff -point is fairly high. For example, on an AMD Athlon XP processor with $\beta = 2^{28}$, the cutoff point is around 127 digits. - -Consider squaring a 200 digit number with this technique. It will be split into two 100 digit halves which are subsequently squared. -The 100 digit halves will not be squared using Karatsuba, but instead using the faster Comba based squaring algorithm. If Karatsuba multiplication -were used instead, the 100 digit numbers would be squared with a slower Comba based multiplication. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_karatsuba\_sqr}. \\ -\textbf{Input}. mp\_int $a$ \\ -\textbf{Output}. $b \leftarrow a^2$ \\ -\hline \\ -1. Initialize the following temporary mp\_ints: $x0$, $x1$, $t1$, $t2$, $x0x0$ and $x1x1$. \\ -2. If any of the initializations on step 1 failed return(\textit{MP\_MEM}). \\ -\\ -Split the input. e.g. $a = x1\beta^B + x0$ \\ -3. $B \leftarrow \lfloor a.used / 2 \rfloor$ \\ -4. $x0 \leftarrow a \mbox{ (mod }\beta^B\mbox{)}$ (\textit{mp\_mod\_2d}) \\ -5. $x1 \leftarrow \lfloor a / \beta^B \rfloor$ (\textit{mp\_lshd}) \\ -\\ -Calculate the three squares. \\ -6. $x0x0 \leftarrow x0^2$ (\textit{mp\_sqr}) \\ -7. $x1x1 \leftarrow x1^2$ \\ -8. $t1 \leftarrow x1 + x0$ (\textit{s\_mp\_add}) \\ -9. $t1 \leftarrow t1^2$ \\ -\\ -Compute the middle term. \\ -10. $t2 \leftarrow x0x0 + x1x1$ (\textit{s\_mp\_add}) \\ -11. $t1 \leftarrow t1 - t2$ \\ -\\ -Compute final product. \\ -12. $t1 \leftarrow t1\beta^B$ (\textit{mp\_lshd}) \\ -13. $x1x1 \leftarrow x1x1\beta^{2B}$ \\ -14. $t1 \leftarrow t1 + x0x0$ \\ -15. $b \leftarrow t1 + x1x1$ \\ -16. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_karatsuba\_sqr} -\end{figure} - -\textbf{Algorithm mp\_karatsuba\_sqr.} -This algorithm computes the square of an input $a$ using the Karatsuba technique. This algorithm is very similar to the Karatsuba based -multiplication algorithm with the exception that the three half-size multiplications have been replaced with three half-size squarings. - -The radix point for squaring is simply placed exactly in the middle of the digits when the input has an odd number of digits, otherwise it is -placed just below the middle. Step 3, 4 and 5 compute the two halves required using $B$ -as the radix point. The first two squares in steps 6 and 7 are rather straightforward while the last square is of a more compact form. - -By expanding $\left (x1 + x0 \right )^2$, the $x1^2$ and $x0^2$ terms in the middle disappear, that is $(x0 - x1)^2 - (x1^2 + x0^2) = 2 \cdot x0 \cdot x1$. -Now if $5n$ single precision additions and a squaring of $n$-digits is faster than multiplying two $n$-digit numbers and doubling then -this method is faster. Assuming no further recursions occur, the difference can be estimated with the following inequality. - -Let $p$ represent the cost of a single precision addition and $q$ the cost of a single precision multiplication both in terms of time\footnote{Or -machine clock cycles.}. - -\begin{equation} -5pn +{{q(n^2 + n)} \over 2} \le pn + qn^2 -\end{equation} - -For example, on an AMD Athlon XP processor $p = {1 \over 3}$ and $q = 6$. This implies that the following inequality should hold. -\begin{center} -\begin{tabular}{rcl} -${5n \over 3} + 3n^2 + 3n$ & $<$ & ${n \over 3} + 6n^2$ \\ -${5 \over 3} + 3n + 3$ & $<$ & ${1 \over 3} + 6n$ \\ -${13 \over 9}$ & $<$ & $n$ \\ -\end{tabular} -\end{center} - -This results in a cutoff point around $n = 2$. As a consequence it is actually faster to compute the middle term the ``long way'' on processors -where multiplication is substantially slower\footnote{On the Athlon there is a 1:17 ratio between clock cycles for addition and multiplication. On -the Intel P4 processor this ratio is 1:29 making this method even more beneficial. The only common exception is the ARMv4 processor which has a -ratio of 1:7. } than simpler operations such as addition. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_karatsuba\_sqr.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* Karatsuba squaring, computes b = a*a using three -018 * half size squarings -019 * -020 * See comments of karatsuba_mul for details. It -021 * is essentially the same algorithm but merely -022 * tuned to perform recursive squarings. -023 */ -024 int mp_karatsuba_sqr (mp_int * a, mp_int * b) -025 \{ -026 mp_int x0, x1, t1, t2, x0x0, x1x1; -027 int B, err; -028 -029 err = MP_MEM; -030 -031 /* min # of digits */ -032 B = a->used; -033 -034 /* now divide in two */ -035 B = B >> 1; -036 -037 /* init copy all the temps */ -038 if (mp_init_size (&x0, B) != MP_OKAY) -039 goto ERR; -040 if (mp_init_size (&x1, a->used - B) != MP_OKAY) -041 goto X0; -042 -043 /* init temps */ -044 if (mp_init_size (&t1, a->used * 2) != MP_OKAY) -045 goto X1; -046 if (mp_init_size (&t2, a->used * 2) != MP_OKAY) -047 goto T1; -048 if (mp_init_size (&x0x0, B * 2) != MP_OKAY) -049 goto T2; -050 if (mp_init_size (&x1x1, (a->used - B) * 2) != MP_OKAY) -051 goto X0X0; -052 -053 \{ -054 int x; -055 mp_digit *dst, *src; -056 -057 src = a->dp; -058 -059 /* now shift the digits */ -060 dst = x0.dp; -061 for (x = 0; x < B; x++) \{ -062 *dst++ = *src++; -063 \} -064 -065 dst = x1.dp; -066 for (x = B; x < a->used; x++) \{ -067 *dst++ = *src++; -068 \} -069 \} -070 -071 x0.used = B; -072 x1.used = a->used - B; -073 -074 mp_clamp (&x0); -075 -076 /* now calc the products x0*x0 and x1*x1 */ -077 if (mp_sqr (&x0, &x0x0) != MP_OKAY) -078 goto X1X1; /* x0x0 = x0*x0 */ -079 if (mp_sqr (&x1, &x1x1) != MP_OKAY) -080 goto X1X1; /* x1x1 = x1*x1 */ -081 -082 /* now calc (x1+x0)**2 */ -083 if (s_mp_add (&x1, &x0, &t1) != MP_OKAY) -084 goto X1X1; /* t1 = x1 - x0 */ -085 if (mp_sqr (&t1, &t1) != MP_OKAY) -086 goto X1X1; /* t1 = (x1 - x0) * (x1 - x0) */ -087 -088 /* add x0y0 */ -089 if (s_mp_add (&x0x0, &x1x1, &t2) != MP_OKAY) -090 goto X1X1; /* t2 = x0x0 + x1x1 */ -091 if (s_mp_sub (&t1, &t2, &t1) != MP_OKAY) -092 goto X1X1; /* t1 = (x1+x0)**2 - (x0x0 + x1x1) */ -093 -094 /* shift by B */ -095 if (mp_lshd (&t1, B) != MP_OKAY) -096 goto X1X1; /* t1 = (x0x0 + x1x1 - (x1-x0)*(x1-x0))<<B */ -097 if (mp_lshd (&x1x1, B * 2) != MP_OKAY) -098 goto X1X1; /* x1x1 = x1x1 << 2*B */ -099 -100 if (mp_add (&x0x0, &t1, &t1) != MP_OKAY) -101 goto X1X1; /* t1 = x0x0 + t1 */ -102 if (mp_add (&t1, &x1x1, b) != MP_OKAY) -103 goto X1X1; /* t1 = x0x0 + t1 + x1x1 */ -104 -105 err = MP_OKAY; -106 -107 X1X1:mp_clear (&x1x1); -108 X0X0:mp_clear (&x0x0); -109 T2:mp_clear (&t2); -110 T1:mp_clear (&t1); -111 X1:mp_clear (&x1); -112 X0:mp_clear (&x0); -113 ERR: -114 return err; -115 \} -116 #endif -117 -\end{alltt} -\end{small} - -This implementation is largely based on the implementation of algorithm mp\_karatsuba\_mul. It uses the same inline style to copy and -shift the input into the two halves. The loop from line 53 to line 69 has been modified since only one input exists. The \textbf{used} -count of both $x0$ and $x1$ is fixed up and $x0$ is clamped before the calculations begin. At this point $x1$ and $x0$ are valid equivalents -to the respective halves as if mp\_rshd and mp\_mod\_2d had been used. - -By inlining the copy and shift operations the cutoff point for Karatsuba multiplication can be lowered. On the Athlon the cutoff point -is exactly at the point where Comba squaring can no longer be used (\textit{128 digits}). On slower processors such as the Intel P4 -it is actually below the Comba limit (\textit{at 110 digits}). - -This routine uses the same error trap coding style as mp\_karatsuba\_sqr. As the temporary variables are initialized errors are -redirected to the error trap higher up. If the algorithm completes without error the error code is set to \textbf{MP\_OKAY} and -mp\_clears are executed normally. - -\subsection{Toom-Cook Squaring} -The Toom-Cook squaring algorithm mp\_toom\_sqr is heavily based on the algorithm mp\_toom\_mul with the exception that squarings are used -instead of multiplication to find the five relations. The reader is encouraged to read the description of the latter algorithm and try to -derive their own Toom-Cook squaring algorithm. - -\subsection{High Level Squaring} -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_sqr}. \\ -\textbf{Input}. mp\_int $a$ \\ -\textbf{Output}. $b \leftarrow a^2$ \\ -\hline \\ -1. If $a.used \ge TOOM\_SQR\_CUTOFF$ then \\ -\hspace{3mm}1.1 $b \leftarrow a^2$ using algorithm mp\_toom\_sqr \\ -2. else if $a.used \ge KARATSUBA\_SQR\_CUTOFF$ then \\ -\hspace{3mm}2.1 $b \leftarrow a^2$ using algorithm mp\_karatsuba\_sqr \\ -3. else \\ -\hspace{3mm}3.1 $digs \leftarrow a.used + b.used + 1$ \\ -\hspace{3mm}3.2 If $digs < MP\_ARRAY$ and $a.used \le \delta$ then \\ -\hspace{6mm}3.2.1 $b \leftarrow a^2$ using algorithm fast\_s\_mp\_sqr. \\ -\hspace{3mm}3.3 else \\ -\hspace{6mm}3.3.1 $b \leftarrow a^2$ using algorithm s\_mp\_sqr. \\ -4. $b.sign \leftarrow MP\_ZPOS$ \\ -5. Return the result of the unsigned squaring performed. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_sqr} -\end{figure} - -\textbf{Algorithm mp\_sqr.} -This algorithm computes the square of the input using one of four different algorithms. If the input is very large and has at least -\textbf{TOOM\_SQR\_CUTOFF} or \textbf{KARATSUBA\_SQR\_CUTOFF} digits then either the Toom-Cook or the Karatsuba Squaring algorithm is used. If -neither of the polynomial basis algorithms should be used then either the Comba or baseline algorithm is used. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_sqr.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* computes b = a*a */ -018 int -019 mp_sqr (mp_int * a, mp_int * b) -020 \{ -021 int res; -022 -023 #ifdef BN_MP_TOOM_SQR_C -024 /* use Toom-Cook? */ -025 if (a->used >= TOOM_SQR_CUTOFF) \{ -026 res = mp_toom_sqr(a, b); -027 /* Karatsuba? */ -028 \} else -029 #endif -030 #ifdef BN_MP_KARATSUBA_SQR_C -031 if (a->used >= KARATSUBA_SQR_CUTOFF) \{ -032 res = mp_karatsuba_sqr (a, b); -033 \} else -034 #endif -035 \{ -036 #ifdef BN_FAST_S_MP_SQR_C -037 /* can we use the fast comba multiplier? */ -038 if ((((a->used * 2) + 1) < MP_WARRAY) && -039 (a->used < -040 (1 << (((sizeof(mp_word) * CHAR_BIT) - (2 * DIGIT_BIT)) - 1)))) \{ -041 res = fast_s_mp_sqr (a, b); -042 \} else -043 #endif -044 \{ -045 #ifdef BN_S_MP_SQR_C -046 res = s_mp_sqr (a, b); -047 #else -048 res = MP_VAL; -049 #endif -050 \} -051 \} -052 b->sign = MP_ZPOS; -053 return res; -054 \} -055 #endif -056 -\end{alltt} -\end{small} - -\section*{Exercises} -\begin{tabular}{cl} -$\left [ 3 \right ] $ & Devise an efficient algorithm for selection of the radix point to handle inputs \\ - & that have different number of digits in Karatsuba multiplication. \\ - & \\ -$\left [ 2 \right ] $ & In section 5.3 the fact that every column of a squaring is made up \\ - & of double products and at most one square is stated. Prove this statement. \\ - & \\ -$\left [ 3 \right ] $ & Prove the equation for Karatsuba squaring. \\ - & \\ -$\left [ 1 \right ] $ & Prove that Karatsuba squaring requires $O \left (n^{lg(3)} \right )$ time. \\ - & \\ -$\left [ 2 \right ] $ & Determine the minimal ratio between addition and multiplication clock cycles \\ - & required for equation $6.7$ to be true. \\ - & \\ -$\left [ 3 \right ] $ & Implement a threaded version of Comba multiplication (and squaring) where you \\ - & compute subsets of the columns in each thread. Determine a cutoff point where \\ - & it is effective and add the logic to mp\_mul() and mp\_sqr(). \\ - &\\ -$\left [ 4 \right ] $ & Same as the previous but also modify the Karatsuba and Toom-Cook. You must \\ - & increase the throughput of mp\_exptmod() for random odd moduli in the range \\ - & $512 \ldots 4096$ bits significantly ($> 2x$) to complete this challenge. \\ - & \\ -\end{tabular} - -\chapter{Modular Reduction} -\section{Basics of Modular Reduction} -\index{modular residue} -Modular reduction is an operation that arises quite often within public key cryptography algorithms and various number theoretic algorithms, -such as factoring. Modular reduction algorithms are the third class of algorithms of the ``multipliers'' set. A number $a$ is said to be \textit{reduced} -modulo another number $b$ by finding the remainder of the division $a/b$. Full integer division with remainder is a topic to be covered -in~\ref{sec:division}. - -Modular reduction is equivalent to solving for $r$ in the following equation. $a = bq + r$ where $q = \lfloor a/b \rfloor$. The result -$r$ is said to be ``congruent to $a$ modulo $b$'' which is also written as $r \equiv a \mbox{ (mod }b\mbox{)}$. In other vernacular $r$ is known as the -``modular residue'' which leads to ``quadratic residue''\footnote{That's fancy talk for $b \equiv a^2 \mbox{ (mod }p\mbox{)}$.} and -other forms of residues. - -Modular reductions are normally used to create either finite groups, rings or fields. The most common usage for performance driven modular reductions -is in modular exponentiation algorithms. That is to compute $d = a^b \mbox{ (mod }c\mbox{)}$ as fast as possible. This operation is used in the -RSA and Diffie-Hellman public key algorithms, for example. Modular multiplication and squaring also appears as a fundamental operation in -elliptic curve cryptographic algorithms. As will be discussed in the subsequent chapter there exist fast algorithms for computing modular -exponentiations without having to perform (\textit{in this example}) $b - 1$ multiplications. These algorithms will produce partial results in the -range $0 \le x < c^2$ which can be taken advantage of to create several efficient algorithms. They have also been used to create redundancy check -algorithms known as CRCs, error correction codes such as Reed-Solomon and solve a variety of number theoeretic problems. - -\section{The Barrett Reduction} -The Barrett reduction algorithm \cite{BARRETT} was inspired by fast division algorithms which multiply by the reciprocal to emulate -division. Barretts observation was that the residue $c$ of $a$ modulo $b$ is equal to - -\begin{equation} -c = a - b \cdot \lfloor a/b \rfloor -\end{equation} - -Since algorithms such as modular exponentiation would be using the same modulus extensively, typical DSP\footnote{It is worth noting that Barrett's paper -targeted the DSP56K processor.} intuition would indicate the next step would be to replace $a/b$ by a multiplication by the reciprocal. However, -DSP intuition on its own will not work as these numbers are considerably larger than the precision of common DSP floating point data types. -It would take another common optimization to optimize the algorithm. - -\subsection{Fixed Point Arithmetic} -The trick used to optimize the above equation is based on a technique of emulating floating point data types with fixed precision integers. Fixed -point arithmetic would become very popular as it greatly optimize the ``3d-shooter'' genre of games in the mid 1990s when floating point units were -fairly slow if not unavailable. The idea behind fixed point arithmetic is to take a normal $k$-bit integer data type and break it into $p$-bit -integer and a $q$-bit fraction part (\textit{where $p+q = k$}). - -In this system a $k$-bit integer $n$ would actually represent $n/2^q$. For example, with $q = 4$ the integer $n = 37$ would actually represent the -value $2.3125$. To multiply two fixed point numbers the integers are multiplied using traditional arithmetic and subsequently normalized by -moving the implied decimal point back to where it should be. For example, with $q = 4$ to multiply the integers $9$ and $5$ they must be converted -to fixed point first by multiplying by $2^q$. Let $a = 9(2^q)$ represent the fixed point representation of $9$ and $b = 5(2^q)$ represent the -fixed point representation of $5$. The product $ab$ is equal to $45(2^{2q})$ which when normalized by dividing by $2^q$ produces $45(2^q)$. - -This technique became popular since a normal integer multiplication and logical shift right are the only required operations to perform a multiplication -of two fixed point numbers. Using fixed point arithmetic, division can be easily approximated by multiplying by the reciprocal. If $2^q$ is -equivalent to one than $2^q/b$ is equivalent to the fixed point approximation of $1/b$ using real arithmetic. Using this fact dividing an integer -$a$ by another integer $b$ can be achieved with the following expression. - -\begin{equation} -\lfloor a / b \rfloor \mbox{ }\approx\mbox{ } \lfloor (a \cdot \lfloor 2^q / b \rfloor)/2^q \rfloor -\end{equation} - -The precision of the division is proportional to the value of $q$. If the divisor $b$ is used frequently as is the case with -modular exponentiation pre-computing $2^q/b$ will allow a division to be performed with a multiplication and a right shift. Both operations -are considerably faster than division on most processors. - -Consider dividing $19$ by $5$. The correct result is $\lfloor 19/5 \rfloor = 3$. With $q = 3$ the reciprocal is $\lfloor 2^q/5 \rfloor = 1$ which -leads to a product of $19$ which when divided by $2^q$ produces $2$. However, with $q = 4$ the reciprocal is $\lfloor 2^q/5 \rfloor = 3$ and -the result of the emulated division is $\lfloor 3 \cdot 19 / 2^q \rfloor = 3$ which is correct. The value of $2^q$ must be close to or ideally -larger than the dividend. In effect if $a$ is the dividend then $q$ should allow $0 \le \lfloor a/2^q \rfloor \le 1$ in order for this approach -to work correctly. Plugging this form of divison into the original equation the following modular residue equation arises. - -\begin{equation} -c = a - b \cdot \lfloor (a \cdot \lfloor 2^q / b \rfloor)/2^q \rfloor -\end{equation} - -Using the notation from \cite{BARRETT} the value of $\lfloor 2^q / b \rfloor$ will be represented by the $\mu$ symbol. Using the $\mu$ -variable also helps re-inforce the idea that it is meant to be computed once and re-used. - -\begin{equation} -c = a - b \cdot \lfloor (a \cdot \mu)/2^q \rfloor -\end{equation} - -Provided that $2^q \ge a$ this algorithm will produce a quotient that is either exactly correct or off by a value of one. In the context of Barrett -reduction the value of $a$ is bound by $0 \le a \le (b - 1)^2$ meaning that $2^q \ge b^2$ is sufficient to ensure the reciprocal will have enough -precision. - -Let $n$ represent the number of digits in $b$. This algorithm requires approximately $2n^2$ single precision multiplications to produce the quotient and -another $n^2$ single precision multiplications to find the residue. In total $3n^2$ single precision multiplications are required to -reduce the number. - -For example, if $b = 1179677$ and $q = 41$ ($2^q > b^2$), then the reciprocal $\mu$ is equal to $\lfloor 2^q / b \rfloor = 1864089$. Consider reducing -$a = 180388626447$ modulo $b$ using the above reduction equation. The quotient using the new formula is $\lfloor (a \cdot \mu) / 2^q \rfloor = 152913$. -By subtracting $152913b$ from $a$ the correct residue $a \equiv 677346 \mbox{ (mod }b\mbox{)}$ is found. - -\subsection{Choosing a Radix Point} -Using the fixed point representation a modular reduction can be performed with $3n^2$ single precision multiplications. If that were the best -that could be achieved a full division\footnote{A division requires approximately $O(2cn^2)$ single precision multiplications for a small value of $c$. -See~\ref{sec:division} for further details.} might as well be used in its place. The key to optimizing the reduction is to reduce the precision of -the initial multiplication that finds the quotient. - -Let $a$ represent the number of which the residue is sought. Let $b$ represent the modulus used to find the residue. Let $m$ represent -the number of digits in $b$. For the purposes of this discussion we will assume that the number of digits in $a$ is $2m$, which is generally true if -two $m$-digit numbers have been multiplied. Dividing $a$ by $b$ is the same as dividing a $2m$ digit integer by a $m$ digit integer. Digits below the -$m - 1$'th digit of $a$ will contribute at most a value of $1$ to the quotient because $\beta^k < b$ for any $0 \le k \le m - 1$. Another way to -express this is by re-writing $a$ as two parts. If $a' \equiv a \mbox{ (mod }b^m\mbox{)}$ and $a'' = a - a'$ then -${a \over b} \equiv {{a' + a''} \over b}$ which is equivalent to ${a' \over b} + {a'' \over b}$. Since $a'$ is bound to be less than $b$ the quotient -is bound by $0 \le {a' \over b} < 1$. - -Since the digits of $a'$ do not contribute much to the quotient the observation is that they might as well be zero. However, if the digits -``might as well be zero'' they might as well not be there in the first place. Let $q_0 = \lfloor a/\beta^{m-1} \rfloor$ represent the input -with the irrelevant digits trimmed. Now the modular reduction is trimmed to the almost equivalent equation - -\begin{equation} -c = a - b \cdot \lfloor (q_0 \cdot \mu) / \beta^{m+1} \rfloor -\end{equation} - -Note that the original divisor $2^q$ has been replaced with $\beta^{m+1}$ where in this case $q$ is a multiple of $lg(\beta)$. Also note that the -exponent on the divisor when added to the amount $q_0$ was shifted by equals $2m$. If the optimization had not been performed the divisor -would have the exponent $2m$ so in the end the exponents do ``add up''. Using the above equation the quotient -$\lfloor (q_0 \cdot \mu) / \beta^{m+1} \rfloor$ can be off from the true quotient by at most two. The original fixed point quotient can be off -by as much as one (\textit{provided the radix point is chosen suitably}) and now that the lower irrelevent digits have been trimmed the quotient -can be off by an additional value of one for a total of at most two. This implies that -$0 \le a - b \cdot \lfloor (q_0 \cdot \mu) / \beta^{m+1} \rfloor < 3b$. By first subtracting $b$ times the quotient and then conditionally subtracting -$b$ once or twice the residue is found. - -The quotient is now found using $(m + 1)(m) = m^2 + m$ single precision multiplications and the residue with an additional $m^2$ single -precision multiplications, ignoring the subtractions required. In total $2m^2 + m$ single precision multiplications are required to find the residue. -This is considerably faster than the original attempt. - -For example, let $\beta = 10$ represent the radix of the digits. Let $b = 9999$ represent the modulus which implies $m = 4$. Let $a = 99929878$ -represent the value of which the residue is desired. In this case $q = 8$ since $10^7 < 9999^2$ meaning that $\mu = \lfloor \beta^{q}/b \rfloor = 10001$. -With the new observation the multiplicand for the quotient is equal to $q_0 = \lfloor a / \beta^{m - 1} \rfloor = 99929$. The quotient is then -$\lfloor (q_0 \cdot \mu) / \beta^{m+1} \rfloor = 9993$. Subtracting $9993b$ from $a$ and the correct residue $a \equiv 9871 \mbox{ (mod }b\mbox{)}$ -is found. - -\subsection{Trimming the Quotient} -So far the reduction algorithm has been optimized from $3m^2$ single precision multiplications down to $2m^2 + m$ single precision multiplications. As -it stands now the algorithm is already fairly fast compared to a full integer division algorithm. However, there is still room for -optimization. - -After the first multiplication inside the quotient ($q_0 \cdot \mu$) the value is shifted right by $m + 1$ places effectively nullifying the lower -half of the product. It would be nice to be able to remove those digits from the product to effectively cut down the number of single precision -multiplications. If the number of digits in the modulus $m$ is far less than $\beta$ a full product is not required for the algorithm to work properly. -In fact the lower $m - 2$ digits will not affect the upper half of the product at all and do not need to be computed. - -The value of $\mu$ is a $m$-digit number and $q_0$ is a $m + 1$ digit number. Using a full multiplier $(m + 1)(m) = m^2 + m$ single precision -multiplications would be required. Using a multiplier that will only produce digits at and above the $m - 1$'th digit reduces the number -of single precision multiplications to ${m^2 + m} \over 2$ single precision multiplications. - -\subsection{Trimming the Residue} -After the quotient has been calculated it is used to reduce the input. As previously noted the algorithm is not exact and it can be off by a small -multiple of the modulus, that is $0 \le a - b \cdot \lfloor (q_0 \cdot \mu) / \beta^{m+1} \rfloor < 3b$. If $b$ is $m$ digits than the -result of reduction equation is a value of at most $m + 1$ digits (\textit{provided $3 < \beta$}) implying that the upper $m - 1$ digits are -implicitly zero. - -The next optimization arises from this very fact. Instead of computing $b \cdot \lfloor (q_0 \cdot \mu) / \beta^{m+1} \rfloor$ using a full -$O(m^2)$ multiplication algorithm only the lower $m+1$ digits of the product have to be computed. Similarly the value of $a$ can -be reduced modulo $\beta^{m+1}$ before the multiple of $b$ is subtracted which simplifes the subtraction as well. A multiplication that produces -only the lower $m+1$ digits requires ${m^2 + 3m - 2} \over 2$ single precision multiplications. - -With both optimizations in place the algorithm is the algorithm Barrett proposed. It requires $m^2 + 2m - 1$ single precision multiplications which -is considerably faster than the straightforward $3m^2$ method. - -\subsection{The Barrett Algorithm} -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_reduce}. \\ -\textbf{Input}. mp\_int $a$, mp\_int $b$ and $\mu = \lfloor \beta^{2m}/b \rfloor, m = \lceil lg_{\beta}(b) \rceil, (0 \le a < b^2, b > 1)$ \\ -\textbf{Output}. $a \mbox{ (mod }b\mbox{)}$ \\ -\hline \\ -Let $m$ represent the number of digits in $b$. \\ -1. Make a copy of $a$ and store it in $q$. (\textit{mp\_init\_copy}) \\ -2. $q \leftarrow \lfloor q / \beta^{m - 1} \rfloor$ (\textit{mp\_rshd}) \\ -\\ -Produce the quotient. \\ -3. $q \leftarrow q \cdot \mu$ (\textit{note: only produce digits at or above $m-1$}) \\ -4. $q \leftarrow \lfloor q / \beta^{m + 1} \rfloor$ \\ -\\ -Subtract the multiple of modulus from the input. \\ -5. $a \leftarrow a \mbox{ (mod }\beta^{m+1}\mbox{)}$ (\textit{mp\_mod\_2d}) \\ -6. $q \leftarrow q \cdot b \mbox{ (mod }\beta^{m+1}\mbox{)}$ (\textit{s\_mp\_mul\_digs}) \\ -7. $a \leftarrow a - q$ (\textit{mp\_sub}) \\ -\\ -Add $\beta^{m+1}$ if a carry occured. \\ -8. If $a < 0$ then (\textit{mp\_cmp\_d}) \\ -\hspace{3mm}8.1 $q \leftarrow 1$ (\textit{mp\_set}) \\ -\hspace{3mm}8.2 $q \leftarrow q \cdot \beta^{m+1}$ (\textit{mp\_lshd}) \\ -\hspace{3mm}8.3 $a \leftarrow a + q$ \\ -\\ -Now subtract the modulus if the residue is too large (e.g. quotient too small). \\ -9. While $a \ge b$ do (\textit{mp\_cmp}) \\ -\hspace{3mm}9.1 $c \leftarrow a - b$ \\ -10. Clear $q$. \\ -11. Return(\textit{MP\_OKAY}) \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_reduce} -\end{figure} - -\textbf{Algorithm mp\_reduce.} -This algorithm will reduce the input $a$ modulo $b$ in place using the Barrett algorithm. It is loosely based on algorithm 14.42 of HAC -\cite[pp. 602]{HAC} which is based on the paper from Paul Barrett \cite{BARRETT}. The algorithm has several restrictions and assumptions which must -be adhered to for the algorithm to work. - -First the modulus $b$ is assumed to be positive and greater than one. If the modulus were less than or equal to one than subtracting -a multiple of it would either accomplish nothing or actually enlarge the input. The input $a$ must be in the range $0 \le a < b^2$ in order -for the quotient to have enough precision. If $a$ is the product of two numbers that were already reduced modulo $b$, this will not be a problem. -Technically the algorithm will still work if $a \ge b^2$ but it will take much longer to finish. The value of $\mu$ is passed as an argument to this -algorithm and is assumed to be calculated and stored before the algorithm is used. - -Recall that the multiplication for the quotient on step 3 must only produce digits at or above the $m-1$'th position. An algorithm called -$s\_mp\_mul\_high\_digs$ which has not been presented is used to accomplish this task. The algorithm is based on $s\_mp\_mul\_digs$ except that -instead of stopping at a given level of precision it starts at a given level of precision. This optimal algorithm can only be used if the number -of digits in $b$ is very much smaller than $\beta$. - -While it is known that -$a \ge b \cdot \lfloor (q_0 \cdot \mu) / \beta^{m+1} \rfloor$ only the lower $m+1$ digits are being used to compute the residue, so an implied -``borrow'' from the higher digits might leave a negative result. After the multiple of the modulus has been subtracted from $a$ the residue must be -fixed up in case it is negative. The invariant $\beta^{m+1}$ must be added to the residue to make it positive again. - -The while loop at step 9 will subtract $b$ until the residue is less than $b$. If the algorithm is performed correctly this step is -performed at most twice, and on average once. However, if $a \ge b^2$ than it will iterate substantially more times than it should. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_reduce.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* reduces x mod m, assumes 0 < x < m**2, mu is -018 * precomputed via mp_reduce_setup. -019 * From HAC pp.604 Algorithm 14.42 -020 */ -021 int mp_reduce (mp_int * x, mp_int * m, mp_int * mu) -022 \{ -023 mp_int q; -024 int res, um = m->used; -025 -026 /* q = x */ -027 if ((res = mp_init_copy (&q, x)) != MP_OKAY) \{ -028 return res; -029 \} -030 -031 /* q1 = x / b**(k-1) */ -032 mp_rshd (&q, um - 1); -033 -034 /* according to HAC this optimization is ok */ -035 if (((mp_digit) um) > (((mp_digit)1) << (DIGIT_BIT - 1))) \{ -036 if ((res = mp_mul (&q, mu, &q)) != MP_OKAY) \{ -037 goto CLEANUP; -038 \} -039 \} else \{ -040 #ifdef BN_S_MP_MUL_HIGH_DIGS_C -041 if ((res = s_mp_mul_high_digs (&q, mu, &q, um)) != MP_OKAY) \{ -042 goto CLEANUP; -043 \} -044 #elif defined(BN_FAST_S_MP_MUL_HIGH_DIGS_C) -045 if ((res = fast_s_mp_mul_high_digs (&q, mu, &q, um)) != MP_OKAY) \{ -046 goto CLEANUP; -047 \} -048 #else -049 \{ -050 res = MP_VAL; -051 goto CLEANUP; -052 \} -053 #endif -054 \} -055 -056 /* q3 = q2 / b**(k+1) */ -057 mp_rshd (&q, um + 1); -058 -059 /* x = x mod b**(k+1), quick (no division) */ -060 if ((res = mp_mod_2d (x, DIGIT_BIT * (um + 1), x)) != MP_OKAY) \{ -061 goto CLEANUP; -062 \} -063 -064 /* q = q * m mod b**(k+1), quick (no division) */ -065 if ((res = s_mp_mul_digs (&q, m, &q, um + 1)) != MP_OKAY) \{ -066 goto CLEANUP; -067 \} -068 -069 /* x = x - q */ -070 if ((res = mp_sub (x, &q, x)) != MP_OKAY) \{ -071 goto CLEANUP; -072 \} -073 -074 /* If x < 0, add b**(k+1) to it */ -075 if (mp_cmp_d (x, 0) == MP_LT) \{ -076 mp_set (&q, 1); -077 if ((res = mp_lshd (&q, um + 1)) != MP_OKAY) -078 goto CLEANUP; -079 if ((res = mp_add (x, &q, x)) != MP_OKAY) -080 goto CLEANUP; -081 \} -082 -083 /* Back off if it's too big */ -084 while (mp_cmp (x, m) != MP_LT) \{ -085 if ((res = s_mp_sub (x, m, x)) != MP_OKAY) \{ -086 goto CLEANUP; -087 \} -088 \} -089 -090 CLEANUP: -091 mp_clear (&q); -092 -093 return res; -094 \} -095 #endif -096 -\end{alltt} -\end{small} - -The first multiplication that determines the quotient can be performed by only producing the digits from $m - 1$ and up. This essentially halves -the number of single precision multiplications required. However, the optimization is only safe if $\beta$ is much larger than the number of digits -in the modulus. In the source code this is evaluated on lines 36 to 43 where algorithm s\_mp\_mul\_high\_digs is used when it is -safe to do so. - -\subsection{The Barrett Setup Algorithm} -In order to use algorithm mp\_reduce the value of $\mu$ must be calculated in advance. Ideally this value should be computed once and stored for -future use so that the Barrett algorithm can be used without delay. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_reduce\_setup}. \\ -\textbf{Input}. mp\_int $a$ ($a > 1$) \\ -\textbf{Output}. $\mu \leftarrow \lfloor \beta^{2m}/a \rfloor$ \\ -\hline \\ -1. $\mu \leftarrow 2^{2 \cdot lg(\beta) \cdot m}$ (\textit{mp\_2expt}) \\ -2. $\mu \leftarrow \lfloor \mu / b \rfloor$ (\textit{mp\_div}) \\ -3. Return(\textit{MP\_OKAY}) \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_reduce\_setup} -\end{figure} - -\textbf{Algorithm mp\_reduce\_setup.} -This algorithm computes the reciprocal $\mu$ required for Barrett reduction. First $\beta^{2m}$ is calculated as $2^{2 \cdot lg(\beta) \cdot m}$ which -is equivalent and much faster. The final value is computed by taking the integer quotient of $\lfloor \mu / b \rfloor$. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_reduce\_setup.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* pre-calculate the value required for Barrett reduction -018 * For a given modulus "b" it calulates the value required in "a" -019 */ -020 int mp_reduce_setup (mp_int * a, mp_int * b) -021 \{ -022 int res; -023 -024 if ((res = mp_2expt (a, b->used * 2 * DIGIT_BIT)) != MP_OKAY) \{ -025 return res; -026 \} -027 return mp_div (a, b, a, NULL); -028 \} -029 #endif -030 -\end{alltt} -\end{small} - -This simple routine calculates the reciprocal $\mu$ required by Barrett reduction. Note the extended usage of algorithm mp\_div where the variable -which would received the remainder is passed as NULL. As will be discussed in~\ref{sec:division} the division routine allows both the quotient and the -remainder to be passed as NULL meaning to ignore the value. - -\section{The Montgomery Reduction} -Montgomery reduction\footnote{Thanks to Niels Ferguson for his insightful explanation of the algorithm.} \cite{MONT} is by far the most interesting -form of reduction in common use. It computes a modular residue which is not actually equal to the residue of the input yet instead equal to a -residue times a constant. However, as perplexing as this may sound the algorithm is relatively simple and very efficient. - -Throughout this entire section the variable $n$ will represent the modulus used to form the residue. As will be discussed shortly the value of -$n$ must be odd. The variable $x$ will represent the quantity of which the residue is sought. Similar to the Barrett algorithm the input -is restricted to $0 \le x < n^2$. To begin the description some simple number theory facts must be established. - -\textbf{Fact 1.} Adding $n$ to $x$ does not change the residue since in effect it adds one to the quotient $\lfloor x / n \rfloor$. Another way -to explain this is that $n$ is (\textit{or multiples of $n$ are}) congruent to zero modulo $n$. Adding zero will not change the value of the residue. - -\textbf{Fact 2.} If $x$ is even then performing a division by two in $\Z$ is congruent to $x \cdot 2^{-1} \mbox{ (mod }n\mbox{)}$. Actually -this is an application of the fact that if $x$ is evenly divisible by any $k \in \Z$ then division in $\Z$ will be congruent to -multiplication by $k^{-1}$ modulo $n$. - -From these two simple facts the following simple algorithm can be derived. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{Montgomery Reduction}. \\ -\textbf{Input}. Integer $x$, $n$ and $k$ \\ -\textbf{Output}. $2^{-k}x \mbox{ (mod }n\mbox{)}$ \\ -\hline \\ -1. for $t$ from $1$ to $k$ do \\ -\hspace{3mm}1.1 If $x$ is odd then \\ -\hspace{6mm}1.1.1 $x \leftarrow x + n$ \\ -\hspace{3mm}1.2 $x \leftarrow x/2$ \\ -2. Return $x$. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm Montgomery Reduction} -\end{figure} - -The algorithm reduces the input one bit at a time using the two congruencies stated previously. Inside the loop $n$, which is odd, is -added to $x$ if $x$ is odd. This forces $x$ to be even which allows the division by two in $\Z$ to be congruent to a modular division by two. Since -$x$ is assumed to be initially much larger than $n$ the addition of $n$ will contribute an insignificant magnitude to $x$. Let $r$ represent the -final result of the Montgomery algorithm. If $k > lg(n)$ and $0 \le x < n^2$ then the final result is limited to -$0 \le r < \lfloor x/2^k \rfloor + n$. As a result at most a single subtraction is required to get the residue desired. - -\begin{figure}[here] -\begin{small} -\begin{center} -\begin{tabular}{|c|l|} -\hline \textbf{Step number ($t$)} & \textbf{Result ($x$)} \\ -\hline $1$ & $x + n = 5812$, $x/2 = 2906$ \\ -\hline $2$ & $x/2 = 1453$ \\ -\hline $3$ & $x + n = 1710$, $x/2 = 855$ \\ -\hline $4$ & $x + n = 1112$, $x/2 = 556$ \\ -\hline $5$ & $x/2 = 278$ \\ -\hline $6$ & $x/2 = 139$ \\ -\hline $7$ & $x + n = 396$, $x/2 = 198$ \\ -\hline $8$ & $x/2 = 99$ \\ -\hline $9$ & $x + n = 356$, $x/2 = 178$ \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Example of Montgomery Reduction (I)} -\label{fig:MONT1} -\end{figure} - -Consider the example in figure~\ref{fig:MONT1} which reduces $x = 5555$ modulo $n = 257$ when $k = 9$ (note $\beta^k = 512$ which is larger than $n$). The result of -the algorithm $r = 178$ is congruent to the value of $2^{-9} \cdot 5555 \mbox{ (mod }257\mbox{)}$. When $r$ is multiplied by $2^9$ modulo $257$ the correct residue -$r \equiv 158$ is produced. - -Let $k = \lfloor lg(n) \rfloor + 1$ represent the number of bits in $n$. The current algorithm requires $2k^2$ single precision shifts -and $k^2$ single precision additions. At this rate the algorithm is most certainly slower than Barrett reduction and not terribly useful. -Fortunately there exists an alternative representation of the algorithm. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{Montgomery Reduction} (modified I). \\ -\textbf{Input}. Integer $x$, $n$ and $k$ ($2^k > n$) \\ -\textbf{Output}. $2^{-k}x \mbox{ (mod }n\mbox{)}$ \\ -\hline \\ -1. for $t$ from $1$ to $k$ do \\ -\hspace{3mm}1.1 If the $t$'th bit of $x$ is one then \\ -\hspace{6mm}1.1.1 $x \leftarrow x + 2^tn$ \\ -2. Return $x/2^k$. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm Montgomery Reduction (modified I)} -\end{figure} - -This algorithm is equivalent since $2^tn$ is a multiple of $n$ and the lower $k$ bits of $x$ are zero by step 2. The number of single -precision shifts has now been reduced from $2k^2$ to $k^2 + k$ which is only a small improvement. - -\begin{figure}[here] -\begin{small} -\begin{center} -\begin{tabular}{|c|l|r|} -\hline \textbf{Step number ($t$)} & \textbf{Result ($x$)} & \textbf{Result ($x$) in Binary} \\ -\hline -- & $5555$ & $1010110110011$ \\ -\hline $1$ & $x + 2^{0}n = 5812$ & $1011010110100$ \\ -\hline $2$ & $5812$ & $1011010110100$ \\ -\hline $3$ & $x + 2^{2}n = 6840$ & $1101010111000$ \\ -\hline $4$ & $x + 2^{3}n = 8896$ & $10001011000000$ \\ -\hline $5$ & $8896$ & $10001011000000$ \\ -\hline $6$ & $8896$ & $10001011000000$ \\ -\hline $7$ & $x + 2^{6}n = 25344$ & $110001100000000$ \\ -\hline $8$ & $25344$ & $110001100000000$ \\ -\hline $9$ & $x + 2^{7}n = 91136$ & $10110010000000000$ \\ -\hline -- & $x/2^k = 178$ & \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Example of Montgomery Reduction (II)} -\label{fig:MONT2} -\end{figure} - -Figure~\ref{fig:MONT2} demonstrates the modified algorithm reducing $x = 5555$ modulo $n = 257$ with $k = 9$. -With this algorithm a single shift right at the end is the only right shift required to reduce the input instead of $k$ right shifts inside the -loop. Note that for the iterations $t = 2, 5, 6$ and $8$ where the result $x$ is not changed. In those iterations the $t$'th bit of $x$ is -zero and the appropriate multiple of $n$ does not need to be added to force the $t$'th bit of the result to zero. - -\subsection{Digit Based Montgomery Reduction} -Instead of computing the reduction on a bit-by-bit basis it is actually much faster to compute it on digit-by-digit basis. Consider the -previous algorithm re-written to compute the Montgomery reduction in this new fashion. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{Montgomery Reduction} (modified II). \\ -\textbf{Input}. Integer $x$, $n$ and $k$ ($\beta^k > n$) \\ -\textbf{Output}. $\beta^{-k}x \mbox{ (mod }n\mbox{)}$ \\ -\hline \\ -1. for $t$ from $0$ to $k - 1$ do \\ -\hspace{3mm}1.1 $x \leftarrow x + \mu n \beta^t$ \\ -2. Return $x/\beta^k$. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm Montgomery Reduction (modified II)} -\end{figure} - -The value $\mu n \beta^t$ is a multiple of the modulus $n$ meaning that it will not change the residue. If the first digit of -the value $\mu n \beta^t$ equals the negative (modulo $\beta$) of the $t$'th digit of $x$ then the addition will result in a zero digit. This -problem breaks down to solving the following congruency. - -\begin{center} -\begin{tabular}{rcl} -$x_t + \mu n_0$ & $\equiv$ & $0 \mbox{ (mod }\beta\mbox{)}$ \\ -$\mu n_0$ & $\equiv$ & $-x_t \mbox{ (mod }\beta\mbox{)}$ \\ -$\mu$ & $\equiv$ & $-x_t/n_0 \mbox{ (mod }\beta\mbox{)}$ \\ -\end{tabular} -\end{center} - -In each iteration of the loop on step 1 a new value of $\mu$ must be calculated. The value of $-1/n_0 \mbox{ (mod }\beta\mbox{)}$ is used -extensively in this algorithm and should be precomputed. Let $\rho$ represent the negative of the modular inverse of $n_0$ modulo $\beta$. - -For example, let $\beta = 10$ represent the radix. Let $n = 17$ represent the modulus which implies $k = 2$ and $\rho \equiv 7$. Let $x = 33$ -represent the value to reduce. - -\newpage\begin{figure} -\begin{center} -\begin{tabular}{|c|c|c|} -\hline \textbf{Step ($t$)} & \textbf{Value of $x$} & \textbf{Value of $\mu$} \\ -\hline -- & $33$ & --\\ -\hline $0$ & $33 + \mu n = 50$ & $1$ \\ -\hline $1$ & $50 + \mu n \beta = 900$ & $5$ \\ -\hline -\end{tabular} -\end{center} -\caption{Example of Montgomery Reduction} -\end{figure} - -The final result $900$ is then divided by $\beta^k$ to produce the final result $9$. The first observation is that $9 \nequiv x \mbox{ (mod }n\mbox{)}$ -which implies the result is not the modular residue of $x$ modulo $n$. However, recall that the residue is actually multiplied by $\beta^{-k}$ in -the algorithm. To get the true residue the value must be multiplied by $\beta^k$. In this case $\beta^k \equiv 15 \mbox{ (mod }n\mbox{)}$ and -the correct residue is $9 \cdot 15 \equiv 16 \mbox{ (mod }n\mbox{)}$. - -\subsection{Baseline Montgomery Reduction} -The baseline Montgomery reduction algorithm will produce the residue for any size input. It is designed to be a catch-all algororithm for -Montgomery reductions. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_montgomery\_reduce}. \\ -\textbf{Input}. mp\_int $x$, mp\_int $n$ and a digit $\rho \equiv -1/n_0 \mbox{ (mod }n\mbox{)}$. \\ -\hspace{11.5mm}($0 \le x < n^2, n > 1, (n, \beta) = 1, \beta^k > n$) \\ -\textbf{Output}. $\beta^{-k}x \mbox{ (mod }n\mbox{)}$ \\ -\hline \\ -1. $digs \leftarrow 2n.used + 1$ \\ -2. If $digs < MP\_ARRAY$ and $m.used < \delta$ then \\ -\hspace{3mm}2.1 Use algorithm fast\_mp\_montgomery\_reduce instead. \\ -\\ -Setup $x$ for the reduction. \\ -3. If $x.alloc < digs$ then grow $x$ to $digs$ digits. \\ -4. $x.used \leftarrow digs$ \\ -\\ -Eliminate the lower $k$ digits. \\ -5. For $ix$ from $0$ to $k - 1$ do \\ -\hspace{3mm}5.1 $\mu \leftarrow x_{ix} \cdot \rho \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{3mm}5.2 $u \leftarrow 0$ \\ -\hspace{3mm}5.3 For $iy$ from $0$ to $k - 1$ do \\ -\hspace{6mm}5.3.1 $\hat r \leftarrow \mu n_{iy} + x_{ix + iy} + u$ \\ -\hspace{6mm}5.3.2 $x_{ix + iy} \leftarrow \hat r \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{6mm}5.3.3 $u \leftarrow \lfloor \hat r / \beta \rfloor$ \\ -\hspace{3mm}5.4 While $u > 0$ do \\ -\hspace{6mm}5.4.1 $iy \leftarrow iy + 1$ \\ -\hspace{6mm}5.4.2 $x_{ix + iy} \leftarrow x_{ix + iy} + u$ \\ -\hspace{6mm}5.4.3 $u \leftarrow \lfloor x_{ix+iy} / \beta \rfloor$ \\ -\hspace{6mm}5.4.4 $x_{ix + iy} \leftarrow x_{ix+iy} \mbox{ (mod }\beta\mbox{)}$ \\ -\\ -Divide by $\beta^k$ and fix up as required. \\ -6. $x \leftarrow \lfloor x / \beta^k \rfloor$ \\ -7. If $x \ge n$ then \\ -\hspace{3mm}7.1 $x \leftarrow x - n$ \\ -8. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_montgomery\_reduce} -\end{figure} - -\textbf{Algorithm mp\_montgomery\_reduce.} -This algorithm reduces the input $x$ modulo $n$ in place using the Montgomery reduction algorithm. The algorithm is loosely based -on algorithm 14.32 of \cite[pp.601]{HAC} except it merges the multiplication of $\mu n \beta^t$ with the addition in the inner loop. The -restrictions on this algorithm are fairly easy to adapt to. First $0 \le x < n^2$ bounds the input to numbers in the same range as -for the Barrett algorithm. Additionally if $n > 1$ and $n$ is odd there will exist a modular inverse $\rho$. $\rho$ must be calculated in -advance of this algorithm. Finally the variable $k$ is fixed and a pseudonym for $n.used$. - -Step 2 decides whether a faster Montgomery algorithm can be used. It is based on the Comba technique meaning that there are limits on -the size of the input. This algorithm is discussed in sub-section 6.3.3. - -Step 5 is the main reduction loop of the algorithm. The value of $\mu$ is calculated once per iteration in the outer loop. The inner loop -calculates $x + \mu n \beta^{ix}$ by multiplying $\mu n$ and adding the result to $x$ shifted by $ix$ digits. Both the addition and -multiplication are performed in the same loop to save time and memory. Step 5.4 will handle any additional carries that escape the inner loop. - -Using a quick inspection this algorithm requires $n$ single precision multiplications for the outer loop and $n^2$ single precision multiplications -in the inner loop. In total $n^2 + n$ single precision multiplications which compares favourably to Barrett at $n^2 + 2n - 1$ single precision -multiplications. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_montgomery\_reduce.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* computes xR**-1 == x (mod N) via Montgomery Reduction */ -018 int -019 mp_montgomery_reduce (mp_int * x, mp_int * n, mp_digit rho) -020 \{ -021 int ix, res, digs; -022 mp_digit mu; -023 -024 /* can the fast reduction [comba] method be used? -025 * -026 * Note that unlike in mul you're safely allowed *less* -027 * than the available columns [255 per default] since carries -028 * are fixed up in the inner loop. -029 */ -030 digs = (n->used * 2) + 1; -031 if ((digs < MP_WARRAY) && -032 (n->used < -033 (1 << ((CHAR_BIT * sizeof(mp_word)) - (2 * DIGIT_BIT))))) \{ -034 return fast_mp_montgomery_reduce (x, n, rho); -035 \} -036 -037 /* grow the input as required */ -038 if (x->alloc < digs) \{ -039 if ((res = mp_grow (x, digs)) != MP_OKAY) \{ -040 return res; -041 \} -042 \} -043 x->used = digs; -044 -045 for (ix = 0; ix < n->used; ix++) \{ -046 /* mu = ai * rho mod b -047 * -048 * The value of rho must be precalculated via -049 * montgomery_setup() such that -050 * it equals -1/n0 mod b this allows the -051 * following inner loop to reduce the -052 * input one digit at a time -053 */ -054 mu = (mp_digit) (((mp_word)x->dp[ix] * (mp_word)rho) & MP_MASK); -055 -056 /* a = a + mu * m * b**i */ -057 \{ -058 int iy; -059 mp_digit *tmpn, *tmpx, u; -060 mp_word r; -061 -062 /* alias for digits of the modulus */ -063 tmpn = n->dp; -064 -065 /* alias for the digits of x [the input] */ -066 tmpx = x->dp + ix; -067 -068 /* set the carry to zero */ -069 u = 0; -070 -071 /* Multiply and add in place */ -072 for (iy = 0; iy < n->used; iy++) \{ -073 /* compute product and sum */ -074 r = ((mp_word)mu * (mp_word)*tmpn++) + -075 (mp_word) u + (mp_word) *tmpx; -076 -077 /* get carry */ -078 u = (mp_digit)(r >> ((mp_word) DIGIT_BIT)); -079 -080 /* fix digit */ -081 *tmpx++ = (mp_digit)(r & ((mp_word) MP_MASK)); -082 \} -083 /* At this point the ix'th digit of x should be zero */ -084 -085 -086 /* propagate carries upwards as required*/ -087 while (u != 0) \{ -088 *tmpx += u; -089 u = *tmpx >> DIGIT_BIT; -090 *tmpx++ &= MP_MASK; -091 \} -092 \} -093 \} -094 -095 /* at this point the n.used'th least -096 * significant digits of x are all zero -097 * which means we can shift x to the -098 * right by n.used digits and the -099 * residue is unchanged. -100 */ -101 -102 /* x = x/b**n.used */ -103 mp_clamp(x); -104 mp_rshd (x, n->used); -105 -106 /* if x >= n then x = x - n */ -107 if (mp_cmp_mag (x, n) != MP_LT) \{ -108 return s_mp_sub (x, n, x); -109 \} -110 -111 return MP_OKAY; -112 \} -113 #endif -114 -\end{alltt} -\end{small} - -This is the baseline implementation of the Montgomery reduction algorithm. Lines 30 to 35 determine if the Comba based -routine can be used instead. Line 48 computes the value of $\mu$ for that particular iteration of the outer loop. - -The multiplication $\mu n \beta^{ix}$ is performed in one step in the inner loop. The alias $tmpx$ refers to the $ix$'th digit of $x$ and -the alias $tmpn$ refers to the modulus $n$. - -\subsection{Faster ``Comba'' Montgomery Reduction} - -The Montgomery reduction requires fewer single precision multiplications than a Barrett reduction, however it is much slower due to the serial -nature of the inner loop. The Barrett reduction algorithm requires two slightly modified multipliers which can be implemented with the Comba -technique. The Montgomery reduction algorithm cannot directly use the Comba technique to any significant advantage since the inner loop calculates -a $k \times 1$ product $k$ times. - -The biggest obstacle is that at the $ix$'th iteration of the outer loop the value of $x_{ix}$ is required to calculate $\mu$. This means the -carries from $0$ to $ix - 1$ must have been propagated upwards to form a valid $ix$'th digit. The solution as it turns out is very simple. -Perform a Comba like multiplier and inside the outer loop just after the inner loop fix up the $ix + 1$'th digit by forwarding the carry. - -With this change in place the Montgomery reduction algorithm can be performed with a Comba style multiplication loop which substantially increases -the speed of the algorithm. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{fast\_mp\_montgomery\_reduce}. \\ -\textbf{Input}. mp\_int $x$, mp\_int $n$ and a digit $\rho \equiv -1/n_0 \mbox{ (mod }n\mbox{)}$. \\ -\hspace{11.5mm}($0 \le x < n^2, n > 1, (n, \beta) = 1, \beta^k > n$) \\ -\textbf{Output}. $\beta^{-k}x \mbox{ (mod }n\mbox{)}$ \\ -\hline \\ -Place an array of \textbf{MP\_WARRAY} mp\_word variables called $\hat W$ on the stack. \\ -1. if $x.alloc < n.used + 1$ then grow $x$ to $n.used + 1$ digits. \\ -Copy the digits of $x$ into the array $\hat W$ \\ -2. For $ix$ from $0$ to $x.used - 1$ do \\ -\hspace{3mm}2.1 $\hat W_{ix} \leftarrow x_{ix}$ \\ -3. For $ix$ from $x.used$ to $2n.used - 1$ do \\ -\hspace{3mm}3.1 $\hat W_{ix} \leftarrow 0$ \\ -Elimiate the lower $k$ digits. \\ -4. for $ix$ from $0$ to $n.used - 1$ do \\ -\hspace{3mm}4.1 $\mu \leftarrow \hat W_{ix} \cdot \rho \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{3mm}4.2 For $iy$ from $0$ to $n.used - 1$ do \\ -\hspace{6mm}4.2.1 $\hat W_{iy + ix} \leftarrow \hat W_{iy + ix} + \mu \cdot n_{iy}$ \\ -\hspace{3mm}4.3 $\hat W_{ix + 1} \leftarrow \hat W_{ix + 1} + \lfloor \hat W_{ix} / \beta \rfloor$ \\ -Propagate carries upwards. \\ -5. for $ix$ from $n.used$ to $2n.used + 1$ do \\ -\hspace{3mm}5.1 $\hat W_{ix + 1} \leftarrow \hat W_{ix + 1} + \lfloor \hat W_{ix} / \beta \rfloor$ \\ -Shift right and reduce modulo $\beta$ simultaneously. \\ -6. for $ix$ from $0$ to $n.used + 1$ do \\ -\hspace{3mm}6.1 $x_{ix} \leftarrow \hat W_{ix + n.used} \mbox{ (mod }\beta\mbox{)}$ \\ -Zero excess digits and fixup $x$. \\ -7. if $x.used > n.used + 1$ then do \\ -\hspace{3mm}7.1 for $ix$ from $n.used + 1$ to $x.used - 1$ do \\ -\hspace{6mm}7.1.1 $x_{ix} \leftarrow 0$ \\ -8. $x.used \leftarrow n.used + 1$ \\ -9. Clamp excessive digits of $x$. \\ -10. If $x \ge n$ then \\ -\hspace{3mm}10.1 $x \leftarrow x - n$ \\ -11. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm fast\_mp\_montgomery\_reduce} -\end{figure} - -\textbf{Algorithm fast\_mp\_montgomery\_reduce.} -This algorithm will compute the Montgomery reduction of $x$ modulo $n$ using the Comba technique. It is on most computer platforms significantly -faster than algorithm mp\_montgomery\_reduce and algorithm mp\_reduce (\textit{Barrett reduction}). The algorithm has the same restrictions -on the input as the baseline reduction algorithm. An additional two restrictions are imposed on this algorithm. The number of digits $k$ in the -the modulus $n$ must not violate $MP\_WARRAY > 2k +1$ and $n < \delta$. When $\beta = 2^{28}$ this algorithm can be used to reduce modulo -a modulus of at most $3,556$ bits in length. - -As in the other Comba reduction algorithms there is a $\hat W$ array which stores the columns of the product. It is initially filled with the -contents of $x$ with the excess digits zeroed. The reduction loop is very similar the to the baseline loop at heart. The multiplication on step -4.1 can be single precision only since $ab \mbox{ (mod }\beta\mbox{)} \equiv (a \mbox{ mod }\beta)(b \mbox{ mod }\beta)$. Some multipliers such -as those on the ARM processors take a variable length time to complete depending on the number of bytes of result it must produce. By performing -a single precision multiplication instead half the amount of time is spent. - -Also note that digit $\hat W_{ix}$ must have the carry from the $ix - 1$'th digit propagated upwards in order for this to work. That is what step -4.3 will do. In effect over the $n.used$ iterations of the outer loop the $n.used$'th lower columns all have the their carries propagated forwards. Note -how the upper bits of those same words are not reduced modulo $\beta$. This is because those values will be discarded shortly and there is no -point. - -Step 5 will propagate the remainder of the carries upwards. On step 6 the columns are reduced modulo $\beta$ and shifted simultaneously as they are -stored in the destination $x$. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_fast\_mp\_montgomery\_reduce.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* computes xR**-1 == x (mod N) via Montgomery Reduction -018 * -019 * This is an optimized implementation of montgomery_reduce -020 * which uses the comba method to quickly calculate the columns of the -021 * reduction. -022 * -023 * Based on Algorithm 14.32 on pp.601 of HAC. -024 */ -025 int fast_mp_montgomery_reduce (mp_int * x, mp_int * n, mp_digit rho) -026 \{ -027 int ix, res, olduse; -028 mp_word W[MP_WARRAY]; -029 -030 /* get old used count */ -031 olduse = x->used; -032 -033 /* grow a as required */ -034 if (x->alloc < (n->used + 1)) \{ -035 if ((res = mp_grow (x, n->used + 1)) != MP_OKAY) \{ -036 return res; -037 \} -038 \} -039 -040 /* first we have to get the digits of the input into -041 * an array of double precision words W[...] -042 */ -043 \{ -044 mp_word *_W; -045 mp_digit *tmpx; -046 -047 /* alias for the W[] array */ -048 _W = W; -049 -050 /* alias for the digits of x*/ -051 tmpx = x->dp; -052 -053 /* copy the digits of a into W[0..a->used-1] */ -054 for (ix = 0; ix < x->used; ix++) \{ -055 *_W++ = *tmpx++; -056 \} -057 -058 /* zero the high words of W[a->used..m->used*2] */ -059 for (; ix < ((n->used * 2) + 1); ix++) \{ -060 *_W++ = 0; -061 \} -062 \} -063 -064 /* now we proceed to zero successive digits -065 * from the least significant upwards -066 */ -067 for (ix = 0; ix < n->used; ix++) \{ -068 /* mu = ai * m' mod b -069 * -070 * We avoid a double precision multiplication (which isn't required) -071 * by casting the value down to a mp_digit. Note this requires -072 * that W[ix-1] have the carry cleared (see after the inner loop) -073 */ -074 mp_digit mu; -075 mu = (mp_digit) (((W[ix] & MP_MASK) * rho) & MP_MASK); -076 -077 /* a = a + mu * m * b**i -078 * -079 * This is computed in place and on the fly. The multiplication -080 * by b**i is handled by offseting which columns the results -081 * are added to. -082 * -083 * Note the comba method normally doesn't handle carries in the -084 * inner loop In this case we fix the carry from the previous -085 * column since the Montgomery reduction requires digits of the -086 * result (so far) [see above] to work. This is -087 * handled by fixing up one carry after the inner loop. The -088 * carry fixups are done in order so after these loops the -089 * first m->used words of W[] have the carries fixed -090 */ -091 \{ -092 int iy; -093 mp_digit *tmpn; -094 mp_word *_W; -095 -096 /* alias for the digits of the modulus */ -097 tmpn = n->dp; -098 -099 /* Alias for the columns set by an offset of ix */ -100 _W = W + ix; -101 -102 /* inner loop */ -103 for (iy = 0; iy < n->used; iy++) \{ -104 *_W++ += ((mp_word)mu) * ((mp_word)*tmpn++); -105 \} -106 \} -107 -108 /* now fix carry for next digit, W[ix+1] */ -109 W[ix + 1] += W[ix] >> ((mp_word) DIGIT_BIT); -110 \} -111 -112 /* now we have to propagate the carries and -113 * shift the words downward [all those least -114 * significant digits we zeroed]. -115 */ -116 \{ -117 mp_digit *tmpx; -118 mp_word *_W, *_W1; -119 -120 /* nox fix rest of carries */ -121 -122 /* alias for current word */ -123 _W1 = W + ix; -124 -125 /* alias for next word, where the carry goes */ -126 _W = W + ++ix; -127 -128 for (; ix <= ((n->used * 2) + 1); ix++) \{ -129 *_W++ += *_W1++ >> ((mp_word) DIGIT_BIT); -130 \} -131 -132 /* copy out, A = A/b**n -133 * -134 * The result is A/b**n but instead of converting from an -135 * array of mp_word to mp_digit than calling mp_rshd -136 * we just copy them in the right order -137 */ -138 -139 /* alias for destination word */ -140 tmpx = x->dp; -141 -142 /* alias for shifted double precision result */ -143 _W = W + n->used; -144 -145 for (ix = 0; ix < (n->used + 1); ix++) \{ -146 *tmpx++ = (mp_digit)(*_W++ & ((mp_word) MP_MASK)); -147 \} -148 -149 /* zero oldused digits, if the input a was larger than -150 * m->used+1 we'll have to clear the digits -151 */ -152 for (; ix < olduse; ix++) \{ -153 *tmpx++ = 0; -154 \} -155 \} -156 -157 /* set the max used and clamp */ -158 x->used = n->used + 1; -159 mp_clamp (x); -160 -161 /* if A >= m then A = A - m */ -162 if (mp_cmp_mag (x, n) != MP_LT) \{ -163 return s_mp_sub (x, n, x); -164 \} -165 return MP_OKAY; -166 \} -167 #endif -168 -\end{alltt} -\end{small} - -The $\hat W$ array is first filled with digits of $x$ on line 50 then the rest of the digits are zeroed on line 54. Both loops share -the same alias variables to make the code easier to read. - -The value of $\mu$ is calculated in an interesting fashion. First the value $\hat W_{ix}$ is reduced modulo $\beta$ and cast to a mp\_digit. This -forces the compiler to use a single precision multiplication and prevents any concerns about loss of precision. Line 109 fixes the carry -for the next iteration of the loop by propagating the carry from $\hat W_{ix}$ to $\hat W_{ix+1}$. - -The for loop on line 108 propagates the rest of the carries upwards through the columns. The for loop on line 125 reduces the columns -modulo $\beta$ and shifts them $k$ places at the same time. The alias $\_ \hat W$ actually refers to the array $\hat W$ starting at the $n.used$'th -digit, that is $\_ \hat W_{t} = \hat W_{n.used + t}$. - -\subsection{Montgomery Setup} -To calculate the variable $\rho$ a relatively simple algorithm will be required. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_montgomery\_setup}. \\ -\textbf{Input}. mp\_int $n$ ($n > 1$ and $(n, 2) = 1$) \\ -\textbf{Output}. $\rho \equiv -1/n_0 \mbox{ (mod }\beta\mbox{)}$ \\ -\hline \\ -1. $b \leftarrow n_0$ \\ -2. If $b$ is even return(\textit{MP\_VAL}) \\ -3. $x \leftarrow (((b + 2) \mbox{ AND } 4) << 1) + b$ \\ -4. for $k$ from 0 to $\lceil lg(lg(\beta)) \rceil - 2$ do \\ -\hspace{3mm}4.1 $x \leftarrow x \cdot (2 - bx)$ \\ -5. $\rho \leftarrow \beta - x \mbox{ (mod }\beta\mbox{)}$ \\ -6. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_montgomery\_setup} -\end{figure} - -\textbf{Algorithm mp\_montgomery\_setup.} -This algorithm will calculate the value of $\rho$ required within the Montgomery reduction algorithms. It uses a very interesting trick -to calculate $1/n_0$ when $\beta$ is a power of two. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_montgomery\_setup.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* setups the montgomery reduction stuff */ -018 int -019 mp_montgomery_setup (mp_int * n, mp_digit * rho) -020 \{ -021 mp_digit x, b; -022 -023 /* fast inversion mod 2**k -024 * -025 * Based on the fact that -026 * -027 * XA = 1 (mod 2**n) => (X(2-XA)) A = 1 (mod 2**2n) -028 * => 2*X*A - X*X*A*A = 1 -029 * => 2*(1) - (1) = 1 -030 */ -031 b = n->dp[0]; -032 -033 if ((b & 1) == 0) \{ -034 return MP_VAL; -035 \} -036 -037 x = (((b + 2) & 4) << 1) + b; /* here x*a==1 mod 2**4 */ -038 x *= 2 - (b * x); /* here x*a==1 mod 2**8 */ -039 #if !defined(MP_8BIT) -040 x *= 2 - (b * x); /* here x*a==1 mod 2**16 */ -041 #endif -042 #if defined(MP_64BIT) || !(defined(MP_8BIT) || defined(MP_16BIT)) -043 x *= 2 - (b * x); /* here x*a==1 mod 2**32 */ -044 #endif -045 #ifdef MP_64BIT -046 x *= 2 - (b * x); /* here x*a==1 mod 2**64 */ -047 #endif -048 -049 /* rho = -1/m mod b */ -050 *rho = (mp_digit)(((mp_word)1 << ((mp_word) DIGIT_BIT)) - x) & MP_MASK; -051 -052 return MP_OKAY; -053 \} -054 #endif -055 -\end{alltt} -\end{small} - -This source code computes the value of $\rho$ required to perform Montgomery reduction. It has been modified to avoid performing excess -multiplications when $\beta$ is not the default 28-bits. - -\section{The Diminished Radix Algorithm} -The Diminished Radix method of modular reduction \cite{DRMET} is a fairly clever technique which can be more efficient than either the Barrett -or Montgomery methods for certain forms of moduli. The technique is based on the following simple congruence. - -\begin{equation} -(x \mbox{ mod } n) + k \lfloor x / n \rfloor \equiv x \mbox{ (mod }(n - k)\mbox{)} -\end{equation} - -This observation was used in the MMB \cite{MMB} block cipher to create a diffusion primitive. It used the fact that if $n = 2^{31}$ and $k=1$ that -then a x86 multiplier could produce the 62-bit product and use the ``shrd'' instruction to perform a double-precision right shift. The proof -of the above equation is very simple. First write $x$ in the product form. - -\begin{equation} -x = qn + r -\end{equation} - -Now reduce both sides modulo $(n - k)$. - -\begin{equation} -x \equiv qk + r \mbox{ (mod }(n-k)\mbox{)} -\end{equation} - -The variable $n$ reduces modulo $n - k$ to $k$. By putting $q = \lfloor x/n \rfloor$ and $r = x \mbox{ mod } n$ -into the equation the original congruence is reproduced, thus concluding the proof. The following algorithm is based on this observation. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{Diminished Radix Reduction}. \\ -\textbf{Input}. Integer $x$, $n$, $k$ \\ -\textbf{Output}. $x \mbox{ mod } (n - k)$ \\ -\hline \\ -1. $q \leftarrow \lfloor x / n \rfloor$ \\ -2. $q \leftarrow k \cdot q$ \\ -3. $x \leftarrow x \mbox{ (mod }n\mbox{)}$ \\ -4. $x \leftarrow x + q$ \\ -5. If $x \ge (n - k)$ then \\ -\hspace{3mm}5.1 $x \leftarrow x - (n - k)$ \\ -\hspace{3mm}5.2 Goto step 1. \\ -6. Return $x$ \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm Diminished Radix Reduction} -\label{fig:DR} -\end{figure} - -This algorithm will reduce $x$ modulo $n - k$ and return the residue. If $0 \le x < (n - k)^2$ then the algorithm will loop almost always -once or twice and occasionally three times. For simplicity sake the value of $x$ is bounded by the following simple polynomial. - -\begin{equation} -0 \le x < n^2 + k^2 - 2nk -\end{equation} - -The true bound is $0 \le x < (n - k - 1)^2$ but this has quite a few more terms. The value of $q$ after step 1 is bounded by the following. - -\begin{equation} -q < n - 2k - k^2/n -\end{equation} - -Since $k^2$ is going to be considerably smaller than $n$ that term will always be zero. The value of $x$ after step 3 is bounded trivially as -$0 \le x < n$. By step four the sum $x + q$ is bounded by - -\begin{equation} -0 \le q + x < (k + 1)n - 2k^2 - 1 -\end{equation} - -With a second pass $q$ will be loosely bounded by $0 \le q < k^2$ after step 2 while $x$ will still be loosely bounded by $0 \le x < n$ after step 3. After the second pass it is highly unlike that the -sum in step 4 will exceed $n - k$. In practice fewer than three passes of the algorithm are required to reduce virtually every input in the -range $0 \le x < (n - k - 1)^2$. - -\begin{figure} -\begin{small} -\begin{center} -\begin{tabular}{|l|} -\hline -$x = 123456789, n = 256, k = 3$ \\ -\hline $q \leftarrow \lfloor x/n \rfloor = 482253$ \\ -$q \leftarrow q*k = 1446759$ \\ -$x \leftarrow x \mbox{ mod } n = 21$ \\ -$x \leftarrow x + q = 1446780$ \\ -$x \leftarrow x - (n - k) = 1446527$ \\ -\hline -$q \leftarrow \lfloor x/n \rfloor = 5650$ \\ -$q \leftarrow q*k = 16950$ \\ -$x \leftarrow x \mbox{ mod } n = 127$ \\ -$x \leftarrow x + q = 17077$ \\ -$x \leftarrow x - (n - k) = 16824$ \\ -\hline -$q \leftarrow \lfloor x/n \rfloor = 65$ \\ -$q \leftarrow q*k = 195$ \\ -$x \leftarrow x \mbox{ mod } n = 184$ \\ -$x \leftarrow x + q = 379$ \\ -$x \leftarrow x - (n - k) = 126$ \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Example Diminished Radix Reduction} -\label{fig:EXDR} -\end{figure} - -Figure~\ref{fig:EXDR} demonstrates the reduction of $x = 123456789$ modulo $n - k = 253$ when $n = 256$ and $k = 3$. Note that even while $x$ -is considerably larger than $(n - k - 1)^2 = 63504$ the algorithm still converges on the modular residue exceedingly fast. In this case only -three passes were required to find the residue $x \equiv 126$. - - -\subsection{Choice of Moduli} -On the surface this algorithm looks like a very expensive algorithm. It requires a couple of subtractions followed by multiplication and other -modular reductions. The usefulness of this algorithm becomes exceedingly clear when an appropriate modulus is chosen. - -Division in general is a very expensive operation to perform. The one exception is when the division is by a power of the radix of representation used. -Division by ten for example is simple for pencil and paper mathematics since it amounts to shifting the decimal place to the right. Similarly division -by two (\textit{or powers of two}) is very simple for binary computers to perform. It would therefore seem logical to choose $n$ of the form $2^p$ -which would imply that $\lfloor x / n \rfloor$ is a simple shift of $x$ right $p$ bits. - -However, there is one operation related to division of power of twos that is even faster than this. If $n = \beta^p$ then the division may be -performed by moving whole digits to the right $p$ places. In practice division by $\beta^p$ is much faster than division by $2^p$ for any $p$. -Also with the choice of $n = \beta^p$ reducing $x$ modulo $n$ merely requires zeroing the digits above the $p-1$'th digit of $x$. - -Throughout the next section the term ``restricted modulus'' will refer to a modulus of the form $\beta^p - k$ whereas the term ``unrestricted -modulus'' will refer to a modulus of the form $2^p - k$. The word ``restricted'' in this case refers to the fact that it is based on the -$2^p$ logic except $p$ must be a multiple of $lg(\beta)$. - -\subsection{Choice of $k$} -Now that division and reduction (\textit{step 1 and 3 of figure~\ref{fig:DR}}) have been optimized to simple digit operations the multiplication by $k$ -in step 2 is the most expensive operation. Fortunately the choice of $k$ is not terribly limited. For all intents and purposes it might -as well be a single digit. The smaller the value of $k$ is the faster the algorithm will be. - -\subsection{Restricted Diminished Radix Reduction} -The restricted Diminished Radix algorithm can quickly reduce an input modulo a modulus of the form $n = \beta^p - k$. This algorithm can reduce -an input $x$ within the range $0 \le x < n^2$ using only a couple passes of the algorithm demonstrated in figure~\ref{fig:DR}. The implementation -of this algorithm has been optimized to avoid additional overhead associated with a division by $\beta^p$, the multiplication by $k$ or the addition -of $x$ and $q$. The resulting algorithm is very efficient and can lead to substantial improvements over Barrett and Montgomery reduction when modular -exponentiations are performed. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_dr\_reduce}. \\ -\textbf{Input}. mp\_int $x$, $n$ and a mp\_digit $k = \beta - n_0$ \\ -\hspace{11.5mm}($0 \le x < n^2$, $n > 1$, $0 < k < \beta$) \\ -\textbf{Output}. $x \mbox{ mod } n$ \\ -\hline \\ -1. $m \leftarrow n.used$ \\ -2. If $x.alloc < 2m$ then grow $x$ to $2m$ digits. \\ -3. $\mu \leftarrow 0$ \\ -4. for $i$ from $0$ to $m - 1$ do \\ -\hspace{3mm}4.1 $\hat r \leftarrow k \cdot x_{m+i} + x_{i} + \mu$ \\ -\hspace{3mm}4.2 $x_{i} \leftarrow \hat r \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{3mm}4.3 $\mu \leftarrow \lfloor \hat r / \beta \rfloor$ \\ -5. $x_{m} \leftarrow \mu$ \\ -6. for $i$ from $m + 1$ to $x.used - 1$ do \\ -\hspace{3mm}6.1 $x_{i} \leftarrow 0$ \\ -7. Clamp excess digits of $x$. \\ -8. If $x \ge n$ then \\ -\hspace{3mm}8.1 $x \leftarrow x - n$ \\ -\hspace{3mm}8.2 Goto step 3. \\ -9. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_dr\_reduce} -\end{figure} - -\textbf{Algorithm mp\_dr\_reduce.} -This algorithm will perform the Dimished Radix reduction of $x$ modulo $n$. It has similar restrictions to that of the Barrett reduction -with the addition that $n$ must be of the form $n = \beta^m - k$ where $0 < k <\beta$. - -This algorithm essentially implements the pseudo-code in figure~\ref{fig:DR} except with a slight optimization. The division by $\beta^m$, multiplication by $k$ -and addition of $x \mbox{ mod }\beta^m$ are all performed simultaneously inside the loop on step 4. The division by $\beta^m$ is emulated by accessing -the term at the $m+i$'th position which is subsequently multiplied by $k$ and added to the term at the $i$'th position. After the loop the $m$'th -digit is set to the carry and the upper digits are zeroed. Steps 5 and 6 emulate the reduction modulo $\beta^m$ that should have happend to -$x$ before the addition of the multiple of the upper half. - -At step 8 if $x$ is still larger than $n$ another pass of the algorithm is required. First $n$ is subtracted from $x$ and then the algorithm resumes -at step 3. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_dr\_reduce.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* reduce "x" in place modulo "n" using the Diminished Radix algorithm. -018 * -019 * Based on algorithm from the paper -020 * -021 * "Generating Efficient Primes for Discrete Log Cryptosystems" -022 * Chae Hoon Lim, Pil Joong Lee, -023 * POSTECH Information Research Laboratories -024 * -025 * The modulus must be of a special format [see manual] -026 * -027 * Has been modified to use algorithm 7.10 from the LTM book instead -028 * -029 * Input x must be in the range 0 <= x <= (n-1)**2 -030 */ -031 int -032 mp_dr_reduce (mp_int * x, mp_int * n, mp_digit k) -033 \{ -034 int err, i, m; -035 mp_word r; -036 mp_digit mu, *tmpx1, *tmpx2; -037 -038 /* m = digits in modulus */ -039 m = n->used; -040 -041 /* ensure that "x" has at least 2m digits */ -042 if (x->alloc < (m + m)) \{ -043 if ((err = mp_grow (x, m + m)) != MP_OKAY) \{ -044 return err; -045 \} -046 \} -047 -048 /* top of loop, this is where the code resumes if -049 * another reduction pass is required. -050 */ -051 top: -052 /* aliases for digits */ -053 /* alias for lower half of x */ -054 tmpx1 = x->dp; -055 -056 /* alias for upper half of x, or x/B**m */ -057 tmpx2 = x->dp + m; -058 -059 /* set carry to zero */ -060 mu = 0; -061 -062 /* compute (x mod B**m) + k * [x/B**m] inline and inplace */ -063 for (i = 0; i < m; i++) \{ -064 r = (((mp_word)*tmpx2++) * (mp_word)k) + *tmpx1 + mu; -065 *tmpx1++ = (mp_digit)(r & MP_MASK); -066 mu = (mp_digit)(r >> ((mp_word)DIGIT_BIT)); -067 \} -068 -069 /* set final carry */ -070 *tmpx1++ = mu; -071 -072 /* zero words above m */ -073 for (i = m + 1; i < x->used; i++) \{ -074 *tmpx1++ = 0; -075 \} -076 -077 /* clamp, sub and return */ -078 mp_clamp (x); -079 -080 /* if x >= n then subtract and reduce again -081 * Each successive "recursion" makes the input smaller and smaller. -082 */ -083 if (mp_cmp_mag (x, n) != MP_LT) \{ -084 if ((err = s_mp_sub(x, n, x)) != MP_OKAY) \{ -085 return err; -086 \} -087 goto top; -088 \} -089 return MP_OKAY; -090 \} -091 #endif -092 -\end{alltt} -\end{small} - -The first step is to grow $x$ as required to $2m$ digits since the reduction is performed in place on $x$. The label on line 51 is where -the algorithm will resume if further reduction passes are required. In theory it could be placed at the top of the function however, the size of -the modulus and question of whether $x$ is large enough are invariant after the first pass meaning that it would be a waste of time. - -The aliases $tmpx1$ and $tmpx2$ refer to the digits of $x$ where the latter is offset by $m$ digits. By reading digits from $x$ offset by $m$ digits -a division by $\beta^m$ can be simulated virtually for free. The loop on line 63 performs the bulk of the work (\textit{corresponds to step 4 of algorithm 7.11}) -in this algorithm. - -By line 70 the pointer $tmpx1$ points to the $m$'th digit of $x$ which is where the final carry will be placed. Similarly by line 73 the -same pointer will point to the $m+1$'th digit where the zeroes will be placed. - -Since the algorithm is only valid if both $x$ and $n$ are greater than zero an unsigned comparison suffices to determine if another pass is required. -With the same logic at line 84 the value of $x$ is known to be greater than or equal to $n$ meaning that an unsigned subtraction can be used -as well. Since the destination of the subtraction is the larger of the inputs the call to algorithm s\_mp\_sub cannot fail and the return code -does not need to be checked. - -\subsubsection{Setup} -To setup the restricted Diminished Radix algorithm the value $k = \beta - n_0$ is required. This algorithm is not really complicated but provided for -completeness. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_dr\_setup}. \\ -\textbf{Input}. mp\_int $n$ \\ -\textbf{Output}. $k = \beta - n_0$ \\ -\hline \\ -1. $k \leftarrow \beta - n_0$ \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_dr\_setup} -\end{figure} - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_dr\_setup.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* determines the setup value */ -018 void mp_dr_setup(mp_int *a, mp_digit *d) -019 \{ -020 /* the casts are required if DIGIT_BIT is one less than -021 * the number of bits in a mp_digit [e.g. DIGIT_BIT==31] -022 */ -023 *d = (mp_digit)((((mp_word)1) << ((mp_word)DIGIT_BIT)) - -024 ((mp_word)a->dp[0])); -025 \} -026 -027 #endif -028 -\end{alltt} -\end{small} - -\subsubsection{Modulus Detection} -Another algorithm which will be useful is the ability to detect a restricted Diminished Radix modulus. An integer is said to be -of restricted Diminished Radix form if all of the digits are equal to $\beta - 1$ except the trailing digit which may be any value. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_dr\_is\_modulus}. \\ -\textbf{Input}. mp\_int $n$ \\ -\textbf{Output}. $1$ if $n$ is in D.R form, $0$ otherwise \\ -\hline -1. If $n.used < 2$ then return($0$). \\ -2. for $ix$ from $1$ to $n.used - 1$ do \\ -\hspace{3mm}2.1 If $n_{ix} \ne \beta - 1$ return($0$). \\ -3. Return($1$). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_dr\_is\_modulus} -\end{figure} - -\textbf{Algorithm mp\_dr\_is\_modulus.} -This algorithm determines if a value is in Diminished Radix form. Step 1 rejects obvious cases where fewer than two digits are -in the mp\_int. Step 2 tests all but the first digit to see if they are equal to $\beta - 1$. If the algorithm manages to get to -step 3 then $n$ must be of Diminished Radix form. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_dr\_is\_modulus.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* determines if a number is a valid DR modulus */ -018 int mp_dr_is_modulus(mp_int *a) -019 \{ -020 int ix; -021 -022 /* must be at least two digits */ -023 if (a->used < 2) \{ -024 return 0; -025 \} -026 -027 /* must be of the form b**k - a [a <= b] so all -028 * but the first digit must be equal to -1 (mod b). -029 */ -030 for (ix = 1; ix < a->used; ix++) \{ -031 if (a->dp[ix] != MP_MASK) \{ -032 return 0; -033 \} -034 \} -035 return 1; -036 \} -037 -038 #endif -039 -\end{alltt} -\end{small} - -\subsection{Unrestricted Diminished Radix Reduction} -The unrestricted Diminished Radix algorithm allows modular reductions to be performed when the modulus is of the form $2^p - k$. This algorithm -is a straightforward adaptation of algorithm~\ref{fig:DR}. - -In general the restricted Diminished Radix reduction algorithm is much faster since it has considerably lower overhead. However, this new -algorithm is much faster than either Montgomery or Barrett reduction when the moduli are of the appropriate form. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_reduce\_2k}. \\ -\textbf{Input}. mp\_int $a$ and $n$. mp\_digit $k$ \\ -\hspace{11.5mm}($a \ge 0$, $n > 1$, $0 < k < \beta$, $n + k$ is a power of two) \\ -\textbf{Output}. $a \mbox{ (mod }n\mbox{)}$ \\ -\hline -1. $p \leftarrow \lceil lg(n) \rceil$ (\textit{mp\_count\_bits}) \\ -2. While $a \ge n$ do \\ -\hspace{3mm}2.1 $q \leftarrow \lfloor a / 2^p \rfloor$ (\textit{mp\_div\_2d}) \\ -\hspace{3mm}2.2 $a \leftarrow a \mbox{ (mod }2^p\mbox{)}$ (\textit{mp\_mod\_2d}) \\ -\hspace{3mm}2.3 $q \leftarrow q \cdot k$ (\textit{mp\_mul\_d}) \\ -\hspace{3mm}2.4 $a \leftarrow a - q$ (\textit{s\_mp\_sub}) \\ -\hspace{3mm}2.5 If $a \ge n$ then do \\ -\hspace{6mm}2.5.1 $a \leftarrow a - n$ \\ -3. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_reduce\_2k} -\end{figure} - -\textbf{Algorithm mp\_reduce\_2k.} -This algorithm quickly reduces an input $a$ modulo an unrestricted Diminished Radix modulus $n$. Division by $2^p$ is emulated with a right -shift which makes the algorithm fairly inexpensive to use. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_reduce\_2k.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* reduces a modulo n where n is of the form 2**p - d */ -018 int mp_reduce_2k(mp_int *a, mp_int *n, mp_digit d) -019 \{ -020 mp_int q; -021 int p, res; -022 -023 if ((res = mp_init(&q)) != MP_OKAY) \{ -024 return res; -025 \} -026 -027 p = mp_count_bits(n); -028 top: -029 /* q = a/2**p, a = a mod 2**p */ -030 if ((res = mp_div_2d(a, p, &q, a)) != MP_OKAY) \{ -031 goto ERR; -032 \} -033 -034 if (d != 1) \{ -035 /* q = q * d */ -036 if ((res = mp_mul_d(&q, d, &q)) != MP_OKAY) \{ -037 goto ERR; -038 \} -039 \} -040 -041 /* a = a + q */ -042 if ((res = s_mp_add(a, &q, a)) != MP_OKAY) \{ -043 goto ERR; -044 \} -045 -046 if (mp_cmp_mag(a, n) != MP_LT) \{ -047 if ((res = s_mp_sub(a, n, a)) != MP_OKAY) \{ -048 goto ERR; -049 \} -050 goto top; -051 \} -052 -053 ERR: -054 mp_clear(&q); -055 return res; -056 \} -057 -058 #endif -059 -\end{alltt} -\end{small} - -The algorithm mp\_count\_bits calculates the number of bits in an mp\_int which is used to find the initial value of $p$. The call to mp\_div\_2d -on line 30 calculates both the quotient $q$ and the remainder $a$ required. By doing both in a single function call the code size -is kept fairly small. The multiplication by $k$ is only performed if $k > 1$. This allows reductions modulo $2^p - 1$ to be performed without -any multiplications. - -The unsigned s\_mp\_add, mp\_cmp\_mag and s\_mp\_sub are used in place of their full sign counterparts since the inputs are only valid if they are -positive. By using the unsigned versions the overhead is kept to a minimum. - -\subsubsection{Unrestricted Setup} -To setup this reduction algorithm the value of $k = 2^p - n$ is required. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_reduce\_2k\_setup}. \\ -\textbf{Input}. mp\_int $n$ \\ -\textbf{Output}. $k = 2^p - n$ \\ -\hline -1. $p \leftarrow \lceil lg(n) \rceil$ (\textit{mp\_count\_bits}) \\ -2. $x \leftarrow 2^p$ (\textit{mp\_2expt}) \\ -3. $x \leftarrow x - n$ (\textit{mp\_sub}) \\ -4. $k \leftarrow x_0$ \\ -5. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_reduce\_2k\_setup} -\end{figure} - -\textbf{Algorithm mp\_reduce\_2k\_setup.} -This algorithm computes the value of $k$ required for the algorithm mp\_reduce\_2k. By making a temporary variable $x$ equal to $2^p$ a subtraction -is sufficient to solve for $k$. Alternatively if $n$ has more than one digit the value of $k$ is simply $\beta - n_0$. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_reduce\_2k\_setup.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* determines the setup value */ -018 int mp_reduce_2k_setup(mp_int *a, mp_digit *d) -019 \{ -020 int res, p; -021 mp_int tmp; -022 -023 if ((res = mp_init(&tmp)) != MP_OKAY) \{ -024 return res; -025 \} -026 -027 p = mp_count_bits(a); -028 if ((res = mp_2expt(&tmp, p)) != MP_OKAY) \{ -029 mp_clear(&tmp); -030 return res; -031 \} -032 -033 if ((res = s_mp_sub(&tmp, a, &tmp)) != MP_OKAY) \{ -034 mp_clear(&tmp); -035 return res; -036 \} -037 -038 *d = tmp.dp[0]; -039 mp_clear(&tmp); -040 return MP_OKAY; -041 \} -042 #endif -043 -\end{alltt} -\end{small} - -\subsubsection{Unrestricted Detection} -An integer $n$ is a valid unrestricted Diminished Radix modulus if either of the following are true. - -\begin{enumerate} -\item The number has only one digit. -\item The number has more than one digit and every bit from the $\beta$'th to the most significant is one. -\end{enumerate} - -If either condition is true than there is a power of two $2^p$ such that $0 < 2^p - n < \beta$. If the input is only -one digit than it will always be of the correct form. Otherwise all of the bits above the first digit must be one. This arises from the fact -that there will be value of $k$ that when added to the modulus causes a carry in the first digit which propagates all the way to the most -significant bit. The resulting sum will be a power of two. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_reduce\_is\_2k}. \\ -\textbf{Input}. mp\_int $n$ \\ -\textbf{Output}. $1$ if of proper form, $0$ otherwise \\ -\hline -1. If $n.used = 0$ then return($0$). \\ -2. If $n.used = 1$ then return($1$). \\ -3. $p \leftarrow \lceil lg(n) \rceil$ (\textit{mp\_count\_bits}) \\ -4. for $x$ from $lg(\beta)$ to $p$ do \\ -\hspace{3mm}4.1 If the ($x \mbox{ mod }lg(\beta)$)'th bit of the $\lfloor x / lg(\beta) \rfloor$ of $n$ is zero then return($0$). \\ -5. Return($1$). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_reduce\_is\_2k} -\end{figure} - -\textbf{Algorithm mp\_reduce\_is\_2k.} -This algorithm quickly determines if a modulus is of the form required for algorithm mp\_reduce\_2k to function properly. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_reduce\_is\_2k.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* determines if mp_reduce_2k can be used */ -018 int mp_reduce_is_2k(mp_int *a) -019 \{ -020 int ix, iy, iw; -021 mp_digit iz; -022 -023 if (a->used == 0) \{ -024 return MP_NO; -025 \} else if (a->used == 1) \{ -026 return MP_YES; -027 \} else if (a->used > 1) \{ -028 iy = mp_count_bits(a); -029 iz = 1; -030 iw = 1; -031 -032 /* Test every bit from the second digit up, must be 1 */ -033 for (ix = DIGIT_BIT; ix < iy; ix++) \{ -034 if ((a->dp[iw] & iz) == 0) \{ -035 return MP_NO; -036 \} -037 iz <<= 1; -038 if (iz > (mp_digit)MP_MASK) \{ -039 ++iw; -040 iz = 1; -041 \} -042 \} -043 \} -044 return MP_YES; -045 \} -046 -047 #endif -048 -\end{alltt} -\end{small} - - - -\section{Algorithm Comparison} -So far three very different algorithms for modular reduction have been discussed. Each of the algorithms have their own strengths and weaknesses -that makes having such a selection very useful. The following table sumarizes the three algorithms along with comparisons of work factors. Since -all three algorithms have the restriction that $0 \le x < n^2$ and $n > 1$ those limitations are not included in the table. - -\begin{center} -\begin{small} -\begin{tabular}{|c|c|c|c|c|c|} -\hline \textbf{Method} & \textbf{Work Required} & \textbf{Limitations} & \textbf{$m = 8$} & \textbf{$m = 32$} & \textbf{$m = 64$} \\ -\hline Barrett & $m^2 + 2m - 1$ & None & $79$ & $1087$ & $4223$ \\ -\hline Montgomery & $m^2 + m$ & $n$ must be odd & $72$ & $1056$ & $4160$ \\ -\hline D.R. & $2m$ & $n = \beta^m - k$ & $16$ & $64$ & $128$ \\ -\hline -\end{tabular} -\end{small} -\end{center} - -In theory Montgomery and Barrett reductions would require roughly the same amount of time to complete. However, in practice since Montgomery -reduction can be written as a single function with the Comba technique it is much faster. Barrett reduction suffers from the overhead of -calling the half precision multipliers, addition and division by $\beta$ algorithms. - -For almost every cryptographic algorithm Montgomery reduction is the algorithm of choice. The one set of algorithms where Diminished Radix reduction truly -shines are based on the discrete logarithm problem such as Diffie-Hellman \cite{DH} and ElGamal \cite{ELGAMAL}. In these algorithms -primes of the form $\beta^m - k$ can be found and shared amongst users. These primes will allow the Diminished Radix algorithm to be used in -modular exponentiation to greatly speed up the operation. - - - -\section*{Exercises} -\begin{tabular}{cl} -$\left [ 3 \right ]$ & Prove that the ``trick'' in algorithm mp\_montgomery\_setup actually \\ - & calculates the correct value of $\rho$. \\ - & \\ -$\left [ 2 \right ]$ & Devise an algorithm to reduce modulo $n + k$ for small $k$ quickly. \\ - & \\ -$\left [ 4 \right ]$ & Prove that the pseudo-code algorithm ``Diminished Radix Reduction'' \\ - & (\textit{figure~\ref{fig:DR}}) terminates. Also prove the probability that it will \\ - & terminate within $1 \le k \le 10$ iterations. \\ - & \\ -\end{tabular} - - -\chapter{Exponentiation} -Exponentiation is the operation of raising one variable to the power of another, for example, $a^b$. A variant of exponentiation, computed -in a finite field or ring, is called modular exponentiation. This latter style of operation is typically used in public key -cryptosystems such as RSA and Diffie-Hellman. The ability to quickly compute modular exponentiations is of great benefit to any -such cryptosystem and many methods have been sought to speed it up. - -\section{Exponentiation Basics} -A trivial algorithm would simply multiply $a$ against itself $b - 1$ times to compute the exponentiation desired. However, as $b$ grows in size -the number of multiplications becomes prohibitive. Imagine what would happen if $b$ $\approx$ $2^{1024}$ as is the case when computing an RSA signature -with a $1024$-bit key. Such a calculation could never be completed as it would take simply far too long. - -Fortunately there is a very simple algorithm based on the laws of exponents. Recall that $lg_a(a^b) = b$ and that $lg_a(a^ba^c) = b + c$ which -are two trivial relationships between the base and the exponent. Let $b_i$ represent the $i$'th bit of $b$ starting from the least -significant bit. If $b$ is a $k$-bit integer than the following equation is true. - -\begin{equation} -a^b = \prod_{i=0}^{k-1} a^{2^i \cdot b_i} -\end{equation} - -By taking the base $a$ logarithm of both sides of the equation the following equation is the result. - -\begin{equation} -b = \sum_{i=0}^{k-1}2^i \cdot b_i -\end{equation} - -The term $a^{2^i}$ can be found from the $i - 1$'th term by squaring the term since $\left ( a^{2^i} \right )^2$ is equal to -$a^{2^{i+1}}$. This observation forms the basis of essentially all fast exponentiation algorithms. It requires $k$ squarings and on average -$k \over 2$ multiplications to compute the result. This is indeed quite an improvement over simply multiplying by $a$ a total of $b-1$ times. - -While this current method is a considerable speed up there are further improvements to be made. For example, the $a^{2^i}$ term does not need to -be computed in an auxilary variable. Consider the following equivalent algorithm. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{Left to Right Exponentiation}. \\ -\textbf{Input}. Integer $a$, $b$ and $k$ \\ -\textbf{Output}. $c = a^b$ \\ -\hline \\ -1. $c \leftarrow 1$ \\ -2. for $i$ from $k - 1$ to $0$ do \\ -\hspace{3mm}2.1 $c \leftarrow c^2$ \\ -\hspace{3mm}2.2 $c \leftarrow c \cdot a^{b_i}$ \\ -3. Return $c$. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Left to Right Exponentiation} -\label{fig:LTOR} -\end{figure} - -This algorithm starts from the most significant bit and works towards the least significant bit. When the $i$'th bit of $b$ is set $a$ is -multiplied against the current product. In each iteration the product is squared which doubles the exponent of the individual terms of the -product. - -For example, let $b = 101100_2 \equiv 44_{10}$. The following chart demonstrates the actions of the algorithm. - -\newpage\begin{figure} -\begin{center} -\begin{tabular}{|c|c|} -\hline \textbf{Value of $i$} & \textbf{Value of $c$} \\ -\hline - & $1$ \\ -\hline $5$ & $a$ \\ -\hline $4$ & $a^2$ \\ -\hline $3$ & $a^4 \cdot a$ \\ -\hline $2$ & $a^8 \cdot a^2 \cdot a$ \\ -\hline $1$ & $a^{16} \cdot a^4 \cdot a^2$ \\ -\hline $0$ & $a^{32} \cdot a^8 \cdot a^4$ \\ -\hline -\end{tabular} -\end{center} -\caption{Example of Left to Right Exponentiation} -\end{figure} - -When the product $a^{32} \cdot a^8 \cdot a^4$ is simplified it is equal $a^{44}$ which is the desired exponentiation. This particular algorithm is -called ``Left to Right'' because it reads the exponent in that order. All of the exponentiation algorithms that will be presented are of this nature. - -\subsection{Single Digit Exponentiation} -The first algorithm in the series of exponentiation algorithms will be an unbounded algorithm where the exponent is a single digit. It is intended -to be used when a small power of an input is required (\textit{e.g. $a^5$}). It is faster than simply multiplying $b - 1$ times for all values of -$b$ that are greater than three. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_expt\_d}. \\ -\textbf{Input}. mp\_int $a$ and mp\_digit $b$ \\ -\textbf{Output}. $c = a^b$ \\ -\hline \\ -1. $g \leftarrow a$ (\textit{mp\_init\_copy}) \\ -2. $c \leftarrow 1$ (\textit{mp\_set}) \\ -3. for $x$ from 1 to $lg(\beta)$ do \\ -\hspace{3mm}3.1 $c \leftarrow c^2$ (\textit{mp\_sqr}) \\ -\hspace{3mm}3.2 If $b$ AND $2^{lg(\beta) - 1} \ne 0$ then \\ -\hspace{6mm}3.2.1 $c \leftarrow c \cdot g$ (\textit{mp\_mul}) \\ -\hspace{3mm}3.3 $b \leftarrow b << 1$ \\ -4. Clear $g$. \\ -5. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_expt\_d} -\end{figure} - -\textbf{Algorithm mp\_expt\_d.} -This algorithm computes the value of $a$ raised to the power of a single digit $b$. It uses the left to right exponentiation algorithm to -quickly compute the exponentiation. It is loosely based on algorithm 14.79 of HAC \cite[pp. 615]{HAC} with the difference that the -exponent is a fixed width. - -A copy of $a$ is made first to allow destination variable $c$ be the same as the source variable $a$. The result is set to the initial value of -$1$ in the subsequent step. - -Inside the loop the exponent is read from the most significant bit first down to the least significant bit. First $c$ is invariably squared -on step 3.1. In the following step if the most significant bit of $b$ is one the copy of $a$ is multiplied against $c$. The value -of $b$ is shifted left one bit to make the next bit down from the most signficant bit the new most significant bit. In effect each -iteration of the loop moves the bits of the exponent $b$ upwards to the most significant location. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_expt\_d\_ex.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* calculate c = a**b using a square-multiply algorithm */ -018 int mp_expt_d_ex (mp_int * a, mp_digit b, mp_int * c, int fast) -019 \{ -020 int res; -021 unsigned int x; -022 -023 mp_int g; -024 -025 if ((res = mp_init_copy (&g, a)) != MP_OKAY) \{ -026 return res; -027 \} -028 -029 /* set initial result */ -030 mp_set (c, 1); -031 -032 if (fast != 0) \{ -033 while (b > 0) \{ -034 /* if the bit is set multiply */ -035 if ((b & 1) != 0) \{ -036 if ((res = mp_mul (c, &g, c)) != MP_OKAY) \{ -037 mp_clear (&g); -038 return res; -039 \} -040 \} -041 -042 /* square */ -043 if (b > 1) \{ -044 if ((res = mp_sqr (&g, &g)) != MP_OKAY) \{ -045 mp_clear (&g); -046 return res; -047 \} -048 \} -049 -050 /* shift to next bit */ -051 b >>= 1; -052 \} -053 \} -054 else \{ -055 for (x = 0; x < DIGIT_BIT; x++) \{ -056 /* square */ -057 if ((res = mp_sqr (c, c)) != MP_OKAY) \{ -058 mp_clear (&g); -059 return res; -060 \} -061 -062 /* if the bit is set multiply */ -063 if ((b & (mp_digit) (((mp_digit)1) << (DIGIT_BIT - 1))) != 0) \{ -064 if ((res = mp_mul (c, &g, c)) != MP_OKAY) \{ -065 mp_clear (&g); -066 return res; -067 \} -068 \} -069 -070 /* shift to next bit */ -071 b <<= 1; -072 \} -073 \} /* if ... else */ -074 -075 mp_clear (&g); -076 return MP_OKAY; -077 \} -078 #endif -079 -\end{alltt} -\end{small} - -This describes only the algorithm that is used when the parameter $fast$ is $0$. Line 30 sets the initial value of the result to $1$. Next the loop on line 55 steps through each bit of the exponent starting from -the most significant down towards the least significant. The invariant squaring operation placed on line 57 is performed first. After -the squaring the result $c$ is multiplied by the base $g$ if and only if the most significant bit of the exponent is set. The shift on line -71 moves all of the bits of the exponent upwards towards the most significant location. - -\section{$k$-ary Exponentiation} -When calculating an exponentiation the most time consuming bottleneck is the multiplications which are in general a small factor -slower than squaring. Recall from the previous algorithm that $b_{i}$ refers to the $i$'th bit of the exponent $b$. Suppose instead it referred to -the $i$'th $k$-bit digit of the exponent of $b$. For $k = 1$ the definitions are synonymous and for $k > 1$ algorithm~\ref{fig:KARY} -computes the same exponentiation. A group of $k$ bits from the exponent is called a \textit{window}. That is it is a small window on only a -portion of the entire exponent. Consider the following modification to the basic left to right exponentiation algorithm. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{$k$-ary Exponentiation}. \\ -\textbf{Input}. Integer $a$, $b$, $k$ and $t$ \\ -\textbf{Output}. $c = a^b$ \\ -\hline \\ -1. $c \leftarrow 1$ \\ -2. for $i$ from $t - 1$ to $0$ do \\ -\hspace{3mm}2.1 $c \leftarrow c^{2^k} $ \\ -\hspace{3mm}2.2 Extract the $i$'th $k$-bit word from $b$ and store it in $g$. \\ -\hspace{3mm}2.3 $c \leftarrow c \cdot a^g$ \\ -3. Return $c$. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{$k$-ary Exponentiation} -\label{fig:KARY} -\end{figure} - -The squaring on step 2.1 can be calculated by squaring the value $c$ successively $k$ times. If the values of $a^g$ for $0 < g < 2^k$ have been -precomputed this algorithm requires only $t$ multiplications and $tk$ squarings. The table can be generated with $2^{k - 1} - 1$ squarings and -$2^{k - 1} + 1$ multiplications. This algorithm assumes that the number of bits in the exponent is evenly divisible by $k$. -However, when it is not the remaining $0 < x \le k - 1$ bits can be handled with algorithm~\ref{fig:LTOR}. - -Suppose $k = 4$ and $t = 100$. This modified algorithm will require $109$ multiplications and $408$ squarings to compute the exponentiation. The -original algorithm would on average have required $200$ multiplications and $400$ squrings to compute the same value. The total number of squarings -has increased slightly but the number of multiplications has nearly halved. - -\subsection{Optimal Values of $k$} -An optimal value of $k$ will minimize $2^{k} + \lceil n / k \rceil + n - 1$ for a fixed number of bits in the exponent $n$. The simplest -approach is to brute force search amongst the values $k = 2, 3, \ldots, 8$ for the lowest result. Table~\ref{fig:OPTK} lists optimal values of $k$ -for various exponent sizes and compares the number of multiplication and squarings required against algorithm~\ref{fig:LTOR}. - -\begin{figure}[here] -\begin{center} -\begin{small} -\begin{tabular}{|c|c|c|c|c|c|} -\hline \textbf{Exponent (bits)} & \textbf{Optimal $k$} & \textbf{Work at $k$} & \textbf{Work with ~\ref{fig:LTOR}} \\ -\hline $16$ & $2$ & $27$ & $24$ \\ -\hline $32$ & $3$ & $49$ & $48$ \\ -\hline $64$ & $3$ & $92$ & $96$ \\ -\hline $128$ & $4$ & $175$ & $192$ \\ -\hline $256$ & $4$ & $335$ & $384$ \\ -\hline $512$ & $5$ & $645$ & $768$ \\ -\hline $1024$ & $6$ & $1257$ & $1536$ \\ -\hline $2048$ & $6$ & $2452$ & $3072$ \\ -\hline $4096$ & $7$ & $4808$ & $6144$ \\ -\hline -\end{tabular} -\end{small} -\end{center} -\caption{Optimal Values of $k$ for $k$-ary Exponentiation} -\label{fig:OPTK} -\end{figure} - -\subsection{Sliding-Window Exponentiation} -A simple modification to the previous algorithm is only generate the upper half of the table in the range $2^{k-1} \le g < 2^k$. Essentially -this is a table for all values of $g$ where the most significant bit of $g$ is a one. However, in order for this to be allowed in the -algorithm values of $g$ in the range $0 \le g < 2^{k-1}$ must be avoided. - -Table~\ref{fig:OPTK2} lists optimal values of $k$ for various exponent sizes and compares the work required against algorithm {\ref{fig:KARY}}. - -\begin{figure}[here] -\begin{center} -\begin{small} -\begin{tabular}{|c|c|c|c|c|c|} -\hline \textbf{Exponent (bits)} & \textbf{Optimal $k$} & \textbf{Work at $k$} & \textbf{Work with ~\ref{fig:KARY}} \\ -\hline $16$ & $3$ & $24$ & $27$ \\ -\hline $32$ & $3$ & $45$ & $49$ \\ -\hline $64$ & $4$ & $87$ & $92$ \\ -\hline $128$ & $4$ & $167$ & $175$ \\ -\hline $256$ & $5$ & $322$ & $335$ \\ -\hline $512$ & $6$ & $628$ & $645$ \\ -\hline $1024$ & $6$ & $1225$ & $1257$ \\ -\hline $2048$ & $7$ & $2403$ & $2452$ \\ -\hline $4096$ & $8$ & $4735$ & $4808$ \\ -\hline -\end{tabular} -\end{small} -\end{center} -\caption{Optimal Values of $k$ for Sliding Window Exponentiation} -\label{fig:OPTK2} -\end{figure} - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{Sliding Window $k$-ary Exponentiation}. \\ -\textbf{Input}. Integer $a$, $b$, $k$ and $t$ \\ -\textbf{Output}. $c = a^b$ \\ -\hline \\ -1. $c \leftarrow 1$ \\ -2. for $i$ from $t - 1$ to $0$ do \\ -\hspace{3mm}2.1 If the $i$'th bit of $b$ is a zero then \\ -\hspace{6mm}2.1.1 $c \leftarrow c^2$ \\ -\hspace{3mm}2.2 else do \\ -\hspace{6mm}2.2.1 $c \leftarrow c^{2^k}$ \\ -\hspace{6mm}2.2.2 Extract the $k$ bits from $(b_{i}b_{i-1}\ldots b_{i-(k-1)})$ and store it in $g$. \\ -\hspace{6mm}2.2.3 $c \leftarrow c \cdot a^g$ \\ -\hspace{6mm}2.2.4 $i \leftarrow i - k$ \\ -3. Return $c$. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Sliding Window $k$-ary Exponentiation} -\end{figure} - -Similar to the previous algorithm this algorithm must have a special handler when fewer than $k$ bits are left in the exponent. While this -algorithm requires the same number of squarings it can potentially have fewer multiplications. The pre-computed table $a^g$ is also half -the size as the previous table. - -Consider the exponent $b = 111101011001000_2 \equiv 31432_{10}$ with $k = 3$ using both algorithms. The first algorithm will divide the exponent up as -the following five $3$-bit words $b \equiv \left ( 111, 101, 011, 001, 000 \right )_{2}$. The second algorithm will break the -exponent as $b \equiv \left ( 111, 101, 0, 110, 0, 100, 0 \right )_{2}$. The single digit $0$ in the second representation are where -a single squaring took place instead of a squaring and multiplication. In total the first method requires $10$ multiplications and $18$ -squarings. The second method requires $8$ multiplications and $18$ squarings. - -In general the sliding window method is never slower than the generic $k$-ary method and often it is slightly faster. - -\section{Modular Exponentiation} - -Modular exponentiation is essentially computing the power of a base within a finite field or ring. For example, computing -$d \equiv a^b \mbox{ (mod }c\mbox{)}$ is a modular exponentiation. Instead of first computing $a^b$ and then reducing it -modulo $c$ the intermediate result is reduced modulo $c$ after every squaring or multiplication operation. - -This guarantees that any intermediate result is bounded by $0 \le d \le c^2 - 2c + 1$ and can be reduced modulo $c$ quickly using -one of the algorithms presented in chapter six. - -Before the actual modular exponentiation algorithm can be written a wrapper algorithm must be written first. This algorithm -will allow the exponent $b$ to be negative which is computed as $c \equiv \left (1 / a \right )^{\vert b \vert} \mbox{(mod }d\mbox{)}$. The -value of $(1/a) \mbox{ mod }c$ is computed using the modular inverse (\textit{see \ref{sec;modinv}}). If no inverse exists the algorithm -terminates with an error. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_exptmod}. \\ -\textbf{Input}. mp\_int $a$, $b$ and $c$ \\ -\textbf{Output}. $y \equiv g^x \mbox{ (mod }p\mbox{)}$ \\ -\hline \\ -1. If $c.sign = MP\_NEG$ return(\textit{MP\_VAL}). \\ -2. If $b.sign = MP\_NEG$ then \\ -\hspace{3mm}2.1 $g' \leftarrow g^{-1} \mbox{ (mod }c\mbox{)}$ \\ -\hspace{3mm}2.2 $x' \leftarrow \vert x \vert$ \\ -\hspace{3mm}2.3 Compute $d \equiv g'^{x'} \mbox{ (mod }c\mbox{)}$ via recursion. \\ -3. if $p$ is odd \textbf{OR} $p$ is a D.R. modulus then \\ -\hspace{3mm}3.1 Compute $y \equiv g^{x} \mbox{ (mod }p\mbox{)}$ via algorithm mp\_exptmod\_fast. \\ -4. else \\ -\hspace{3mm}4.1 Compute $y \equiv g^{x} \mbox{ (mod }p\mbox{)}$ via algorithm s\_mp\_exptmod. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_exptmod} -\end{figure} - -\textbf{Algorithm mp\_exptmod.} -The first algorithm which actually performs modular exponentiation is algorithm s\_mp\_exptmod. It is a sliding window $k$-ary algorithm -which uses Barrett reduction to reduce the product modulo $p$. The second algorithm mp\_exptmod\_fast performs the same operation -except it uses either Montgomery or Diminished Radix reduction. The two latter reduction algorithms are clumped in the same exponentiation -algorithm since their arguments are essentially the same (\textit{two mp\_ints and one mp\_digit}). - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_exptmod.c -\vspace{-3mm} -\begin{alltt} -016 -017 -018 /* this is a shell function that calls either the normal or Montgomery -019 * exptmod functions. Originally the call to the montgomery code was -020 * embedded in the normal function but that wasted alot of stack space -021 * for nothing (since 99% of the time the Montgomery code would be called) -022 */ -023 int mp_exptmod (mp_int * G, mp_int * X, mp_int * P, mp_int * Y) -024 \{ -025 int dr; -026 -027 /* modulus P must be positive */ -028 if (P->sign == MP_NEG) \{ -029 return MP_VAL; -030 \} -031 -032 /* if exponent X is negative we have to recurse */ -033 if (X->sign == MP_NEG) \{ -034 #ifdef BN_MP_INVMOD_C -035 mp_int tmpG, tmpX; -036 int err; -037 -038 /* first compute 1/G mod P */ -039 if ((err = mp_init(&tmpG)) != MP_OKAY) \{ -040 return err; -041 \} -042 if ((err = mp_invmod(G, P, &tmpG)) != MP_OKAY) \{ -043 mp_clear(&tmpG); -044 return err; -045 \} -046 -047 /* now get |X| */ -048 if ((err = mp_init(&tmpX)) != MP_OKAY) \{ -049 mp_clear(&tmpG); -050 return err; -051 \} -052 if ((err = mp_abs(X, &tmpX)) != MP_OKAY) \{ -053 mp_clear_multi(&tmpG, &tmpX, NULL); -054 return err; -055 \} -056 -057 /* and now compute (1/G)**|X| instead of G**X [X < 0] */ -058 err = mp_exptmod(&tmpG, &tmpX, P, Y); -059 mp_clear_multi(&tmpG, &tmpX, NULL); -060 return err; -061 #else -062 /* no invmod */ -063 return MP_VAL; -064 #endif -065 \} -066 -067 /* modified diminished radix reduction */ -068 #if defined(BN_MP_REDUCE_IS_2K_L_C) && defined(BN_MP_REDUCE_2K_L_C) && defin - ed(BN_S_MP_EXPTMOD_C) -069 if (mp_reduce_is_2k_l(P) == MP_YES) \{ -070 return s_mp_exptmod(G, X, P, Y, 1); -071 \} -072 #endif -073 -074 #ifdef BN_MP_DR_IS_MODULUS_C -075 /* is it a DR modulus? */ -076 dr = mp_dr_is_modulus(P); -077 #else -078 /* default to no */ -079 dr = 0; -080 #endif -081 -082 #ifdef BN_MP_REDUCE_IS_2K_C -083 /* if not, is it a unrestricted DR modulus? */ -084 if (dr == 0) \{ -085 dr = mp_reduce_is_2k(P) << 1; -086 \} -087 #endif -088 -089 /* if the modulus is odd or dr != 0 use the montgomery method */ -090 #ifdef BN_MP_EXPTMOD_FAST_C -091 if ((mp_isodd (P) == MP_YES) || (dr != 0)) \{ -092 return mp_exptmod_fast (G, X, P, Y, dr); -093 \} else \{ -094 #endif -095 #ifdef BN_S_MP_EXPTMOD_C -096 /* otherwise use the generic Barrett reduction technique */ -097 return s_mp_exptmod (G, X, P, Y, 0); -098 #else -099 /* no exptmod for evens */ -100 return MP_VAL; -101 #endif -102 #ifdef BN_MP_EXPTMOD_FAST_C -103 \} -104 #endif -105 \} -106 -107 #endif -108 -\end{alltt} -\end{small} - -In order to keep the algorithms in a known state the first step on line 28 is to reject any negative modulus as input. If the exponent is -negative the algorithm tries to perform a modular exponentiation with the modular inverse of the base $G$. The temporary variable $tmpG$ is assigned -the modular inverse of $G$ and $tmpX$ is assigned the absolute value of $X$. The algorithm will recuse with these new values with a positive -exponent. - -If the exponent is positive the algorithm resumes the exponentiation. Line 76 determines if the modulus is of the restricted Diminished Radix -form. If it is not line 69 attempts to determine if it is of a unrestricted Diminished Radix form. The integer $dr$ will take on one -of three values. - -\begin{enumerate} -\item $dr = 0$ means that the modulus is not of either restricted or unrestricted Diminished Radix form. -\item $dr = 1$ means that the modulus is of restricted Diminished Radix form. -\item $dr = 2$ means that the modulus is of unrestricted Diminished Radix form. -\end{enumerate} - -Line 69 determines if the fast modular exponentiation algorithm can be used. It is allowed if $dr \ne 0$ or if the modulus is odd. Otherwise, -the slower s\_mp\_exptmod algorithm is used which uses Barrett reduction. - -\subsection{Barrett Modular Exponentiation} - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{s\_mp\_exptmod}. \\ -\textbf{Input}. mp\_int $a$, $b$ and $c$ \\ -\textbf{Output}. $y \equiv g^x \mbox{ (mod }p\mbox{)}$ \\ -\hline \\ -1. $k \leftarrow lg(x)$ \\ -2. $winsize \leftarrow \left \lbrace \begin{array}{ll} - 2 & \mbox{if }k \le 7 \\ - 3 & \mbox{if }7 < k \le 36 \\ - 4 & \mbox{if }36 < k \le 140 \\ - 5 & \mbox{if }140 < k \le 450 \\ - 6 & \mbox{if }450 < k \le 1303 \\ - 7 & \mbox{if }1303 < k \le 3529 \\ - 8 & \mbox{if }3529 < k \\ - \end{array} \right .$ \\ -3. Initialize $2^{winsize}$ mp\_ints in an array named $M$ and one mp\_int named $\mu$ \\ -4. Calculate the $\mu$ required for Barrett Reduction (\textit{mp\_reduce\_setup}). \\ -5. $M_1 \leftarrow g \mbox{ (mod }p\mbox{)}$ \\ -\\ -Setup the table of small powers of $g$. First find $g^{2^{winsize}}$ and then all multiples of it. \\ -6. $k \leftarrow 2^{winsize - 1}$ \\ -7. $M_{k} \leftarrow M_1$ \\ -8. for $ix$ from 0 to $winsize - 2$ do \\ -\hspace{3mm}8.1 $M_k \leftarrow \left ( M_k \right )^2$ (\textit{mp\_sqr}) \\ -\hspace{3mm}8.2 $M_k \leftarrow M_k \mbox{ (mod }p\mbox{)}$ (\textit{mp\_reduce}) \\ -9. for $ix$ from $2^{winsize - 1} + 1$ to $2^{winsize} - 1$ do \\ -\hspace{3mm}9.1 $M_{ix} \leftarrow M_{ix - 1} \cdot M_{1}$ (\textit{mp\_mul}) \\ -\hspace{3mm}9.2 $M_{ix} \leftarrow M_{ix} \mbox{ (mod }p\mbox{)}$ (\textit{mp\_reduce}) \\ -10. $res \leftarrow 1$ \\ -\\ -Start Sliding Window. \\ -11. $mode \leftarrow 0, bitcnt \leftarrow 1, buf \leftarrow 0, digidx \leftarrow x.used - 1, bitcpy \leftarrow 0, bitbuf \leftarrow 0$ \\ -12. Loop \\ -\hspace{3mm}12.1 $bitcnt \leftarrow bitcnt - 1$ \\ -\hspace{3mm}12.2 If $bitcnt = 0$ then do \\ -\hspace{6mm}12.2.1 If $digidx = -1$ goto step 13. \\ -\hspace{6mm}12.2.2 $buf \leftarrow x_{digidx}$ \\ -\hspace{6mm}12.2.3 $digidx \leftarrow digidx - 1$ \\ -\hspace{6mm}12.2.4 $bitcnt \leftarrow lg(\beta)$ \\ -Continued on next page. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm s\_mp\_exptmod} -\end{figure} - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{s\_mp\_exptmod} (\textit{continued}). \\ -\textbf{Input}. mp\_int $a$, $b$ and $c$ \\ -\textbf{Output}. $y \equiv g^x \mbox{ (mod }p\mbox{)}$ \\ -\hline \\ -\hspace{3mm}12.3 $y \leftarrow (buf >> (lg(\beta) - 1))$ AND $1$ \\ -\hspace{3mm}12.4 $buf \leftarrow buf << 1$ \\ -\hspace{3mm}12.5 if $mode = 0$ and $y = 0$ then goto step 12. \\ -\hspace{3mm}12.6 if $mode = 1$ and $y = 0$ then do \\ -\hspace{6mm}12.6.1 $res \leftarrow res^2$ \\ -\hspace{6mm}12.6.2 $res \leftarrow res \mbox{ (mod }p\mbox{)}$ \\ -\hspace{6mm}12.6.3 Goto step 12. \\ -\hspace{3mm}12.7 $bitcpy \leftarrow bitcpy + 1$ \\ -\hspace{3mm}12.8 $bitbuf \leftarrow bitbuf + (y << (winsize - bitcpy))$ \\ -\hspace{3mm}12.9 $mode \leftarrow 2$ \\ -\hspace{3mm}12.10 If $bitcpy = winsize$ then do \\ -\hspace{6mm}Window is full so perform the squarings and single multiplication. \\ -\hspace{6mm}12.10.1 for $ix$ from $0$ to $winsize -1$ do \\ -\hspace{9mm}12.10.1.1 $res \leftarrow res^2$ \\ -\hspace{9mm}12.10.1.2 $res \leftarrow res \mbox{ (mod }p\mbox{)}$ \\ -\hspace{6mm}12.10.2 $res \leftarrow res \cdot M_{bitbuf}$ \\ -\hspace{6mm}12.10.3 $res \leftarrow res \mbox{ (mod }p\mbox{)}$ \\ -\hspace{6mm}Reset the window. \\ -\hspace{6mm}12.10.4 $bitcpy \leftarrow 0, bitbuf \leftarrow 0, mode \leftarrow 1$ \\ -\\ -No more windows left. Check for residual bits of exponent. \\ -13. If $mode = 2$ and $bitcpy > 0$ then do \\ -\hspace{3mm}13.1 for $ix$ form $0$ to $bitcpy - 1$ do \\ -\hspace{6mm}13.1.1 $res \leftarrow res^2$ \\ -\hspace{6mm}13.1.2 $res \leftarrow res \mbox{ (mod }p\mbox{)}$ \\ -\hspace{6mm}13.1.3 $bitbuf \leftarrow bitbuf << 1$ \\ -\hspace{6mm}13.1.4 If $bitbuf$ AND $2^{winsize} \ne 0$ then do \\ -\hspace{9mm}13.1.4.1 $res \leftarrow res \cdot M_{1}$ \\ -\hspace{9mm}13.1.4.2 $res \leftarrow res \mbox{ (mod }p\mbox{)}$ \\ -14. $y \leftarrow res$ \\ -15. Clear $res$, $mu$ and the $M$ array. \\ -16. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm s\_mp\_exptmod (continued)} -\end{figure} - -\textbf{Algorithm s\_mp\_exptmod.} -This algorithm computes the $x$'th power of $g$ modulo $p$ and stores the result in $y$. It takes advantage of the Barrett reduction -algorithm to keep the product small throughout the algorithm. - -The first two steps determine the optimal window size based on the number of bits in the exponent. The larger the exponent the -larger the window size becomes. After a window size $winsize$ has been chosen an array of $2^{winsize}$ mp\_int variables is allocated. This -table will hold the values of $g^x \mbox{ (mod }p\mbox{)}$ for $2^{winsize - 1} \le x < 2^{winsize}$. - -After the table is allocated the first power of $g$ is found. Since $g \ge p$ is allowed it must be first reduced modulo $p$ to make -the rest of the algorithm more efficient. The first element of the table at $2^{winsize - 1}$ is found by squaring $M_1$ successively $winsize - 2$ -times. The rest of the table elements are found by multiplying the previous element by $M_1$ modulo $p$. - -Now that the table is available the sliding window may begin. The following list describes the functions of all the variables in the window. -\begin{enumerate} -\item The variable $mode$ dictates how the bits of the exponent are interpreted. -\begin{enumerate} - \item When $mode = 0$ the bits are ignored since no non-zero bit of the exponent has been seen yet. For example, if the exponent were simply - $1$ then there would be $lg(\beta) - 1$ zero bits before the first non-zero bit. In this case bits are ignored until a non-zero bit is found. - \item When $mode = 1$ a non-zero bit has been seen before and a new $winsize$-bit window has not been formed yet. In this mode leading $0$ bits - are read and a single squaring is performed. If a non-zero bit is read a new window is created. - \item When $mode = 2$ the algorithm is in the middle of forming a window and new bits are appended to the window from the most significant bit - downwards. -\end{enumerate} -\item The variable $bitcnt$ indicates how many bits are left in the current digit of the exponent left to be read. When it reaches zero a new digit - is fetched from the exponent. -\item The variable $buf$ holds the currently read digit of the exponent. -\item The variable $digidx$ is an index into the exponents digits. It starts at the leading digit $x.used - 1$ and moves towards the trailing digit. -\item The variable $bitcpy$ indicates how many bits are in the currently formed window. When it reaches $winsize$ the window is flushed and - the appropriate operations performed. -\item The variable $bitbuf$ holds the current bits of the window being formed. -\end{enumerate} - -All of step 12 is the window processing loop. It will iterate while there are digits available form the exponent to read. The first step -inside this loop is to extract a new digit if no more bits are available in the current digit. If there are no bits left a new digit is -read and if there are no digits left than the loop terminates. - -After a digit is made available step 12.3 will extract the most significant bit of the current digit and move all other bits in the digit -upwards. In effect the digit is read from most significant bit to least significant bit and since the digits are read from leading to -trailing edges the entire exponent is read from most significant bit to least significant bit. - -At step 12.5 if the $mode$ and currently extracted bit $y$ are both zero the bit is ignored and the next bit is read. This prevents the -algorithm from having to perform trivial squaring and reduction operations before the first non-zero bit is read. Step 12.6 and 12.7-10 handle -the two cases of $mode = 1$ and $mode = 2$ respectively. - -\begin{center} -\begin{figure}[here] -\includegraphics{pics/expt_state.ps} -\caption{Sliding Window State Diagram} -\label{pic:expt_state} -\end{figure} -\end{center} - -By step 13 there are no more digits left in the exponent. However, there may be partial bits in the window left. If $mode = 2$ then -a Left-to-Right algorithm is used to process the remaining few bits. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_s\_mp\_exptmod.c -\vspace{-3mm} -\begin{alltt} -016 #ifdef MP_LOW_MEM -017 #define TAB_SIZE 32 -018 #else -019 #define TAB_SIZE 256 -020 #endif -021 -022 int s_mp_exptmod (mp_int * G, mp_int * X, mp_int * P, mp_int * Y, int redmod - e) -023 \{ -024 mp_int M[TAB_SIZE], res, mu; -025 mp_digit buf; -026 int err, bitbuf, bitcpy, bitcnt, mode, digidx, x, y, winsize; -027 int (*redux)(mp_int*,mp_int*,mp_int*); -028 -029 /* find window size */ -030 x = mp_count_bits (X); -031 if (x <= 7) \{ -032 winsize = 2; -033 \} else if (x <= 36) \{ -034 winsize = 3; -035 \} else if (x <= 140) \{ -036 winsize = 4; -037 \} else if (x <= 450) \{ -038 winsize = 5; -039 \} else if (x <= 1303) \{ -040 winsize = 6; -041 \} else if (x <= 3529) \{ -042 winsize = 7; -043 \} else \{ -044 winsize = 8; -045 \} -046 -047 #ifdef MP_LOW_MEM -048 if (winsize > 5) \{ -049 winsize = 5; -050 \} -051 #endif -052 -053 /* init M array */ -054 /* init first cell */ -055 if ((err = mp_init(&M[1])) != MP_OKAY) \{ -056 return err; -057 \} -058 -059 /* now init the second half of the array */ -060 for (x = 1<<(winsize-1); x < (1 << winsize); x++) \{ -061 if ((err = mp_init(&M[x])) != MP_OKAY) \{ -062 for (y = 1<<(winsize-1); y < x; y++) \{ -063 mp_clear (&M[y]); -064 \} -065 mp_clear(&M[1]); -066 return err; -067 \} -068 \} -069 -070 /* create mu, used for Barrett reduction */ -071 if ((err = mp_init (&mu)) != MP_OKAY) \{ -072 goto LBL_M; -073 \} -074 -075 if (redmode == 0) \{ -076 if ((err = mp_reduce_setup (&mu, P)) != MP_OKAY) \{ -077 goto LBL_MU; -078 \} -079 redux = mp_reduce; -080 \} else \{ -081 if ((err = mp_reduce_2k_setup_l (P, &mu)) != MP_OKAY) \{ -082 goto LBL_MU; -083 \} -084 redux = mp_reduce_2k_l; -085 \} -086 -087 /* create M table -088 * -089 * The M table contains powers of the base, -090 * e.g. M[x] = G**x mod P -091 * -092 * The first half of the table is not -093 * computed though accept for M[0] and M[1] -094 */ -095 if ((err = mp_mod (G, P, &M[1])) != MP_OKAY) \{ -096 goto LBL_MU; -097 \} -098 -099 /* compute the value at M[1<<(winsize-1)] by squaring -100 * M[1] (winsize-1) times -101 */ -102 if ((err = mp_copy (&M[1], &M[1 << (winsize - 1)])) != MP_OKAY) \{ -103 goto LBL_MU; -104 \} -105 -106 for (x = 0; x < (winsize - 1); x++) \{ -107 /* square it */ -108 if ((err = mp_sqr (&M[1 << (winsize - 1)], -109 &M[1 << (winsize - 1)])) != MP_OKAY) \{ -110 goto LBL_MU; -111 \} -112 -113 /* reduce modulo P */ -114 if ((err = redux (&M[1 << (winsize - 1)], P, &mu)) != MP_OKAY) \{ -115 goto LBL_MU; -116 \} -117 \} -118 -119 /* create upper table, that is M[x] = M[x-1] * M[1] (mod P) -120 * for x = (2**(winsize - 1) + 1) to (2**winsize - 1) -121 */ -122 for (x = (1 << (winsize - 1)) + 1; x < (1 << winsize); x++) \{ -123 if ((err = mp_mul (&M[x - 1], &M[1], &M[x])) != MP_OKAY) \{ -124 goto LBL_MU; -125 \} -126 if ((err = redux (&M[x], P, &mu)) != MP_OKAY) \{ -127 goto LBL_MU; -128 \} -129 \} -130 -131 /* setup result */ -132 if ((err = mp_init (&res)) != MP_OKAY) \{ -133 goto LBL_MU; -134 \} -135 mp_set (&res, 1); -136 -137 /* set initial mode and bit cnt */ -138 mode = 0; -139 bitcnt = 1; -140 buf = 0; -141 digidx = X->used - 1; -142 bitcpy = 0; -143 bitbuf = 0; -144 -145 for (;;) \{ -146 /* grab next digit as required */ -147 if (--bitcnt == 0) \{ -148 /* if digidx == -1 we are out of digits */ -149 if (digidx == -1) \{ -150 break; -151 \} -152 /* read next digit and reset the bitcnt */ -153 buf = X->dp[digidx--]; -154 bitcnt = (int) DIGIT_BIT; -155 \} -156 -157 /* grab the next msb from the exponent */ -158 y = (buf >> (mp_digit)(DIGIT_BIT - 1)) & 1; -159 buf <<= (mp_digit)1; -160 -161 /* if the bit is zero and mode == 0 then we ignore it -162 * These represent the leading zero bits before the first 1 bit -163 * in the exponent. Technically this opt is not required but it -164 * does lower the # of trivial squaring/reductions used -165 */ -166 if ((mode == 0) && (y == 0)) \{ -167 continue; -168 \} -169 -170 /* if the bit is zero and mode == 1 then we square */ -171 if ((mode == 1) && (y == 0)) \{ -172 if ((err = mp_sqr (&res, &res)) != MP_OKAY) \{ -173 goto LBL_RES; -174 \} -175 if ((err = redux (&res, P, &mu)) != MP_OKAY) \{ -176 goto LBL_RES; -177 \} -178 continue; -179 \} -180 -181 /* else we add it to the window */ -182 bitbuf |= (y << (winsize - ++bitcpy)); -183 mode = 2; -184 -185 if (bitcpy == winsize) \{ -186 /* ok window is filled so square as required and multiply */ -187 /* square first */ -188 for (x = 0; x < winsize; x++) \{ -189 if ((err = mp_sqr (&res, &res)) != MP_OKAY) \{ -190 goto LBL_RES; -191 \} -192 if ((err = redux (&res, P, &mu)) != MP_OKAY) \{ -193 goto LBL_RES; -194 \} -195 \} -196 -197 /* then multiply */ -198 if ((err = mp_mul (&res, &M[bitbuf], &res)) != MP_OKAY) \{ -199 goto LBL_RES; -200 \} -201 if ((err = redux (&res, P, &mu)) != MP_OKAY) \{ -202 goto LBL_RES; -203 \} -204 -205 /* empty window and reset */ -206 bitcpy = 0; -207 bitbuf = 0; -208 mode = 1; -209 \} -210 \} -211 -212 /* if bits remain then square/multiply */ -213 if ((mode == 2) && (bitcpy > 0)) \{ -214 /* square then multiply if the bit is set */ -215 for (x = 0; x < bitcpy; x++) \{ -216 if ((err = mp_sqr (&res, &res)) != MP_OKAY) \{ -217 goto LBL_RES; -218 \} -219 if ((err = redux (&res, P, &mu)) != MP_OKAY) \{ -220 goto LBL_RES; -221 \} -222 -223 bitbuf <<= 1; -224 if ((bitbuf & (1 << winsize)) != 0) \{ -225 /* then multiply */ -226 if ((err = mp_mul (&res, &M[1], &res)) != MP_OKAY) \{ -227 goto LBL_RES; -228 \} -229 if ((err = redux (&res, P, &mu)) != MP_OKAY) \{ -230 goto LBL_RES; -231 \} -232 \} -233 \} -234 \} -235 -236 mp_exch (&res, Y); -237 err = MP_OKAY; -238 LBL_RES:mp_clear (&res); -239 LBL_MU:mp_clear (&mu); -240 LBL_M: -241 mp_clear(&M[1]); -242 for (x = 1<<(winsize-1); x < (1 << winsize); x++) \{ -243 mp_clear (&M[x]); -244 \} -245 return err; -246 \} -247 #endif -248 -\end{alltt} -\end{small} - -Lines 31 through 45 determine the optimal window size based on the length of the exponent in bits. The window divisions are sorted -from smallest to greatest so that in each \textbf{if} statement only one condition must be tested. For example, by the \textbf{if} statement -on line 37 the value of $x$ is already known to be greater than $140$. - -The conditional piece of code beginning on line 47 allows the window size to be restricted to five bits. This logic is used to ensure -the table of precomputed powers of $G$ remains relatively small. - -The for loop on line 60 initializes the $M$ array while lines 71 and 76 through 85 initialize the reduction -function that will be used for this modulus. - --- More later. - -\section{Quick Power of Two} -Calculating $b = 2^a$ can be performed much quicker than with any of the previous algorithms. Recall that a logical shift left $m << k$ is -equivalent to $m \cdot 2^k$. By this logic when $m = 1$ a quick power of two can be achieved. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_2expt}. \\ -\textbf{Input}. integer $b$ \\ -\textbf{Output}. $a \leftarrow 2^b$ \\ -\hline \\ -1. $a \leftarrow 0$ \\ -2. If $a.alloc < \lfloor b / lg(\beta) \rfloor + 1$ then grow $a$ appropriately. \\ -3. $a.used \leftarrow \lfloor b / lg(\beta) \rfloor + 1$ \\ -4. $a_{\lfloor b / lg(\beta) \rfloor} \leftarrow 1 << (b \mbox{ mod } lg(\beta))$ \\ -5. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_2expt} -\end{figure} - -\textbf{Algorithm mp\_2expt.} - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_2expt.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* computes a = 2**b -018 * -019 * Simple algorithm which zeroes the int, grows it then just sets one bit -020 * as required. -021 */ -022 int -023 mp_2expt (mp_int * a, int b) -024 \{ -025 int res; -026 -027 /* zero a as per default */ -028 mp_zero (a); -029 -030 /* grow a to accomodate the single bit */ -031 if ((res = mp_grow (a, (b / DIGIT_BIT) + 1)) != MP_OKAY) \{ -032 return res; -033 \} -034 -035 /* set the used count of where the bit will go */ -036 a->used = (b / DIGIT_BIT) + 1; -037 -038 /* put the single bit in its place */ -039 a->dp[b / DIGIT_BIT] = ((mp_digit)1) << (b % DIGIT_BIT); -040 -041 return MP_OKAY; -042 \} -043 #endif -044 -\end{alltt} -\end{small} - -\chapter{Higher Level Algorithms} - -This chapter discusses the various higher level algorithms that are required to complete a well rounded multiple precision integer package. These -routines are less performance oriented than the algorithms of chapters five, six and seven but are no less important. - -The first section describes a method of integer division with remainder that is universally well known. It provides the signed division logic -for the package. The subsequent section discusses a set of algorithms which allow a single digit to be the 2nd operand for a variety of operations. -These algorithms serve mostly to simplify other algorithms where small constants are required. The last two sections discuss how to manipulate -various representations of integers. For example, converting from an mp\_int to a string of character. - -\section{Integer Division with Remainder} -\label{sec:division} - -Integer division aside from modular exponentiation is the most intensive algorithm to compute. Like addition, subtraction and multiplication -the basis of this algorithm is the long-hand division algorithm taught to school children. Throughout this discussion several common variables -will be used. Let $x$ represent the divisor and $y$ represent the dividend. Let $q$ represent the integer quotient $\lfloor y / x \rfloor$ and -let $r$ represent the remainder $r = y - x \lfloor y / x \rfloor$. The following simple algorithm will be used to start the discussion. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{Radix-$\beta$ Integer Division}. \\ -\textbf{Input}. integer $x$ and $y$ \\ -\textbf{Output}. $q = \lfloor y/x\rfloor, r = y - xq$ \\ -\hline \\ -1. $q \leftarrow 0$ \\ -2. $n \leftarrow \vert \vert y \vert \vert - \vert \vert x \vert \vert$ \\ -3. for $t$ from $n$ down to $0$ do \\ -\hspace{3mm}3.1 Maximize $k$ such that $kx\beta^t$ is less than or equal to $y$ and $(k + 1)x\beta^t$ is greater. \\ -\hspace{3mm}3.2 $q \leftarrow q + k\beta^t$ \\ -\hspace{3mm}3.3 $y \leftarrow y - kx\beta^t$ \\ -4. $r \leftarrow y$ \\ -5. Return($q, r$) \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm Radix-$\beta$ Integer Division} -\label{fig:raddiv} -\end{figure} - -As children we are taught this very simple algorithm for the case of $\beta = 10$. Almost instinctively several optimizations are taught for which -their reason of existing are never explained. For this example let $y = 5471$ represent the dividend and $x = 23$ represent the divisor. - -To find the first digit of the quotient the value of $k$ must be maximized such that $kx\beta^t$ is less than or equal to $y$ and -simultaneously $(k + 1)x\beta^t$ is greater than $y$. Implicitly $k$ is the maximum value the $t$'th digit of the quotient may have. The habitual method -used to find the maximum is to ``eyeball'' the two numbers, typically only the leading digits and quickly estimate a quotient. By only using leading -digits a much simpler division may be used to form an educated guess at what the value must be. In this case $k = \lfloor 54/23\rfloor = 2$ quickly -arises as a possible solution. Indeed $2x\beta^2 = 4600$ is less than $y = 5471$ and simultaneously $(k + 1)x\beta^2 = 6900$ is larger than $y$. -As a result $k\beta^2$ is added to the quotient which now equals $q = 200$ and $4600$ is subtracted from $y$ to give a remainder of $y = 841$. - -Again this process is repeated to produce the quotient digit $k = 3$ which makes the quotient $q = 200 + 3\beta = 230$ and the remainder -$y = 841 - 3x\beta = 181$. Finally the last iteration of the loop produces $k = 7$ which leads to the quotient $q = 230 + 7 = 237$ and the -remainder $y = 181 - 7x = 20$. The final quotient and remainder found are $q = 237$ and $r = y = 20$ which are indeed correct since -$237 \cdot 23 + 20 = 5471$ is true. - -\subsection{Quotient Estimation} -\label{sec:divest} -As alluded to earlier the quotient digit $k$ can be estimated from only the leading digits of both the divisor and dividend. When $p$ leading -digits are used from both the divisor and dividend to form an estimation the accuracy of the estimation rises as $p$ grows. Technically -speaking the estimation is based on assuming the lower $\vert \vert y \vert \vert - p$ and $\vert \vert x \vert \vert - p$ lower digits of the -dividend and divisor are zero. - -The value of the estimation may off by a few values in either direction and in general is fairly correct. A simplification \cite[pp. 271]{TAOCPV2} -of the estimation technique is to use $t + 1$ digits of the dividend and $t$ digits of the divisor, in particularly when $t = 1$. The estimate -using this technique is never too small. For the following proof let $t = \vert \vert y \vert \vert - 1$ and $s = \vert \vert x \vert \vert - 1$ -represent the most significant digits of the dividend and divisor respectively. - -\textbf{Proof.}\textit{ The quotient $\hat k = \lfloor (y_t\beta + y_{t-1}) / x_s \rfloor$ is greater than or equal to -$k = \lfloor y / (x \cdot \beta^{\vert \vert y \vert \vert - \vert \vert x \vert \vert - 1}) \rfloor$. } -The first obvious case is when $\hat k = \beta - 1$ in which case the proof is concluded since the real quotient cannot be larger. For all other -cases $\hat k = \lfloor (y_t\beta + y_{t-1}) / x_s \rfloor$ and $\hat k x_s \ge y_t\beta + y_{t-1} - x_s + 1$. The latter portion of the inequalility -$-x_s + 1$ arises from the fact that a truncated integer division will give the same quotient for at most $x_s - 1$ values. Next a series of -inequalities will prove the hypothesis. - -\begin{equation} -y - \hat k x \le y - \hat k x_s\beta^s -\end{equation} - -This is trivially true since $x \ge x_s\beta^s$. Next we replace $\hat kx_s\beta^s$ by the previous inequality for $\hat kx_s$. - -\begin{equation} -y - \hat k x \le y_t\beta^t + \ldots + y_0 - (y_t\beta^t + y_{t-1}\beta^{t-1} - x_s\beta^t + \beta^s) -\end{equation} - -By simplifying the previous inequality the following inequality is formed. - -\begin{equation} -y - \hat k x \le y_{t-2}\beta^{t-2} + \ldots + y_0 + x_s\beta^s - \beta^s -\end{equation} - -Subsequently, - -\begin{equation} -y_{t-2}\beta^{t-2} + \ldots + y_0 + x_s\beta^s - \beta^s < x_s\beta^s \le x -\end{equation} - -Which proves that $y - \hat kx \le x$ and by consequence $\hat k \ge k$ which concludes the proof. \textbf{QED} - - -\subsection{Normalized Integers} -For the purposes of division a normalized input is when the divisors leading digit $x_n$ is greater than or equal to $\beta / 2$. By multiplying both -$x$ and $y$ by $j = \lfloor (\beta / 2) / x_n \rfloor$ the quotient remains unchanged and the remainder is simply $j$ times the original -remainder. The purpose of normalization is to ensure the leading digit of the divisor is sufficiently large such that the estimated quotient will -lie in the domain of a single digit. Consider the maximum dividend $(\beta - 1) \cdot \beta + (\beta - 1)$ and the minimum divisor $\beta / 2$. - -\begin{equation} -{{\beta^2 - 1} \over { \beta / 2}} \le 2\beta - {2 \over \beta} -\end{equation} - -At most the quotient approaches $2\beta$, however, in practice this will not occur since that would imply the previous quotient digit was too small. - -\subsection{Radix-$\beta$ Division with Remainder} -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_div}. \\ -\textbf{Input}. mp\_int $a, b$ \\ -\textbf{Output}. $c = \lfloor a/b \rfloor$, $d = a - bc$ \\ -\hline \\ -1. If $b = 0$ return(\textit{MP\_VAL}). \\ -2. If $\vert a \vert < \vert b \vert$ then do \\ -\hspace{3mm}2.1 $d \leftarrow a$ \\ -\hspace{3mm}2.2 $c \leftarrow 0$ \\ -\hspace{3mm}2.3 Return(\textit{MP\_OKAY}). \\ -\\ -Setup the quotient to receive the digits. \\ -3. Grow $q$ to $a.used + 2$ digits. \\ -4. $q \leftarrow 0$ \\ -5. $x \leftarrow \vert a \vert , y \leftarrow \vert b \vert$ \\ -6. $sign \leftarrow \left \lbrace \begin{array}{ll} - MP\_ZPOS & \mbox{if }a.sign = b.sign \\ - MP\_NEG & \mbox{otherwise} \\ - \end{array} \right .$ \\ -\\ -Normalize the inputs such that the leading digit of $y$ is greater than or equal to $\beta / 2$. \\ -7. $norm \leftarrow (lg(\beta) - 1) - (\lceil lg(y) \rceil \mbox{ (mod }lg(\beta)\mbox{)})$ \\ -8. $x \leftarrow x \cdot 2^{norm}, y \leftarrow y \cdot 2^{norm}$ \\ -\\ -Find the leading digit of the quotient. \\ -9. $n \leftarrow x.used - 1, t \leftarrow y.used - 1$ \\ -10. $y \leftarrow y \cdot \beta^{n - t}$ \\ -11. While ($x \ge y$) do \\ -\hspace{3mm}11.1 $q_{n - t} \leftarrow q_{n - t} + 1$ \\ -\hspace{3mm}11.2 $x \leftarrow x - y$ \\ -12. $y \leftarrow \lfloor y / \beta^{n-t} \rfloor$ \\ -\\ -Continued on the next page. \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_div} -\end{figure} - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_div} (continued). \\ -\textbf{Input}. mp\_int $a, b$ \\ -\textbf{Output}. $c = \lfloor a/b \rfloor$, $d = a - bc$ \\ -\hline \\ -Now find the remainder fo the digits. \\ -13. for $i$ from $n$ down to $(t + 1)$ do \\ -\hspace{3mm}13.1 If $i > x.used$ then jump to the next iteration of this loop. \\ -\hspace{3mm}13.2 If $x_{i} = y_{t}$ then \\ -\hspace{6mm}13.2.1 $q_{i - t - 1} \leftarrow \beta - 1$ \\ -\hspace{3mm}13.3 else \\ -\hspace{6mm}13.3.1 $\hat r \leftarrow x_{i} \cdot \beta + x_{i - 1}$ \\ -\hspace{6mm}13.3.2 $\hat r \leftarrow \lfloor \hat r / y_{t} \rfloor$ \\ -\hspace{6mm}13.3.3 $q_{i - t - 1} \leftarrow \hat r$ \\ -\hspace{3mm}13.4 $q_{i - t - 1} \leftarrow q_{i - t - 1} + 1$ \\ -\\ -Fixup quotient estimation. \\ -\hspace{3mm}13.5 Loop \\ -\hspace{6mm}13.5.1 $q_{i - t - 1} \leftarrow q_{i - t - 1} - 1$ \\ -\hspace{6mm}13.5.2 t$1 \leftarrow 0$ \\ -\hspace{6mm}13.5.3 t$1_0 \leftarrow y_{t - 1}, $ t$1_1 \leftarrow y_t,$ t$1.used \leftarrow 2$ \\ -\hspace{6mm}13.5.4 $t1 \leftarrow t1 \cdot q_{i - t - 1}$ \\ -\hspace{6mm}13.5.5 t$2_0 \leftarrow x_{i - 2}, $ t$2_1 \leftarrow x_{i - 1}, $ t$2_2 \leftarrow x_i, $ t$2.used \leftarrow 3$ \\ -\hspace{6mm}13.5.6 If $\vert t1 \vert > \vert t2 \vert$ then goto step 13.5. \\ -\hspace{3mm}13.6 t$1 \leftarrow y \cdot q_{i - t - 1}$ \\ -\hspace{3mm}13.7 t$1 \leftarrow $ t$1 \cdot \beta^{i - t - 1}$ \\ -\hspace{3mm}13.8 $x \leftarrow x - $ t$1$ \\ -\hspace{3mm}13.9 If $x.sign = MP\_NEG$ then \\ -\hspace{6mm}13.10 t$1 \leftarrow y$ \\ -\hspace{6mm}13.11 t$1 \leftarrow $ t$1 \cdot \beta^{i - t - 1}$ \\ -\hspace{6mm}13.12 $x \leftarrow x + $ t$1$ \\ -\hspace{6mm}13.13 $q_{i - t - 1} \leftarrow q_{i - t - 1} - 1$ \\ -\\ -Finalize the result. \\ -14. Clamp excess digits of $q$ \\ -15. $c \leftarrow q, c.sign \leftarrow sign$ \\ -16. $x.sign \leftarrow a.sign$ \\ -17. $d \leftarrow \lfloor x / 2^{norm} \rfloor$ \\ -18. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_div (continued)} -\end{figure} -\textbf{Algorithm mp\_div.} -This algorithm will calculate quotient and remainder from an integer division given a dividend and divisor. The algorithm is a signed -division and will produce a fully qualified quotient and remainder. - -First the divisor $b$ must be non-zero which is enforced in step one. If the divisor is larger than the dividend than the quotient is implicitly -zero and the remainder is the dividend. - -After the first two trivial cases of inputs are handled the variable $q$ is setup to receive the digits of the quotient. Two unsigned copies of the -divisor $y$ and dividend $x$ are made as well. The core of the division algorithm is an unsigned division and will only work if the values are -positive. Now the two values $x$ and $y$ must be normalized such that the leading digit of $y$ is greater than or equal to $\beta / 2$. -This is performed by shifting both to the left by enough bits to get the desired normalization. - -At this point the division algorithm can begin producing digits of the quotient. Recall that maximum value of the estimation used is -$2\beta - {2 \over \beta}$ which means that a digit of the quotient must be first produced by another means. In this case $y$ is shifted -to the left (\textit{step ten}) so that it has the same number of digits as $x$. The loop on step eleven will subtract multiples of the -shifted copy of $y$ until $x$ is smaller. Since the leading digit of $y$ is greater than or equal to $\beta/2$ this loop will iterate at most two -times to produce the desired leading digit of the quotient. - -Now the remainder of the digits can be produced. The equation $\hat q = \lfloor {{x_i \beta + x_{i-1}}\over y_t} \rfloor$ is used to fairly -accurately approximate the true quotient digit. The estimation can in theory produce an estimation as high as $2\beta - {2 \over \beta}$ but by -induction the upper quotient digit is correct (\textit{as established on step eleven}) and the estimate must be less than $\beta$. - -Recall from section~\ref{sec:divest} that the estimation is never too low but may be too high. The next step of the estimation process is -to refine the estimation. The loop on step 13.5 uses $x_i\beta^2 + x_{i-1}\beta + x_{i-2}$ and $q_{i - t - 1}(y_t\beta + y_{t-1})$ as a higher -order approximation to adjust the quotient digit. - -After both phases of estimation the quotient digit may still be off by a value of one\footnote{This is similar to the error introduced -by optimizing Barrett reduction.}. Steps 13.6 and 13.7 subtract the multiple of the divisor from the dividend (\textit{Similar to step 3.3 of -algorithm~\ref{fig:raddiv}} and then subsequently add a multiple of the divisor if the quotient was too large. - -Now that the quotient has been determine finializing the result is a matter of clamping the quotient, fixing the sizes and de-normalizing the -remainder. An important aspect of this algorithm seemingly overlooked in other descriptions such as that of Algorithm 14.20 HAC \cite[pp. 598]{HAC} -is that when the estimations are being made (\textit{inside the loop on step 13.5}) that the digits $y_{t-1}$, $x_{i-2}$ and $x_{i-1}$ may lie -outside their respective boundaries. For example, if $t = 0$ or $i \le 1$ then the digits would be undefined. In those cases the digits should -respectively be replaced with a zero. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_div.c -\vspace{-3mm} -\begin{alltt} -016 -017 #ifdef BN_MP_DIV_SMALL -018 -019 /* slower bit-bang division... also smaller */ -020 int mp_div(mp_int * a, mp_int * b, mp_int * c, mp_int * d) -021 \{ -022 mp_int ta, tb, tq, q; -023 int res, n, n2; -024 -025 /* is divisor zero ? */ -026 if (mp_iszero (b) == MP_YES) \{ -027 return MP_VAL; -028 \} -029 -030 /* if a < b then q=0, r = a */ -031 if (mp_cmp_mag (a, b) == MP_LT) \{ -032 if (d != NULL) \{ -033 res = mp_copy (a, d); -034 \} else \{ -035 res = MP_OKAY; -036 \} -037 if (c != NULL) \{ -038 mp_zero (c); -039 \} -040 return res; -041 \} -042 -043 /* init our temps */ -044 if ((res = mp_init_multi(&ta, &tb, &tq, &q, NULL)) != MP_OKAY) \{ -045 return res; -046 \} -047 -048 -049 mp_set(&tq, 1); -050 n = mp_count_bits(a) - mp_count_bits(b); -051 if (((res = mp_abs(a, &ta)) != MP_OKAY) || -052 ((res = mp_abs(b, &tb)) != MP_OKAY) || -053 ((res = mp_mul_2d(&tb, n, &tb)) != MP_OKAY) || -054 ((res = mp_mul_2d(&tq, n, &tq)) != MP_OKAY)) \{ -055 goto LBL_ERR; -056 \} -057 -058 while (n-- >= 0) \{ -059 if (mp_cmp(&tb, &ta) != MP_GT) \{ -060 if (((res = mp_sub(&ta, &tb, &ta)) != MP_OKAY) || -061 ((res = mp_add(&q, &tq, &q)) != MP_OKAY)) \{ -062 goto LBL_ERR; -063 \} -064 \} -065 if (((res = mp_div_2d(&tb, 1, &tb, NULL)) != MP_OKAY) || -066 ((res = mp_div_2d(&tq, 1, &tq, NULL)) != MP_OKAY)) \{ -067 goto LBL_ERR; -068 \} -069 \} -070 -071 /* now q == quotient and ta == remainder */ -072 n = a->sign; -073 n2 = (a->sign == b->sign) ? MP_ZPOS : MP_NEG; -074 if (c != NULL) \{ -075 mp_exch(c, &q); -076 c->sign = (mp_iszero(c) == MP_YES) ? MP_ZPOS : n2; -077 \} -078 if (d != NULL) \{ -079 mp_exch(d, &ta); -080 d->sign = (mp_iszero(d) == MP_YES) ? MP_ZPOS : n; -081 \} -082 LBL_ERR: -083 mp_clear_multi(&ta, &tb, &tq, &q, NULL); -084 return res; -085 \} -086 -087 #else -088 -089 /* integer signed division. -090 * c*b + d == a [e.g. a/b, c=quotient, d=remainder] -091 * HAC pp.598 Algorithm 14.20 -092 * -093 * Note that the description in HAC is horribly -094 * incomplete. For example, it doesn't consider -095 * the case where digits are removed from 'x' in -096 * the inner loop. It also doesn't consider the -097 * case that y has fewer than three digits, etc.. -098 * -099 * The overall algorithm is as described as -100 * 14.20 from HAC but fixed to treat these cases. -101 */ -102 int mp_div (mp_int * a, mp_int * b, mp_int * c, mp_int * d) -103 \{ -104 mp_int q, x, y, t1, t2; -105 int res, n, t, i, norm, neg; -106 -107 /* is divisor zero ? */ -108 if (mp_iszero (b) == MP_YES) \{ -109 return MP_VAL; -110 \} -111 -112 /* if a < b then q=0, r = a */ -113 if (mp_cmp_mag (a, b) == MP_LT) \{ -114 if (d != NULL) \{ -115 res = mp_copy (a, d); -116 \} else \{ -117 res = MP_OKAY; -118 \} -119 if (c != NULL) \{ -120 mp_zero (c); -121 \} -122 return res; -123 \} -124 -125 if ((res = mp_init_size (&q, a->used + 2)) != MP_OKAY) \{ -126 return res; -127 \} -128 q.used = a->used + 2; -129 -130 if ((res = mp_init (&t1)) != MP_OKAY) \{ -131 goto LBL_Q; -132 \} -133 -134 if ((res = mp_init (&t2)) != MP_OKAY) \{ -135 goto LBL_T1; -136 \} -137 -138 if ((res = mp_init_copy (&x, a)) != MP_OKAY) \{ -139 goto LBL_T2; -140 \} -141 -142 if ((res = mp_init_copy (&y, b)) != MP_OKAY) \{ -143 goto LBL_X; -144 \} -145 -146 /* fix the sign */ -147 neg = (a->sign == b->sign) ? MP_ZPOS : MP_NEG; -148 x.sign = y.sign = MP_ZPOS; -149 -150 /* normalize both x and y, ensure that y >= b/2, [b == 2**DIGIT_BIT] */ -151 norm = mp_count_bits(&y) % DIGIT_BIT; -152 if (norm < (int)(DIGIT_BIT-1)) \{ -153 norm = (DIGIT_BIT-1) - norm; -154 if ((res = mp_mul_2d (&x, norm, &x)) != MP_OKAY) \{ -155 goto LBL_Y; -156 \} -157 if ((res = mp_mul_2d (&y, norm, &y)) != MP_OKAY) \{ -158 goto LBL_Y; -159 \} -160 \} else \{ -161 norm = 0; -162 \} -163 -164 /* note hac does 0 based, so if used==5 then its 0,1,2,3,4, e.g. use 4 */ -165 n = x.used - 1; -166 t = y.used - 1; -167 -168 /* while (x >= y*b**n-t) do \{ q[n-t] += 1; x -= y*b**\{n-t\} \} */ -169 if ((res = mp_lshd (&y, n - t)) != MP_OKAY) \{ /* y = y*b**\{n-t\} */ -170 goto LBL_Y; -171 \} -172 -173 while (mp_cmp (&x, &y) != MP_LT) \{ -174 ++(q.dp[n - t]); -175 if ((res = mp_sub (&x, &y, &x)) != MP_OKAY) \{ -176 goto LBL_Y; -177 \} -178 \} -179 -180 /* reset y by shifting it back down */ -181 mp_rshd (&y, n - t); -182 -183 /* step 3. for i from n down to (t + 1) */ -184 for (i = n; i >= (t + 1); i--) \{ -185 if (i > x.used) \{ -186 continue; -187 \} -188 -189 /* step 3.1 if xi == yt then set q\{i-t-1\} to b-1, -190 * otherwise set q\{i-t-1\} to (xi*b + x\{i-1\})/yt */ -191 if (x.dp[i] == y.dp[t]) \{ -192 q.dp[(i - t) - 1] = ((((mp_digit)1) << DIGIT_BIT) - 1); -193 \} else \{ -194 mp_word tmp; -195 tmp = ((mp_word) x.dp[i]) << ((mp_word) DIGIT_BIT); -196 tmp |= ((mp_word) x.dp[i - 1]); -197 tmp /= ((mp_word) y.dp[t]); -198 if (tmp > (mp_word) MP_MASK) \{ -199 tmp = MP_MASK; -200 \} -201 q.dp[(i - t) - 1] = (mp_digit) (tmp & (mp_word) (MP_MASK)); -202 \} -203 -204 /* while (q\{i-t-1\} * (yt * b + y\{t-1\})) > -205 xi * b**2 + xi-1 * b + xi-2 -206 -207 do q\{i-t-1\} -= 1; -208 */ -209 q.dp[(i - t) - 1] = (q.dp[(i - t) - 1] + 1) & MP_MASK; -210 do \{ -211 q.dp[(i - t) - 1] = (q.dp[(i - t) - 1] - 1) & MP_MASK; -212 -213 /* find left hand */ -214 mp_zero (&t1); -215 t1.dp[0] = ((t - 1) < 0) ? 0 : y.dp[t - 1]; -216 t1.dp[1] = y.dp[t]; -217 t1.used = 2; -218 if ((res = mp_mul_d (&t1, q.dp[(i - t) - 1], &t1)) != MP_OKAY) \{ -219 goto LBL_Y; -220 \} -221 -222 /* find right hand */ -223 t2.dp[0] = ((i - 2) < 0) ? 0 : x.dp[i - 2]; -224 t2.dp[1] = ((i - 1) < 0) ? 0 : x.dp[i - 1]; -225 t2.dp[2] = x.dp[i]; -226 t2.used = 3; -227 \} while (mp_cmp_mag(&t1, &t2) == MP_GT); -228 -229 /* step 3.3 x = x - q\{i-t-1\} * y * b**\{i-t-1\} */ -230 if ((res = mp_mul_d (&y, q.dp[(i - t) - 1], &t1)) != MP_OKAY) \{ -231 goto LBL_Y; -232 \} -233 -234 if ((res = mp_lshd (&t1, (i - t) - 1)) != MP_OKAY) \{ -235 goto LBL_Y; -236 \} -237 -238 if ((res = mp_sub (&x, &t1, &x)) != MP_OKAY) \{ -239 goto LBL_Y; -240 \} -241 -242 /* if x < 0 then \{ x = x + y*b**\{i-t-1\}; q\{i-t-1\} -= 1; \} */ -243 if (x.sign == MP_NEG) \{ -244 if ((res = mp_copy (&y, &t1)) != MP_OKAY) \{ -245 goto LBL_Y; -246 \} -247 if ((res = mp_lshd (&t1, (i - t) - 1)) != MP_OKAY) \{ -248 goto LBL_Y; -249 \} -250 if ((res = mp_add (&x, &t1, &x)) != MP_OKAY) \{ -251 goto LBL_Y; -252 \} -253 -254 q.dp[(i - t) - 1] = (q.dp[(i - t) - 1] - 1UL) & MP_MASK; -255 \} -256 \} -257 -258 /* now q is the quotient and x is the remainder -259 * [which we have to normalize] -260 */ -261 -262 /* get sign before writing to c */ -263 x.sign = (x.used == 0) ? MP_ZPOS : a->sign; -264 -265 if (c != NULL) \{ -266 mp_clamp (&q); -267 mp_exch (&q, c); -268 c->sign = neg; -269 \} -270 -271 if (d != NULL) \{ -272 if ((res = mp_div_2d (&x, norm, &x, NULL)) != MP_OKAY) \{ -273 goto LBL_Y; -274 \} -275 mp_exch (&x, d); -276 \} -277 -278 res = MP_OKAY; -279 -280 LBL_Y:mp_clear (&y); -281 LBL_X:mp_clear (&x); -282 LBL_T2:mp_clear (&t2); -283 LBL_T1:mp_clear (&t1); -284 LBL_Q:mp_clear (&q); -285 return res; -286 \} -287 -288 #endif -289 -290 #endif -291 -\end{alltt} -\end{small} - -The implementation of this algorithm differs slightly from the pseudo code presented previously. In this algorithm either of the quotient $c$ or -remainder $d$ may be passed as a \textbf{NULL} pointer which indicates their value is not desired. For example, the C code to call the division -algorithm with only the quotient is - -\begin{verbatim} -mp_div(&a, &b, &c, NULL); /* c = [a/b] */ -\end{verbatim} - -Lines 108 and 113 handle the two trivial cases of inputs which are division by zero and dividend smaller than the divisor -respectively. After the two trivial cases all of the temporary variables are initialized. Line 147 determines the sign of -the quotient and line 148 ensures that both $x$ and $y$ are positive. - -The number of bits in the leading digit is calculated on line 151. Implictly an mp\_int with $r$ digits will require $lg(\beta)(r-1) + k$ bits -of precision which when reduced modulo $lg(\beta)$ produces the value of $k$. In this case $k$ is the number of bits in the leading digit which is -exactly what is required. For the algorithm to operate $k$ must equal $lg(\beta) - 1$ and when it does not the inputs must be normalized by shifting -them to the left by $lg(\beta) - 1 - k$ bits. - -Throughout the variables $n$ and $t$ will represent the highest digit of $x$ and $y$ respectively. These are first used to produce the -leading digit of the quotient. The loop beginning on line 184 will produce the remainder of the quotient digits. - -The conditional ``continue'' on line 186 is used to prevent the algorithm from reading past the leading edge of $x$ which can occur when the -algorithm eliminates multiple non-zero digits in a single iteration. This ensures that $x_i$ is always non-zero since by definition the digits -above the $i$'th position $x$ must be zero in order for the quotient to be precise\footnote{Precise as far as integer division is concerned.}. - -Lines 214, 216 and 223 through 225 manually construct the high accuracy estimations by setting the digits of the two mp\_int -variables directly. - -\section{Single Digit Helpers} - -This section briefly describes a series of single digit helper algorithms which come in handy when working with small constants. All of -the helper functions assume the single digit input is positive and will treat them as such. - -\subsection{Single Digit Addition and Subtraction} - -Both addition and subtraction are performed by ``cheating'' and using mp\_set followed by the higher level addition or subtraction -algorithms. As a result these algorithms are subtantially simpler with a slight cost in performance. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_add\_d}. \\ -\textbf{Input}. mp\_int $a$ and a mp\_digit $b$ \\ -\textbf{Output}. $c = a + b$ \\ -\hline \\ -1. $t \leftarrow b$ (\textit{mp\_set}) \\ -2. $c \leftarrow a + t$ \\ -3. Return(\textit{MP\_OKAY}) \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_add\_d} -\end{figure} - -\textbf{Algorithm mp\_add\_d.} -This algorithm initiates a temporary mp\_int with the value of the single digit and uses algorithm mp\_add to add the two values together. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_add\_d.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* single digit addition */ -018 int -019 mp_add_d (mp_int * a, mp_digit b, mp_int * c) -020 \{ -021 int res, ix, oldused; -022 mp_digit *tmpa, *tmpc, mu; -023 -024 /* grow c as required */ -025 if (c->alloc < (a->used + 1)) \{ -026 if ((res = mp_grow(c, a->used + 1)) != MP_OKAY) \{ -027 return res; -028 \} -029 \} -030 -031 /* if a is negative and |a| >= b, call c = |a| - b */ -032 if ((a->sign == MP_NEG) && ((a->used > 1) || (a->dp[0] >= b))) \{ -033 /* temporarily fix sign of a */ -034 a->sign = MP_ZPOS; -035 -036 /* c = |a| - b */ -037 res = mp_sub_d(a, b, c); -038 -039 /* fix sign */ -040 a->sign = c->sign = MP_NEG; -041 -042 /* clamp */ -043 mp_clamp(c); -044 -045 return res; -046 \} -047 -048 /* old number of used digits in c */ -049 oldused = c->used; -050 -051 /* sign always positive */ -052 c->sign = MP_ZPOS; -053 -054 /* source alias */ -055 tmpa = a->dp; -056 -057 /* destination alias */ -058 tmpc = c->dp; -059 -060 /* if a is positive */ -061 if (a->sign == MP_ZPOS) \{ -062 /* add digit, after this we're propagating -063 * the carry. -064 */ -065 *tmpc = *tmpa++ + b; -066 mu = *tmpc >> DIGIT_BIT; -067 *tmpc++ &= MP_MASK; -068 -069 /* now handle rest of the digits */ -070 for (ix = 1; ix < a->used; ix++) \{ -071 *tmpc = *tmpa++ + mu; -072 mu = *tmpc >> DIGIT_BIT; -073 *tmpc++ &= MP_MASK; -074 \} -075 /* set final carry */ -076 ix++; -077 *tmpc++ = mu; -078 -079 /* setup size */ -080 c->used = a->used + 1; -081 \} else \{ -082 /* a was negative and |a| < b */ -083 c->used = 1; -084 -085 /* the result is a single digit */ -086 if (a->used == 1) \{ -087 *tmpc++ = b - a->dp[0]; -088 \} else \{ -089 *tmpc++ = b; -090 \} -091 -092 /* setup count so the clearing of oldused -093 * can fall through correctly -094 */ -095 ix = 1; -096 \} -097 -098 /* now zero to oldused */ -099 while (ix++ < oldused) \{ -100 *tmpc++ = 0; -101 \} -102 mp_clamp(c); -103 -104 return MP_OKAY; -105 \} -106 -107 #endif -108 -\end{alltt} -\end{small} - -Clever use of the letter 't'. - -\subsubsection{Subtraction} -The single digit subtraction algorithm mp\_sub\_d is essentially the same except it uses mp\_sub to subtract the digit from the mp\_int. - -\subsection{Single Digit Multiplication} -Single digit multiplication arises enough in division and radix conversion that it ought to be implement as a special case of the baseline -multiplication algorithm. Essentially this algorithm is a modified version of algorithm s\_mp\_mul\_digs where one of the multiplicands -only has one digit. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_mul\_d}. \\ -\textbf{Input}. mp\_int $a$ and a mp\_digit $b$ \\ -\textbf{Output}. $c = ab$ \\ -\hline \\ -1. $pa \leftarrow a.used$ \\ -2. Grow $c$ to at least $pa + 1$ digits. \\ -3. $oldused \leftarrow c.used$ \\ -4. $c.used \leftarrow pa + 1$ \\ -5. $c.sign \leftarrow a.sign$ \\ -6. $\mu \leftarrow 0$ \\ -7. for $ix$ from $0$ to $pa - 1$ do \\ -\hspace{3mm}7.1 $\hat r \leftarrow \mu + a_{ix}b$ \\ -\hspace{3mm}7.2 $c_{ix} \leftarrow \hat r \mbox{ (mod }\beta\mbox{)}$ \\ -\hspace{3mm}7.3 $\mu \leftarrow \lfloor \hat r / \beta \rfloor$ \\ -8. $c_{pa} \leftarrow \mu$ \\ -9. for $ix$ from $pa + 1$ to $oldused$ do \\ -\hspace{3mm}9.1 $c_{ix} \leftarrow 0$ \\ -10. Clamp excess digits of $c$. \\ -11. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_mul\_d} -\end{figure} -\textbf{Algorithm mp\_mul\_d.} -This algorithm quickly multiplies an mp\_int by a small single digit value. It is specially tailored to the job and has a minimal of overhead. -Unlike the full multiplication algorithms this algorithm does not require any significnat temporary storage or memory allocations. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_mul\_d.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* multiply by a digit */ -018 int -019 mp_mul_d (mp_int * a, mp_digit b, mp_int * c) -020 \{ -021 mp_digit u, *tmpa, *tmpc; -022 mp_word r; -023 int ix, res, olduse; -024 -025 /* make sure c is big enough to hold a*b */ -026 if (c->alloc < (a->used + 1)) \{ -027 if ((res = mp_grow (c, a->used + 1)) != MP_OKAY) \{ -028 return res; -029 \} -030 \} -031 -032 /* get the original destinations used count */ -033 olduse = c->used; -034 -035 /* set the sign */ -036 c->sign = a->sign; -037 -038 /* alias for a->dp [source] */ -039 tmpa = a->dp; -040 -041 /* alias for c->dp [dest] */ -042 tmpc = c->dp; -043 -044 /* zero carry */ -045 u = 0; -046 -047 /* compute columns */ -048 for (ix = 0; ix < a->used; ix++) \{ -049 /* compute product and carry sum for this term */ -050 r = (mp_word)u + ((mp_word)*tmpa++ * (mp_word)b); -051 -052 /* mask off higher bits to get a single digit */ -053 *tmpc++ = (mp_digit) (r & ((mp_word) MP_MASK)); -054 -055 /* send carry into next iteration */ -056 u = (mp_digit) (r >> ((mp_word) DIGIT_BIT)); -057 \} -058 -059 /* store final carry [if any] and increment ix offset */ -060 *tmpc++ = u; -061 ++ix; -062 -063 /* now zero digits above the top */ -064 while (ix++ < olduse) \{ -065 *tmpc++ = 0; -066 \} -067 -068 /* set used count */ -069 c->used = a->used + 1; -070 mp_clamp(c); -071 -072 return MP_OKAY; -073 \} -074 #endif -075 -\end{alltt} -\end{small} - -In this implementation the destination $c$ may point to the same mp\_int as the source $a$ since the result is written after the digit is -read from the source. This function uses pointer aliases $tmpa$ and $tmpc$ for the digits of $a$ and $c$ respectively. - -\subsection{Single Digit Division} -Like the single digit multiplication algorithm, single digit division is also a fairly common algorithm used in radix conversion. Since the -divisor is only a single digit a specialized variant of the division algorithm can be used to compute the quotient. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_div\_d}. \\ -\textbf{Input}. mp\_int $a$ and a mp\_digit $b$ \\ -\textbf{Output}. $c = \lfloor a / b \rfloor, d = a - cb$ \\ -\hline \\ -1. If $b = 0$ then return(\textit{MP\_VAL}).\\ -2. If $b = 3$ then use algorithm mp\_div\_3 instead. \\ -3. Init $q$ to $a.used$ digits. \\ -4. $q.used \leftarrow a.used$ \\ -5. $q.sign \leftarrow a.sign$ \\ -6. $\hat w \leftarrow 0$ \\ -7. for $ix$ from $a.used - 1$ down to $0$ do \\ -\hspace{3mm}7.1 $\hat w \leftarrow \hat w \beta + a_{ix}$ \\ -\hspace{3mm}7.2 If $\hat w \ge b$ then \\ -\hspace{6mm}7.2.1 $t \leftarrow \lfloor \hat w / b \rfloor$ \\ -\hspace{6mm}7.2.2 $\hat w \leftarrow \hat w \mbox{ (mod }b\mbox{)}$ \\ -\hspace{3mm}7.3 else\\ -\hspace{6mm}7.3.1 $t \leftarrow 0$ \\ -\hspace{3mm}7.4 $q_{ix} \leftarrow t$ \\ -8. $d \leftarrow \hat w$ \\ -9. Clamp excess digits of $q$. \\ -10. $c \leftarrow q$ \\ -11. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_div\_d} -\end{figure} -\textbf{Algorithm mp\_div\_d.} -This algorithm divides the mp\_int $a$ by the single mp\_digit $b$ using an optimized approach. Essentially in every iteration of the -algorithm another digit of the dividend is reduced and another digit of quotient produced. Provided $b < \beta$ the value of $\hat w$ -after step 7.1 will be limited such that $0 \le \lfloor \hat w / b \rfloor < \beta$. - -If the divisor $b$ is equal to three a variant of this algorithm is used which is called mp\_div\_3. It replaces the division by three with -a multiplication by $\lfloor \beta / 3 \rfloor$ and the appropriate shift and residual fixup. In essence it is much like the Barrett reduction -from chapter seven. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_div\_d.c -\vspace{-3mm} -\begin{alltt} -016 -017 static int s_is_power_of_two(mp_digit b, int *p) -018 \{ -019 int x; -020 -021 /* fast return if no power of two */ -022 if ((b == 0) || ((b & (b-1)) != 0)) \{ -023 return 0; -024 \} -025 -026 for (x = 0; x < DIGIT_BIT; x++) \{ -027 if (b == (((mp_digit)1)<<x)) \{ -028 *p = x; -029 return 1; -030 \} -031 \} -032 return 0; -033 \} -034 -035 /* single digit division (based on routine from MPI) */ -036 int mp_div_d (mp_int * a, mp_digit b, mp_int * c, mp_digit * d) -037 \{ -038 mp_int q; -039 mp_word w; -040 mp_digit t; -041 int res, ix; -042 -043 /* cannot divide by zero */ -044 if (b == 0) \{ -045 return MP_VAL; -046 \} -047 -048 /* quick outs */ -049 if ((b == 1) || (mp_iszero(a) == MP_YES)) \{ -050 if (d != NULL) \{ -051 *d = 0; -052 \} -053 if (c != NULL) \{ -054 return mp_copy(a, c); -055 \} -056 return MP_OKAY; -057 \} -058 -059 /* power of two ? */ -060 if (s_is_power_of_two(b, &ix) == 1) \{ -061 if (d != NULL) \{ -062 *d = a->dp[0] & ((((mp_digit)1)<<ix) - 1); -063 \} -064 if (c != NULL) \{ -065 return mp_div_2d(a, ix, c, NULL); -066 \} -067 return MP_OKAY; -068 \} -069 -070 #ifdef BN_MP_DIV_3_C -071 /* three? */ -072 if (b == 3) \{ -073 return mp_div_3(a, c, d); -074 \} -075 #endif -076 -077 /* no easy answer [c'est la vie]. Just division */ -078 if ((res = mp_init_size(&q, a->used)) != MP_OKAY) \{ -079 return res; -080 \} -081 -082 q.used = a->used; -083 q.sign = a->sign; -084 w = 0; -085 for (ix = a->used - 1; ix >= 0; ix--) \{ -086 w = (w << ((mp_word)DIGIT_BIT)) | ((mp_word)a->dp[ix]); -087 -088 if (w >= b) \{ -089 t = (mp_digit)(w / b); -090 w -= ((mp_word)t) * ((mp_word)b); -091 \} else \{ -092 t = 0; -093 \} -094 q.dp[ix] = (mp_digit)t; -095 \} -096 -097 if (d != NULL) \{ -098 *d = (mp_digit)w; -099 \} -100 -101 if (c != NULL) \{ -102 mp_clamp(&q); -103 mp_exch(&q, c); -104 \} -105 mp_clear(&q); -106 -107 return res; -108 \} -109 -110 #endif -111 -\end{alltt} -\end{small} - -Like the implementation of algorithm mp\_div this algorithm allows either of the quotient or remainder to be passed as a \textbf{NULL} pointer to -indicate the respective value is not required. This allows a trivial single digit modular reduction algorithm, mp\_mod\_d to be created. - -The division and remainder on lines 89 and 90 can be replaced often by a single division on most processors. For example, the 32-bit x86 based -processors can divide a 64-bit quantity by a 32-bit quantity and produce the quotient and remainder simultaneously. Unfortunately the GCC -compiler does not recognize that optimization and will actually produce two function calls to find the quotient and remainder respectively. - -\subsection{Single Digit Root Extraction} - -Finding the $n$'th root of an integer is fairly easy as far as numerical analysis is concerned. Algorithms such as the Newton-Raphson approximation -(\ref{eqn:newton}) series will converge very quickly to a root for any continuous function $f(x)$. - -\begin{equation} -x_{i+1} = x_i - {f(x_i) \over f'(x_i)} -\label{eqn:newton} -\end{equation} - -In this case the $n$'th root is desired and $f(x) = x^n - a$ where $a$ is the integer of which the root is desired. The derivative of $f(x)$ is -simply $f'(x) = nx^{n - 1}$. Of particular importance is that this algorithm will be used over the integers not over the a more continuous domain -such as the real numbers. As a result the root found can be above the true root by few and must be manually adjusted. Ideally at the end of the -algorithm the $n$'th root $b$ of an integer $a$ is desired such that $b^n \le a$. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_n\_root}. \\ -\textbf{Input}. mp\_int $a$ and a mp\_digit $b$ \\ -\textbf{Output}. $c^b \le a$ \\ -\hline \\ -1. If $b$ is even and $a.sign = MP\_NEG$ return(\textit{MP\_VAL}). \\ -2. $sign \leftarrow a.sign$ \\ -3. $a.sign \leftarrow MP\_ZPOS$ \\ -4. t$2 \leftarrow 2$ \\ -5. Loop \\ -\hspace{3mm}5.1 t$1 \leftarrow $ t$2$ \\ -\hspace{3mm}5.2 t$3 \leftarrow $ t$1^{b - 1}$ \\ -\hspace{3mm}5.3 t$2 \leftarrow $ t$3 $ $\cdot$ t$1$ \\ -\hspace{3mm}5.4 t$2 \leftarrow $ t$2 - a$ \\ -\hspace{3mm}5.5 t$3 \leftarrow $ t$3 \cdot b$ \\ -\hspace{3mm}5.6 t$3 \leftarrow \lfloor $t$2 / $t$3 \rfloor$ \\ -\hspace{3mm}5.7 t$2 \leftarrow $ t$1 - $ t$3$ \\ -\hspace{3mm}5.8 If t$1 \ne $ t$2$ then goto step 5. \\ -6. Loop \\ -\hspace{3mm}6.1 t$2 \leftarrow $ t$1^b$ \\ -\hspace{3mm}6.2 If t$2 > a$ then \\ -\hspace{6mm}6.2.1 t$1 \leftarrow $ t$1 - 1$ \\ -\hspace{6mm}6.2.2 Goto step 6. \\ -7. $a.sign \leftarrow sign$ \\ -8. $c \leftarrow $ t$1$ \\ -9. $c.sign \leftarrow sign$ \\ -10. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_n\_root} -\end{figure} -\textbf{Algorithm mp\_n\_root.} -This algorithm finds the integer $n$'th root of an input using the Newton-Raphson approach. It is partially optimized based on the observation -that the numerator of ${f(x) \over f'(x)}$ can be derived from a partial denominator. That is at first the denominator is calculated by finding -$x^{b - 1}$. This value can then be multiplied by $x$ and have $a$ subtracted from it to find the numerator. This saves a total of $b - 1$ -multiplications by t$1$ inside the loop. - -The initial value of the approximation is t$2 = 2$ which allows the algorithm to start with very small values and quickly converge on the -root. Ideally this algorithm is meant to find the $n$'th root of an input where $n$ is bounded by $2 \le n \le 5$. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_n\_root.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* wrapper function for mp_n_root_ex() -018 * computes c = (a)**(1/b) such that (c)**b <= a and (c+1)**b > a -019 */ -020 int mp_n_root (mp_int * a, mp_digit b, mp_int * c) -021 \{ -022 return mp_n_root_ex(a, b, c, 0); -023 \} -024 -025 #endif -026 -\end{alltt} -\end{small} - -\section{Random Number Generation} - -Random numbers come up in a variety of activities from public key cryptography to simple simulations and various randomized algorithms. Pollard-Rho -factoring for example, can make use of random values as starting points to find factors of a composite integer. In this case the algorithm presented -is solely for simulations and not intended for cryptographic use. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_rand}. \\ -\textbf{Input}. An integer $b$ \\ -\textbf{Output}. A pseudo-random number of $b$ digits \\ -\hline \\ -1. $a \leftarrow 0$ \\ -2. If $b \le 0$ return(\textit{MP\_OKAY}) \\ -3. Pick a non-zero random digit $d$. \\ -4. $a \leftarrow a + d$ \\ -5. for $ix$ from 1 to $d - 1$ do \\ -\hspace{3mm}5.1 $a \leftarrow a \cdot \beta$ \\ -\hspace{3mm}5.2 Pick a random digit $d$. \\ -\hspace{3mm}5.3 $a \leftarrow a + d$ \\ -6. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_rand} -\end{figure} -\textbf{Algorithm mp\_rand.} -This algorithm produces a pseudo-random integer of $b$ digits. By ensuring that the first digit is non-zero the algorithm also guarantees that the -final result has at least $b$ digits. It relies heavily on a third-part random number generator which should ideally generate uniformly all of -the integers from $0$ to $\beta - 1$. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_rand.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* makes a pseudo-random int of a given size */ -018 int -019 mp_rand (mp_int * a, int digits) -020 \{ -021 int res; -022 mp_digit d; -023 -024 mp_zero (a); -025 if (digits <= 0) \{ -026 return MP_OKAY; -027 \} -028 -029 /* first place a random non-zero digit */ -030 do \{ -031 d = ((mp_digit) abs (MP_GEN_RANDOM())) & MP_MASK; -032 \} while (d == 0); -033 -034 if ((res = mp_add_d (a, d, a)) != MP_OKAY) \{ -035 return res; -036 \} -037 -038 while (--digits > 0) \{ -039 if ((res = mp_lshd (a, 1)) != MP_OKAY) \{ -040 return res; -041 \} -042 -043 if ((res = mp_add_d (a, ((mp_digit) abs (MP_GEN_RANDOM())), a)) != MP_OK - AY) \{ -044 return res; -045 \} -046 \} -047 -048 return MP_OKAY; -049 \} -050 #endif -051 -\end{alltt} -\end{small} - -\section{Formatted Representations} -The ability to emit a radix-$n$ textual representation of an integer is useful for interacting with human parties. For example, the ability to -be given a string of characters such as ``114585'' and turn it into the radix-$\beta$ equivalent would make it easier to enter numbers -into a program. - -\subsection{Reading Radix-n Input} -For the purposes of this text we will assume that a simple lower ASCII map (\ref{fig:ASC}) is used for the values of from $0$ to $63$ to -printable characters. For example, when the character ``N'' is read it represents the integer $23$. The first $16$ characters of the -map are for the common representations up to hexadecimal. After that they match the ``base64'' encoding scheme which are suitable chosen -such that they are printable. While outputting as base64 may not be too helpful for human operators it does allow communication via non binary -mediums. - -\newpage\begin{figure}[here] -\begin{center} -\begin{tabular}{cc|cc|cc|cc} -\hline \textbf{Value} & \textbf{Char} & \textbf{Value} & \textbf{Char} & \textbf{Value} & \textbf{Char} & \textbf{Value} & \textbf{Char} \\ -\hline -0 & 0 & 1 & 1 & 2 & 2 & 3 & 3 \\ -4 & 4 & 5 & 5 & 6 & 6 & 7 & 7 \\ -8 & 8 & 9 & 9 & 10 & A & 11 & B \\ -12 & C & 13 & D & 14 & E & 15 & F \\ -16 & G & 17 & H & 18 & I & 19 & J \\ -20 & K & 21 & L & 22 & M & 23 & N \\ -24 & O & 25 & P & 26 & Q & 27 & R \\ -28 & S & 29 & T & 30 & U & 31 & V \\ -32 & W & 33 & X & 34 & Y & 35 & Z \\ -36 & a & 37 & b & 38 & c & 39 & d \\ -40 & e & 41 & f & 42 & g & 43 & h \\ -44 & i & 45 & j & 46 & k & 47 & l \\ -48 & m & 49 & n & 50 & o & 51 & p \\ -52 & q & 53 & r & 54 & s & 55 & t \\ -56 & u & 57 & v & 58 & w & 59 & x \\ -60 & y & 61 & z & 62 & $+$ & 63 & $/$ \\ -\hline -\end{tabular} -\end{center} -\caption{Lower ASCII Map} -\label{fig:ASC} -\end{figure} - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_read\_radix}. \\ -\textbf{Input}. A string $str$ of length $sn$ and radix $r$. \\ -\textbf{Output}. The radix-$\beta$ equivalent mp\_int. \\ -\hline \\ -1. If $r < 2$ or $r > 64$ return(\textit{MP\_VAL}). \\ -2. $ix \leftarrow 0$ \\ -3. If $str_0 =$ ``-'' then do \\ -\hspace{3mm}3.1 $ix \leftarrow ix + 1$ \\ -\hspace{3mm}3.2 $sign \leftarrow MP\_NEG$ \\ -4. else \\ -\hspace{3mm}4.1 $sign \leftarrow MP\_ZPOS$ \\ -5. $a \leftarrow 0$ \\ -6. for $iy$ from $ix$ to $sn - 1$ do \\ -\hspace{3mm}6.1 Let $y$ denote the position in the map of $str_{iy}$. \\ -\hspace{3mm}6.2 If $str_{iy}$ is not in the map or $y \ge r$ then goto step 7. \\ -\hspace{3mm}6.3 $a \leftarrow a \cdot r$ \\ -\hspace{3mm}6.4 $a \leftarrow a + y$ \\ -7. If $a \ne 0$ then $a.sign \leftarrow sign$ \\ -8. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_read\_radix} -\end{figure} -\textbf{Algorithm mp\_read\_radix.} -This algorithm will read an ASCII string and produce the radix-$\beta$ mp\_int representation of the same integer. A minus symbol ``-'' may precede the -string to indicate the value is negative, otherwise it is assumed to be positive. The algorithm will read up to $sn$ characters from the input -and will stop when it reads a character it cannot map the algorithm stops reading characters from the string. This allows numbers to be embedded -as part of larger input without any significant problem. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_read\_radix.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* read a string [ASCII] in a given radix */ -018 int mp_read_radix (mp_int * a, const char *str, int radix) -019 \{ -020 int y, res, neg; -021 char ch; -022 -023 /* zero the digit bignum */ -024 mp_zero(a); -025 -026 /* make sure the radix is ok */ -027 if ((radix < 2) || (radix > 64)) \{ -028 return MP_VAL; -029 \} -030 -031 /* if the leading digit is a -032 * minus set the sign to negative. -033 */ -034 if (*str == '-') \{ -035 ++str; -036 neg = MP_NEG; -037 \} else \{ -038 neg = MP_ZPOS; -039 \} -040 -041 /* set the integer to the default of zero */ -042 mp_zero (a); -043 -044 /* process each digit of the string */ -045 while (*str != '\symbol{92}0') \{ -046 /* if the radix <= 36 the conversion is case insensitive -047 * this allows numbers like 1AB and 1ab to represent the same value -048 * [e.g. in hex] -049 */ -050 ch = (radix <= 36) ? (char)toupper((int)*str) : *str; -051 for (y = 0; y < 64; y++) \{ -052 if (ch == mp_s_rmap[y]) \{ -053 break; -054 \} -055 \} -056 -057 /* if the char was found in the map -058 * and is less than the given radix add it -059 * to the number, otherwise exit the loop. -060 */ -061 if (y < radix) \{ -062 if ((res = mp_mul_d (a, (mp_digit) radix, a)) != MP_OKAY) \{ -063 return res; -064 \} -065 if ((res = mp_add_d (a, (mp_digit) y, a)) != MP_OKAY) \{ -066 return res; -067 \} -068 \} else \{ -069 break; -070 \} -071 ++str; -072 \} -073 -074 /* set the sign only if a != 0 */ -075 if (mp_iszero(a) != MP_YES) \{ -076 a->sign = neg; -077 \} -078 return MP_OKAY; -079 \} -080 #endif -081 -\end{alltt} -\end{small} - -\subsection{Generating Radix-$n$ Output} -Generating radix-$n$ output is fairly trivial with a division and remainder algorithm. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_toradix}. \\ -\textbf{Input}. A mp\_int $a$ and an integer $r$\\ -\textbf{Output}. The radix-$r$ representation of $a$ \\ -\hline \\ -1. If $r < 2$ or $r > 64$ return(\textit{MP\_VAL}). \\ -2. If $a = 0$ then $str = $ ``$0$'' and return(\textit{MP\_OKAY}). \\ -3. $t \leftarrow a$ \\ -4. $str \leftarrow$ ``'' \\ -5. if $t.sign = MP\_NEG$ then \\ -\hspace{3mm}5.1 $str \leftarrow str + $ ``-'' \\ -\hspace{3mm}5.2 $t.sign = MP\_ZPOS$ \\ -6. While ($t \ne 0$) do \\ -\hspace{3mm}6.1 $d \leftarrow t \mbox{ (mod }r\mbox{)}$ \\ -\hspace{3mm}6.2 $t \leftarrow \lfloor t / r \rfloor$ \\ -\hspace{3mm}6.3 Look up $d$ in the map and store the equivalent character in $y$. \\ -\hspace{3mm}6.4 $str \leftarrow str + y$ \\ -7. If $str_0 = $``$-$'' then \\ -\hspace{3mm}7.1 Reverse the digits $str_1, str_2, \ldots str_n$. \\ -8. Otherwise \\ -\hspace{3mm}8.1 Reverse the digits $str_0, str_1, \ldots str_n$. \\ -9. Return(\textit{MP\_OKAY}).\\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_toradix} -\end{figure} -\textbf{Algorithm mp\_toradix.} -This algorithm computes the radix-$r$ representation of an mp\_int $a$. The ``digits'' of the representation are extracted by reducing -successive powers of $\lfloor a / r^k \rfloor$ the input modulo $r$ until $r^k > a$. Note that instead of actually dividing by $r^k$ in -each iteration the quotient $\lfloor a / r \rfloor$ is saved for the next iteration. As a result a series of trivial $n \times 1$ divisions -are required instead of a series of $n \times k$ divisions. One design flaw of this approach is that the digits are produced in the reverse order -(see~\ref{fig:mpradix}). To remedy this flaw the digits must be swapped or simply ``reversed''. - -\begin{figure} -\begin{center} -\begin{tabular}{|c|c|c|} -\hline \textbf{Value of $a$} & \textbf{Value of $d$} & \textbf{Value of $str$} \\ -\hline $1234$ & -- & -- \\ -\hline $123$ & $4$ & ``4'' \\ -\hline $12$ & $3$ & ``43'' \\ -\hline $1$ & $2$ & ``432'' \\ -\hline $0$ & $1$ & ``4321'' \\ -\hline -\end{tabular} -\end{center} -\caption{Example of Algorithm mp\_toradix.} -\label{fig:mpradix} -\end{figure} - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_toradix.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* stores a bignum as a ASCII string in a given radix (2..64) */ -018 int mp_toradix (mp_int * a, char *str, int radix) -019 \{ -020 int res, digs; -021 mp_int t; -022 mp_digit d; -023 char *_s = str; -024 -025 /* check range of the radix */ -026 if ((radix < 2) || (radix > 64)) \{ -027 return MP_VAL; -028 \} -029 -030 /* quick out if its zero */ -031 if (mp_iszero(a) == MP_YES) \{ -032 *str++ = '0'; -033 *str = '\symbol{92}0'; -034 return MP_OKAY; -035 \} -036 -037 if ((res = mp_init_copy (&t, a)) != MP_OKAY) \{ -038 return res; -039 \} -040 -041 /* if it is negative output a - */ -042 if (t.sign == MP_NEG) \{ -043 ++_s; -044 *str++ = '-'; -045 t.sign = MP_ZPOS; -046 \} -047 -048 digs = 0; -049 while (mp_iszero (&t) == MP_NO) \{ -050 if ((res = mp_div_d (&t, (mp_digit) radix, &t, &d)) != MP_OKAY) \{ -051 mp_clear (&t); -052 return res; -053 \} -054 *str++ = mp_s_rmap[d]; -055 ++digs; -056 \} -057 -058 /* reverse the digits of the string. In this case _s points -059 * to the first digit [exluding the sign] of the number] -060 */ -061 bn_reverse ((unsigned char *)_s, digs); -062 -063 /* append a NULL so the string is properly terminated */ -064 *str = '\symbol{92}0'; -065 -066 mp_clear (&t); -067 return MP_OKAY; -068 \} -069 -070 #endif -071 -\end{alltt} -\end{small} - -\chapter{Number Theoretic Algorithms} -This chapter discusses several fundamental number theoretic algorithms such as the greatest common divisor, least common multiple and Jacobi -symbol computation. These algorithms arise as essential components in several key cryptographic algorithms such as the RSA public key algorithm and -various Sieve based factoring algorithms. - -\section{Greatest Common Divisor} -The greatest common divisor of two integers $a$ and $b$, often denoted as $(a, b)$ is the largest integer $k$ that is a proper divisor of -both $a$ and $b$. That is, $k$ is the largest integer such that $0 \equiv a \mbox{ (mod }k\mbox{)}$ and $0 \equiv b \mbox{ (mod }k\mbox{)}$ occur -simultaneously. - -The most common approach (cite) is to reduce one input modulo another. That is if $a$ and $b$ are divisible by some integer $k$ and if $qa + r = b$ then -$r$ is also divisible by $k$. The reduction pattern follows $\left < a , b \right > \rightarrow \left < b, a \mbox{ mod } b \right >$. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{Greatest Common Divisor (I)}. \\ -\textbf{Input}. Two positive integers $a$ and $b$ greater than zero. \\ -\textbf{Output}. The greatest common divisor $(a, b)$. \\ -\hline \\ -1. While ($b > 0$) do \\ -\hspace{3mm}1.1 $r \leftarrow a \mbox{ (mod }b\mbox{)}$ \\ -\hspace{3mm}1.2 $a \leftarrow b$ \\ -\hspace{3mm}1.3 $b \leftarrow r$ \\ -2. Return($a$). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm Greatest Common Divisor (I)} -\label{fig:gcd1} -\end{figure} - -This algorithm will quickly converge on the greatest common divisor since the residue $r$ tends diminish rapidly. However, divisions are -relatively expensive operations to perform and should ideally be avoided. There is another approach based on a similar relationship of -greatest common divisors. The faster approach is based on the observation that if $k$ divides both $a$ and $b$ it will also divide $a - b$. -In particular, we would like $a - b$ to decrease in magnitude which implies that $b \ge a$. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{Greatest Common Divisor (II)}. \\ -\textbf{Input}. Two positive integers $a$ and $b$ greater than zero. \\ -\textbf{Output}. The greatest common divisor $(a, b)$. \\ -\hline \\ -1. While ($b > 0$) do \\ -\hspace{3mm}1.1 Swap $a$ and $b$ such that $a$ is the smallest of the two. \\ -\hspace{3mm}1.2 $b \leftarrow b - a$ \\ -2. Return($a$). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm Greatest Common Divisor (II)} -\label{fig:gcd2} -\end{figure} - -\textbf{Proof} \textit{Algorithm~\ref{fig:gcd2} will return the greatest common divisor of $a$ and $b$.} -The algorithm in figure~\ref{fig:gcd2} will eventually terminate since $b \ge a$ the subtraction in step 1.2 will be a value less than $b$. In other -words in every iteration that tuple $\left < a, b \right >$ decrease in magnitude until eventually $a = b$. Since both $a$ and $b$ are always -divisible by the greatest common divisor (\textit{until the last iteration}) and in the last iteration of the algorithm $b = 0$, therefore, in the -second to last iteration of the algorithm $b = a$ and clearly $(a, a) = a$ which concludes the proof. \textbf{QED}. - -As a matter of practicality algorithm \ref{fig:gcd1} decreases far too slowly to be useful. Specially if $b$ is much larger than $a$ such that -$b - a$ is still very much larger than $a$. A simple addition to the algorithm is to divide $b - a$ by a power of some integer $p$ which does -not divide the greatest common divisor but will divide $b - a$. In this case ${b - a} \over p$ is also an integer and still divisible by -the greatest common divisor. - -However, instead of factoring $b - a$ to find a suitable value of $p$ the powers of $p$ can be removed from $a$ and $b$ that are in common first. -Then inside the loop whenever $b - a$ is divisible by some power of $p$ it can be safely removed. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{Greatest Common Divisor (III)}. \\ -\textbf{Input}. Two positive integers $a$ and $b$ greater than zero. \\ -\textbf{Output}. The greatest common divisor $(a, b)$. \\ -\hline \\ -1. $k \leftarrow 0$ \\ -2. While $a$ and $b$ are both divisible by $p$ do \\ -\hspace{3mm}2.1 $a \leftarrow \lfloor a / p \rfloor$ \\ -\hspace{3mm}2.2 $b \leftarrow \lfloor b / p \rfloor$ \\ -\hspace{3mm}2.3 $k \leftarrow k + 1$ \\ -3. While $a$ is divisible by $p$ do \\ -\hspace{3mm}3.1 $a \leftarrow \lfloor a / p \rfloor$ \\ -4. While $b$ is divisible by $p$ do \\ -\hspace{3mm}4.1 $b \leftarrow \lfloor b / p \rfloor$ \\ -5. While ($b > 0$) do \\ -\hspace{3mm}5.1 Swap $a$ and $b$ such that $a$ is the smallest of the two. \\ -\hspace{3mm}5.2 $b \leftarrow b - a$ \\ -\hspace{3mm}5.3 While $b$ is divisible by $p$ do \\ -\hspace{6mm}5.3.1 $b \leftarrow \lfloor b / p \rfloor$ \\ -6. Return($a \cdot p^k$). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm Greatest Common Divisor (III)} -\label{fig:gcd3} -\end{figure} - -This algorithm is based on the first except it removes powers of $p$ first and inside the main loop to ensure the tuple $\left < a, b \right >$ -decreases more rapidly. The first loop on step two removes powers of $p$ that are in common. A count, $k$, is kept which will present a common -divisor of $p^k$. After step two the remaining common divisor of $a$ and $b$ cannot be divisible by $p$. This means that $p$ can be safely -divided out of the difference $b - a$ so long as the division leaves no remainder. - -In particular the value of $p$ should be chosen such that the division on step 5.3.1 occur often. It also helps that division by $p$ be easy -to compute. The ideal choice of $p$ is two since division by two amounts to a right logical shift. Another important observation is that by -step five both $a$ and $b$ are odd. Therefore, the diffrence $b - a$ must be even which means that each iteration removes one bit from the -largest of the pair. - -\subsection{Complete Greatest Common Divisor} -The algorithms presented so far cannot handle inputs which are zero or negative. The following algorithm can handle all input cases properly -and will produce the greatest common divisor. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_gcd}. \\ -\textbf{Input}. mp\_int $a$ and $b$ \\ -\textbf{Output}. The greatest common divisor $c = (a, b)$. \\ -\hline \\ -1. If $a = 0$ then \\ -\hspace{3mm}1.1 $c \leftarrow \vert b \vert $ \\ -\hspace{3mm}1.2 Return(\textit{MP\_OKAY}). \\ -2. If $b = 0$ then \\ -\hspace{3mm}2.1 $c \leftarrow \vert a \vert $ \\ -\hspace{3mm}2.2 Return(\textit{MP\_OKAY}). \\ -3. $u \leftarrow \vert a \vert, v \leftarrow \vert b \vert$ \\ -4. $k \leftarrow 0$ \\ -5. While $u.used > 0$ and $v.used > 0$ and $u_0 \equiv v_0 \equiv 0 \mbox{ (mod }2\mbox{)}$ \\ -\hspace{3mm}5.1 $k \leftarrow k + 1$ \\ -\hspace{3mm}5.2 $u \leftarrow \lfloor u / 2 \rfloor$ \\ -\hspace{3mm}5.3 $v \leftarrow \lfloor v / 2 \rfloor$ \\ -6. While $u.used > 0$ and $u_0 \equiv 0 \mbox{ (mod }2\mbox{)}$ \\ -\hspace{3mm}6.1 $u \leftarrow \lfloor u / 2 \rfloor$ \\ -7. While $v.used > 0$ and $v_0 \equiv 0 \mbox{ (mod }2\mbox{)}$ \\ -\hspace{3mm}7.1 $v \leftarrow \lfloor v / 2 \rfloor$ \\ -8. While $v.used > 0$ \\ -\hspace{3mm}8.1 If $\vert u \vert > \vert v \vert$ then \\ -\hspace{6mm}8.1.1 Swap $u$ and $v$. \\ -\hspace{3mm}8.2 $v \leftarrow \vert v \vert - \vert u \vert$ \\ -\hspace{3mm}8.3 While $v.used > 0$ and $v_0 \equiv 0 \mbox{ (mod }2\mbox{)}$ \\ -\hspace{6mm}8.3.1 $v \leftarrow \lfloor v / 2 \rfloor$ \\ -9. $c \leftarrow u \cdot 2^k$ \\ -10. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_gcd} -\end{figure} -\textbf{Algorithm mp\_gcd.} -This algorithm will produce the greatest common divisor of two mp\_ints $a$ and $b$. The algorithm was originally based on Algorithm B of -Knuth \cite[pp. 338]{TAOCPV2} but has been modified to be simpler to explain. In theory it achieves the same asymptotic working time as -Algorithm B and in practice this appears to be true. - -The first two steps handle the cases where either one of or both inputs are zero. If either input is zero the greatest common divisor is the -largest input or zero if they are both zero. If the inputs are not trivial than $u$ and $v$ are assigned the absolute values of -$a$ and $b$ respectively and the algorithm will proceed to reduce the pair. - -Step five will divide out any common factors of two and keep track of the count in the variable $k$. After this step, two is no longer a -factor of the remaining greatest common divisor between $u$ and $v$ and can be safely evenly divided out of either whenever they are even. Step -six and seven ensure that the $u$ and $v$ respectively have no more factors of two. At most only one of the while--loops will iterate since -they cannot both be even. - -By step eight both of $u$ and $v$ are odd which is required for the inner logic. First the pair are swapped such that $v$ is equal to -or greater than $u$. This ensures that the subtraction on step 8.2 will always produce a positive and even result. Step 8.3 removes any -factors of two from the difference $u$ to ensure that in the next iteration of the loop both are once again odd. - -After $v = 0$ occurs the variable $u$ has the greatest common divisor of the pair $\left < u, v \right >$ just after step six. The result -must be adjusted by multiplying by the common factors of two ($2^k$) removed earlier. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_gcd.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* Greatest Common Divisor using the binary method */ -018 int mp_gcd (mp_int * a, mp_int * b, mp_int * c) -019 \{ -020 mp_int u, v; -021 int k, u_lsb, v_lsb, res; -022 -023 /* either zero than gcd is the largest */ -024 if (mp_iszero (a) == MP_YES) \{ -025 return mp_abs (b, c); -026 \} -027 if (mp_iszero (b) == MP_YES) \{ -028 return mp_abs (a, c); -029 \} -030 -031 /* get copies of a and b we can modify */ -032 if ((res = mp_init_copy (&u, a)) != MP_OKAY) \{ -033 return res; -034 \} -035 -036 if ((res = mp_init_copy (&v, b)) != MP_OKAY) \{ -037 goto LBL_U; -038 \} -039 -040 /* must be positive for the remainder of the algorithm */ -041 u.sign = v.sign = MP_ZPOS; -042 -043 /* B1. Find the common power of two for u and v */ -044 u_lsb = mp_cnt_lsb(&u); -045 v_lsb = mp_cnt_lsb(&v); -046 k = MIN(u_lsb, v_lsb); -047 -048 if (k > 0) \{ -049 /* divide the power of two out */ -050 if ((res = mp_div_2d(&u, k, &u, NULL)) != MP_OKAY) \{ -051 goto LBL_V; -052 \} -053 -054 if ((res = mp_div_2d(&v, k, &v, NULL)) != MP_OKAY) \{ -055 goto LBL_V; -056 \} -057 \} -058 -059 /* divide any remaining factors of two out */ -060 if (u_lsb != k) \{ -061 if ((res = mp_div_2d(&u, u_lsb - k, &u, NULL)) != MP_OKAY) \{ -062 goto LBL_V; -063 \} -064 \} -065 -066 if (v_lsb != k) \{ -067 if ((res = mp_div_2d(&v, v_lsb - k, &v, NULL)) != MP_OKAY) \{ -068 goto LBL_V; -069 \} -070 \} -071 -072 while (mp_iszero(&v) == MP_NO) \{ -073 /* make sure v is the largest */ -074 if (mp_cmp_mag(&u, &v) == MP_GT) \{ -075 /* swap u and v to make sure v is >= u */ -076 mp_exch(&u, &v); -077 \} -078 -079 /* subtract smallest from largest */ -080 if ((res = s_mp_sub(&v, &u, &v)) != MP_OKAY) \{ -081 goto LBL_V; -082 \} -083 -084 /* Divide out all factors of two */ -085 if ((res = mp_div_2d(&v, mp_cnt_lsb(&v), &v, NULL)) != MP_OKAY) \{ -086 goto LBL_V; -087 \} -088 \} -089 -090 /* multiply by 2**k which we divided out at the beginning */ -091 if ((res = mp_mul_2d (&u, k, c)) != MP_OKAY) \{ -092 goto LBL_V; -093 \} -094 c->sign = MP_ZPOS; -095 res = MP_OKAY; -096 LBL_V:mp_clear (&u); -097 LBL_U:mp_clear (&v); -098 return res; -099 \} -100 #endif -101 -\end{alltt} -\end{small} - -This function makes use of the macros mp\_iszero and mp\_iseven. The former evaluates to $1$ if the input mp\_int is equivalent to the -integer zero otherwise it evaluates to $0$. The latter evaluates to $1$ if the input mp\_int represents a non-zero even integer otherwise -it evaluates to $0$. Note that just because mp\_iseven may evaluate to $0$ does not mean the input is odd, it could also be zero. The three -trivial cases of inputs are handled on lines 23 through 29. After those lines the inputs are assumed to be non-zero. - -Lines 32 and 36 make local copies $u$ and $v$ of the inputs $a$ and $b$ respectively. At this point the common factors of two -must be divided out of the two inputs. The block starting at line 43 removes common factors of two by first counting the number of trailing -zero bits in both. The local integer $k$ is used to keep track of how many factors of $2$ are pulled out of both values. It is assumed that -the number of factors will not exceed the maximum value of a C ``int'' data type\footnote{Strictly speaking no array in C may have more than -entries than are accessible by an ``int'' so this is not a limitation.}. - -At this point there are no more common factors of two in the two values. The divisions by a power of two on lines 61 and 67 remove -any independent factors of two such that both $u$ and $v$ are guaranteed to be an odd integer before hitting the main body of the algorithm. The while loop -on line 72 performs the reduction of the pair until $v$ is equal to zero. The unsigned comparison and subtraction algorithms are used in -place of the full signed routines since both values are guaranteed to be positive and the result of the subtraction is guaranteed to be non-negative. - -\section{Least Common Multiple} -The least common multiple of a pair of integers is their product divided by their greatest common divisor. For two integers $a$ and $b$ the -least common multiple is normally denoted as $[ a, b ]$ and numerically equivalent to ${ab} \over {(a, b)}$. For example, if $a = 2 \cdot 2 \cdot 3 = 12$ -and $b = 2 \cdot 3 \cdot 3 \cdot 7 = 126$ the least common multiple is ${126 \over {(12, 126)}} = {126 \over 6} = 21$. - -The least common multiple arises often in coding theory as well as number theory. If two functions have periods of $a$ and $b$ respectively they will -collide, that is be in synchronous states, after only $[ a, b ]$ iterations. This is why, for example, random number generators based on -Linear Feedback Shift Registers (LFSR) tend to use registers with periods which are co-prime (\textit{e.g. the greatest common divisor is one.}). -Similarly in number theory if a composite $n$ has two prime factors $p$ and $q$ then maximal order of any unit of $\Z/n\Z$ will be $[ p - 1, q - 1] $. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_lcm}. \\ -\textbf{Input}. mp\_int $a$ and $b$ \\ -\textbf{Output}. The least common multiple $c = [a, b]$. \\ -\hline \\ -1. $c \leftarrow (a, b)$ \\ -2. $t \leftarrow a \cdot b$ \\ -3. $c \leftarrow \lfloor t / c \rfloor$ \\ -4. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_lcm} -\end{figure} -\textbf{Algorithm mp\_lcm.} -This algorithm computes the least common multiple of two mp\_int inputs $a$ and $b$. It computes the least common multiple directly by -dividing the product of the two inputs by their greatest common divisor. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_lcm.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* computes least common multiple as |a*b|/(a, b) */ -018 int mp_lcm (mp_int * a, mp_int * b, mp_int * c) -019 \{ -020 int res; -021 mp_int t1, t2; -022 -023 -024 if ((res = mp_init_multi (&t1, &t2, NULL)) != MP_OKAY) \{ -025 return res; -026 \} -027 -028 /* t1 = get the GCD of the two inputs */ -029 if ((res = mp_gcd (a, b, &t1)) != MP_OKAY) \{ -030 goto LBL_T; -031 \} -032 -033 /* divide the smallest by the GCD */ -034 if (mp_cmp_mag(a, b) == MP_LT) \{ -035 /* store quotient in t2 such that t2 * b is the LCM */ -036 if ((res = mp_div(a, &t1, &t2, NULL)) != MP_OKAY) \{ -037 goto LBL_T; -038 \} -039 res = mp_mul(b, &t2, c); -040 \} else \{ -041 /* store quotient in t2 such that t2 * a is the LCM */ -042 if ((res = mp_div(b, &t1, &t2, NULL)) != MP_OKAY) \{ -043 goto LBL_T; -044 \} -045 res = mp_mul(a, &t2, c); -046 \} -047 -048 /* fix the sign to positive */ -049 c->sign = MP_ZPOS; -050 -051 LBL_T: -052 mp_clear_multi (&t1, &t2, NULL); -053 return res; -054 \} -055 #endif -056 -\end{alltt} -\end{small} - -\section{Jacobi Symbol Computation} -To explain the Jacobi Symbol we shall first discuss the Legendre function\footnote{Arrg. What is the name of this?} off which the Jacobi symbol is -defined. The Legendre function computes whether or not an integer $a$ is a quadratic residue modulo an odd prime $p$. Numerically it is -equivalent to equation \ref{eqn:legendre}. - -\textit{-- Tom, don't be an ass, cite your source here...!} - -\begin{equation} -a^{(p-1)/2} \equiv \begin{array}{rl} - -1 & \mbox{if }a\mbox{ is a quadratic non-residue.} \\ - 0 & \mbox{if }a\mbox{ divides }p\mbox{.} \\ - 1 & \mbox{if }a\mbox{ is a quadratic residue}. - \end{array} \mbox{ (mod }p\mbox{)} -\label{eqn:legendre} -\end{equation} - -\textbf{Proof.} \textit{Equation \ref{eqn:legendre} correctly identifies the residue status of an integer $a$ modulo a prime $p$.} -An integer $a$ is a quadratic residue if the following equation has a solution. - -\begin{equation} -x^2 \equiv a \mbox{ (mod }p\mbox{)} -\label{eqn:root} -\end{equation} - -Consider the following equation. - -\begin{equation} -0 \equiv x^{p-1} - 1 \equiv \left \lbrace \left (x^2 \right )^{(p-1)/2} - a^{(p-1)/2} \right \rbrace + \left ( a^{(p-1)/2} - 1 \right ) \mbox{ (mod }p\mbox{)} -\label{eqn:rooti} -\end{equation} - -Whether equation \ref{eqn:root} has a solution or not equation \ref{eqn:rooti} is always true. If $a^{(p-1)/2} - 1 \equiv 0 \mbox{ (mod }p\mbox{)}$ -then the quantity in the braces must be zero. By reduction, - -\begin{eqnarray} -\left (x^2 \right )^{(p-1)/2} - a^{(p-1)/2} \equiv 0 \nonumber \\ -\left (x^2 \right )^{(p-1)/2} \equiv a^{(p-1)/2} \nonumber \\ -x^2 \equiv a \mbox{ (mod }p\mbox{)} -\end{eqnarray} - -As a result there must be a solution to the quadratic equation and in turn $a$ must be a quadratic residue. If $a$ does not divide $p$ and $a$ -is not a quadratic residue then the only other value $a^{(p-1)/2}$ may be congruent to is $-1$ since -\begin{equation} -0 \equiv a^{p - 1} - 1 \equiv (a^{(p-1)/2} + 1)(a^{(p-1)/2} - 1) \mbox{ (mod }p\mbox{)} -\end{equation} -One of the terms on the right hand side must be zero. \textbf{QED} - -\subsection{Jacobi Symbol} -The Jacobi symbol is a generalization of the Legendre function for any odd non prime moduli $p$ greater than 2. If $p = \prod_{i=0}^n p_i$ then -the Jacobi symbol $\left ( { a \over p } \right )$ is equal to the following equation. - -\begin{equation} -\left ( { a \over p } \right ) = \left ( { a \over p_0} \right ) \left ( { a \over p_1} \right ) \ldots \left ( { a \over p_n} \right ) -\end{equation} - -By inspection if $p$ is prime the Jacobi symbol is equivalent to the Legendre function. The following facts\footnote{See HAC \cite[pp. 72-74]{HAC} for -further details.} will be used to derive an efficient Jacobi symbol algorithm. Where $p$ is an odd integer greater than two and $a, b \in \Z$ the -following are true. - -\begin{enumerate} -\item $\left ( { a \over p} \right )$ equals $-1$, $0$ or $1$. -\item $\left ( { ab \over p} \right ) = \left ( { a \over p} \right )\left ( { b \over p} \right )$. -\item If $a \equiv b$ then $\left ( { a \over p} \right ) = \left ( { b \over p} \right )$. -\item $\left ( { 2 \over p} \right )$ equals $1$ if $p \equiv 1$ or $7 \mbox{ (mod }8\mbox{)}$. Otherwise, it equals $-1$. -\item $\left ( { a \over p} \right ) \equiv \left ( { p \over a} \right ) \cdot (-1)^{(p-1)(a-1)/4}$. More specifically -$\left ( { a \over p} \right ) = \left ( { p \over a} \right )$ if $p \equiv a \equiv 1 \mbox{ (mod }4\mbox{)}$. -\end{enumerate} - -Using these facts if $a = 2^k \cdot a'$ then - -\begin{eqnarray} -\left ( { a \over p } \right ) = \left ( {{2^k} \over p } \right ) \left ( {a' \over p} \right ) \nonumber \\ - = \left ( {2 \over p } \right )^k \left ( {a' \over p} \right ) -\label{eqn:jacobi} -\end{eqnarray} - -By fact five, - -\begin{equation} -\left ( { a \over p } \right ) = \left ( { p \over a } \right ) \cdot (-1)^{(p-1)(a-1)/4} -\end{equation} - -Subsequently by fact three since $p \equiv (p \mbox{ mod }a) \mbox{ (mod }a\mbox{)}$ then - -\begin{equation} -\left ( { a \over p } \right ) = \left ( { {p \mbox{ mod } a} \over a } \right ) \cdot (-1)^{(p-1)(a-1)/4} -\end{equation} - -By putting both observations into equation \ref{eqn:jacobi} the following simplified equation is formed. - -\begin{equation} -\left ( { a \over p } \right ) = \left ( {2 \over p } \right )^k \left ( {{p\mbox{ mod }a'} \over a'} \right ) \cdot (-1)^{(p-1)(a'-1)/4} -\end{equation} - -The value of $\left ( {{p \mbox{ mod }a'} \over a'} \right )$ can be found by using the same equation recursively. The value of -$\left ( {2 \over p } \right )^k$ equals $1$ if $k$ is even otherwise it equals $\left ( {2 \over p } \right )$. Using this approach the -factors of $p$ do not have to be known. Furthermore, if $(a, p) = 1$ then the algorithm will terminate when the recursion requests the -Jacobi symbol computation of $\left ( {1 \over a'} \right )$ which is simply $1$. - -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_jacobi}. \\ -\textbf{Input}. mp\_int $a$ and $p$, $a \ge 0$, $p \ge 3$, $p \equiv 1 \mbox{ (mod }2\mbox{)}$ \\ -\textbf{Output}. The Jacobi symbol $c = \left ( {a \over p } \right )$. \\ -\hline \\ -1. If $a = 0$ then \\ -\hspace{3mm}1.1 $c \leftarrow 0$ \\ -\hspace{3mm}1.2 Return(\textit{MP\_OKAY}). \\ -2. If $a = 1$ then \\ -\hspace{3mm}2.1 $c \leftarrow 1$ \\ -\hspace{3mm}2.2 Return(\textit{MP\_OKAY}). \\ -3. $a' \leftarrow a$ \\ -4. $k \leftarrow 0$ \\ -5. While $a'.used > 0$ and $a'_0 \equiv 0 \mbox{ (mod }2\mbox{)}$ \\ -\hspace{3mm}5.1 $k \leftarrow k + 1$ \\ -\hspace{3mm}5.2 $a' \leftarrow \lfloor a' / 2 \rfloor$ \\ -6. If $k \equiv 0 \mbox{ (mod }2\mbox{)}$ then \\ -\hspace{3mm}6.1 $s \leftarrow 1$ \\ -7. else \\ -\hspace{3mm}7.1 $r \leftarrow p_0 \mbox{ (mod }8\mbox{)}$ \\ -\hspace{3mm}7.2 If $r = 1$ or $r = 7$ then \\ -\hspace{6mm}7.2.1 $s \leftarrow 1$ \\ -\hspace{3mm}7.3 else \\ -\hspace{6mm}7.3.1 $s \leftarrow -1$ \\ -8. If $p_0 \equiv a'_0 \equiv 3 \mbox{ (mod }4\mbox{)}$ then \\ -\hspace{3mm}8.1 $s \leftarrow -s$ \\ -9. If $a' \ne 1$ then \\ -\hspace{3mm}9.1 $p' \leftarrow p \mbox{ (mod }a'\mbox{)}$ \\ -\hspace{3mm}9.2 $s \leftarrow s \cdot \mbox{mp\_jacobi}(p', a')$ \\ -10. $c \leftarrow s$ \\ -11. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_jacobi} -\end{figure} -\textbf{Algorithm mp\_jacobi.} -This algorithm computes the Jacobi symbol for an arbitrary positive integer $a$ with respect to an odd integer $p$ greater than three. The algorithm -is based on algorithm 2.149 of HAC \cite[pp. 73]{HAC}. - -Step numbers one and two handle the trivial cases of $a = 0$ and $a = 1$ respectively. Step five determines the number of two factors in the -input $a$. If $k$ is even than the term $\left ( { 2 \over p } \right )^k$ must always evaluate to one. If $k$ is odd than the term evaluates to one -if $p_0$ is congruent to one or seven modulo eight, otherwise it evaluates to $-1$. After the the $\left ( { 2 \over p } \right )^k$ term is handled -the $(-1)^{(p-1)(a'-1)/4}$ is computed and multiplied against the current product $s$. The latter term evaluates to one if both $p$ and $a'$ -are congruent to one modulo four, otherwise it evaluates to negative one. - -By step nine if $a'$ does not equal one a recursion is required. Step 9.1 computes $p' \equiv p \mbox{ (mod }a'\mbox{)}$ and will recurse to compute -$\left ( {p' \over a'} \right )$ which is multiplied against the current Jacobi product. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_jacobi.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* computes the jacobi c = (a | n) (or Legendre if n is prime) -018 * HAC pp. 73 Algorithm 2.149 -019 * HAC is wrong here, as the special case of (0 | 1) is not -020 * handled correctly. -021 */ -022 int mp_jacobi (mp_int * a, mp_int * n, int *c) -023 \{ -024 mp_int a1, p1; -025 int k, s, r, res; -026 mp_digit residue; -027 -028 /* if a < 0 return MP_VAL */ -029 if (mp_isneg(a) == MP_YES) \{ -030 return MP_VAL; -031 \} -032 -033 /* if n <= 0 return MP_VAL */ -034 if (mp_cmp_d(n, 0) != MP_GT) \{ -035 return MP_VAL; -036 \} -037 -038 /* step 1. handle case of a == 0 */ -039 if (mp_iszero (a) == MP_YES) \{ -040 /* special case of a == 0 and n == 1 */ -041 if (mp_cmp_d (n, 1) == MP_EQ) \{ -042 *c = 1; -043 \} else \{ -044 *c = 0; -045 \} -046 return MP_OKAY; -047 \} -048 -049 /* step 2. if a == 1, return 1 */ -050 if (mp_cmp_d (a, 1) == MP_EQ) \{ -051 *c = 1; -052 return MP_OKAY; -053 \} -054 -055 /* default */ -056 s = 0; -057 -058 /* step 3. write a = a1 * 2**k */ -059 if ((res = mp_init_copy (&a1, a)) != MP_OKAY) \{ -060 return res; -061 \} -062 -063 if ((res = mp_init (&p1)) != MP_OKAY) \{ -064 goto LBL_A1; -065 \} -066 -067 /* divide out larger power of two */ -068 k = mp_cnt_lsb(&a1); -069 if ((res = mp_div_2d(&a1, k, &a1, NULL)) != MP_OKAY) \{ -070 goto LBL_P1; -071 \} -072 -073 /* step 4. if e is even set s=1 */ -074 if ((k & 1) == 0) \{ -075 s = 1; -076 \} else \{ -077 /* else set s=1 if p = 1/7 (mod 8) or s=-1 if p = 3/5 (mod 8) */ -078 residue = n->dp[0] & 7; -079 -080 if ((residue == 1) || (residue == 7)) \{ -081 s = 1; -082 \} else if ((residue == 3) || (residue == 5)) \{ -083 s = -1; -084 \} -085 \} -086 -087 /* step 5. if p == 3 (mod 4) *and* a1 == 3 (mod 4) then s = -s */ -088 if ( ((n->dp[0] & 3) == 3) && ((a1.dp[0] & 3) == 3)) \{ -089 s = -s; -090 \} -091 -092 /* if a1 == 1 we're done */ -093 if (mp_cmp_d (&a1, 1) == MP_EQ) \{ -094 *c = s; -095 \} else \{ -096 /* n1 = n mod a1 */ -097 if ((res = mp_mod (n, &a1, &p1)) != MP_OKAY) \{ -098 goto LBL_P1; -099 \} -100 if ((res = mp_jacobi (&p1, &a1, &r)) != MP_OKAY) \{ -101 goto LBL_P1; -102 \} -103 *c = s * r; -104 \} -105 -106 /* done */ -107 res = MP_OKAY; -108 LBL_P1:mp_clear (&p1); -109 LBL_A1:mp_clear (&a1); -110 return res; -111 \} -112 #endif -113 -\end{alltt} -\end{small} - -As a matter of practicality the variable $a'$ as per the pseudo-code is reprensented by the variable $a1$ since the $'$ symbol is not valid for a C -variable name character. - -The two simple cases of $a = 0$ and $a = 1$ are handled at the very beginning to simplify the algorithm. If the input is non-trivial the algorithm -has to proceed compute the Jacobi. The variable $s$ is used to hold the current Jacobi product. Note that $s$ is merely a C ``int'' data type since -the values it may obtain are merely $-1$, $0$ and $1$. - -After a local copy of $a$ is made all of the factors of two are divided out and the total stored in $k$. Technically only the least significant -bit of $k$ is required, however, it makes the algorithm simpler to follow to perform an addition. In practice an exclusive-or and addition have the same -processor requirements and neither is faster than the other. - -Line 59 through 71 determines the value of $\left ( { 2 \over p } \right )^k$. If the least significant bit of $k$ is zero than -$k$ is even and the value is one. Otherwise, the value of $s$ depends on which residue class $p$ belongs to modulo eight. The value of -$(-1)^{(p-1)(a'-1)/4}$ is compute and multiplied against $s$ on lines 73 through 76. - -Finally, if $a1$ does not equal one the algorithm must recurse and compute $\left ( {p' \over a'} \right )$. - -\textit{-- Comment about default $s$ and such...} - -\section{Modular Inverse} -\label{sec:modinv} -The modular inverse of a number actually refers to the modular multiplicative inverse. Essentially for any integer $a$ such that $(a, p) = 1$ there -exist another integer $b$ such that $ab \equiv 1 \mbox{ (mod }p\mbox{)}$. The integer $b$ is called the multiplicative inverse of $a$ which is -denoted as $b = a^{-1}$. Technically speaking modular inversion is a well defined operation for any finite ring or field not just for rings and -fields of integers. However, the former will be the matter of discussion. - -The simplest approach is to compute the algebraic inverse of the input. That is to compute $b \equiv a^{\Phi(p) - 1}$. If $\Phi(p)$ is the -order of the multiplicative subgroup modulo $p$ then $b$ must be the multiplicative inverse of $a$. The proof of which is trivial. - -\begin{equation} -ab \equiv a \left (a^{\Phi(p) - 1} \right ) \equiv a^{\Phi(p)} \equiv a^0 \equiv 1 \mbox{ (mod }p\mbox{)} -\end{equation} - -However, as simple as this approach may be it has two serious flaws. It requires that the value of $\Phi(p)$ be known which if $p$ is composite -requires all of the prime factors. This approach also is very slow as the size of $p$ grows. - -A simpler approach is based on the observation that solving for the multiplicative inverse is equivalent to solving the linear -Diophantine\footnote{See LeVeque \cite[pp. 40-43]{LeVeque} for more information.} equation. - -\begin{equation} -ab + pq = 1 -\end{equation} - -Where $a$, $b$, $p$ and $q$ are all integers. If such a pair of integers $ \left < b, q \right >$ exist than $b$ is the multiplicative inverse of -$a$ modulo $p$. The extended Euclidean algorithm (Knuth \cite[pp. 342]{TAOCPV2}) can be used to solve such equations provided $(a, p) = 1$. -However, instead of using that algorithm directly a variant known as the binary Extended Euclidean algorithm will be used in its place. The -binary approach is very similar to the binary greatest common divisor algorithm except it will produce a full solution to the Diophantine -equation. - -\subsection{General Case} -\newpage\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_invmod}. \\ -\textbf{Input}. mp\_int $a$ and $b$, $(a, b) = 1$, $p \ge 2$, $0 < a < p$. \\ -\textbf{Output}. The modular inverse $c \equiv a^{-1} \mbox{ (mod }b\mbox{)}$. \\ -\hline \\ -1. If $b \le 0$ then return(\textit{MP\_VAL}). \\ -2. If $b_0 \equiv 1 \mbox{ (mod }2\mbox{)}$ then use algorithm fast\_mp\_invmod. \\ -3. $x \leftarrow \vert a \vert, y \leftarrow b$ \\ -4. If $x_0 \equiv y_0 \equiv 0 \mbox{ (mod }2\mbox{)}$ then return(\textit{MP\_VAL}). \\ -5. $B \leftarrow 0, C \leftarrow 0, A \leftarrow 1, D \leftarrow 1$ \\ -6. While $u.used > 0$ and $u_0 \equiv 0 \mbox{ (mod }2\mbox{)}$ \\ -\hspace{3mm}6.1 $u \leftarrow \lfloor u / 2 \rfloor$ \\ -\hspace{3mm}6.2 If ($A.used > 0$ and $A_0 \equiv 1 \mbox{ (mod }2\mbox{)}$) or ($B.used > 0$ and $B_0 \equiv 1 \mbox{ (mod }2\mbox{)}$) then \\ -\hspace{6mm}6.2.1 $A \leftarrow A + y$ \\ -\hspace{6mm}6.2.2 $B \leftarrow B - x$ \\ -\hspace{3mm}6.3 $A \leftarrow \lfloor A / 2 \rfloor$ \\ -\hspace{3mm}6.4 $B \leftarrow \lfloor B / 2 \rfloor$ \\ -7. While $v.used > 0$ and $v_0 \equiv 0 \mbox{ (mod }2\mbox{)}$ \\ -\hspace{3mm}7.1 $v \leftarrow \lfloor v / 2 \rfloor$ \\ -\hspace{3mm}7.2 If ($C.used > 0$ and $C_0 \equiv 1 \mbox{ (mod }2\mbox{)}$) or ($D.used > 0$ and $D_0 \equiv 1 \mbox{ (mod }2\mbox{)}$) then \\ -\hspace{6mm}7.2.1 $C \leftarrow C + y$ \\ -\hspace{6mm}7.2.2 $D \leftarrow D - x$ \\ -\hspace{3mm}7.3 $C \leftarrow \lfloor C / 2 \rfloor$ \\ -\hspace{3mm}7.4 $D \leftarrow \lfloor D / 2 \rfloor$ \\ -8. If $u \ge v$ then \\ -\hspace{3mm}8.1 $u \leftarrow u - v$ \\ -\hspace{3mm}8.2 $A \leftarrow A - C$ \\ -\hspace{3mm}8.3 $B \leftarrow B - D$ \\ -9. else \\ -\hspace{3mm}9.1 $v \leftarrow v - u$ \\ -\hspace{3mm}9.2 $C \leftarrow C - A$ \\ -\hspace{3mm}9.3 $D \leftarrow D - B$ \\ -10. If $u \ne 0$ goto step 6. \\ -11. If $v \ne 1$ return(\textit{MP\_VAL}). \\ -12. While $C \le 0$ do \\ -\hspace{3mm}12.1 $C \leftarrow C + b$ \\ -13. While $C \ge b$ do \\ -\hspace{3mm}13.1 $C \leftarrow C - b$ \\ -14. $c \leftarrow C$ \\ -15. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\end{figure} -\textbf{Algorithm mp\_invmod.} -This algorithm computes the modular multiplicative inverse of an integer $a$ modulo an integer $b$. This algorithm is a variation of the -extended binary Euclidean algorithm from HAC \cite[pp. 608]{HAC}. It has been modified to only compute the modular inverse and not a complete -Diophantine solution. - -If $b \le 0$ than the modulus is invalid and MP\_VAL is returned. Similarly if both $a$ and $b$ are even then there cannot be a multiplicative -inverse for $a$ and the error is reported. - -The astute reader will observe that steps seven through nine are very similar to the binary greatest common divisor algorithm mp\_gcd. In this case -the other variables to the Diophantine equation are solved. The algorithm terminates when $u = 0$ in which case the solution is - -\begin{equation} -Ca + Db = v -\end{equation} - -If $v$, the greatest common divisor of $a$ and $b$ is not equal to one then the algorithm will report an error as no inverse exists. Otherwise, $C$ -is the modular inverse of $a$. The actual value of $C$ is congruent to, but not necessarily equal to, the ideal modular inverse which should lie -within $1 \le a^{-1} < b$. Step numbers twelve and thirteen adjust the inverse until it is in range. If the original input $a$ is within $0 < a < p$ -then only a couple of additions or subtractions will be required to adjust the inverse. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_invmod.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* hac 14.61, pp608 */ -018 int mp_invmod (mp_int * a, mp_int * b, mp_int * c) -019 \{ -020 /* b cannot be negative */ -021 if ((b->sign == MP_NEG) || (mp_iszero(b) == MP_YES)) \{ -022 return MP_VAL; -023 \} -024 -025 #ifdef BN_FAST_MP_INVMOD_C -026 /* if the modulus is odd we can use a faster routine instead */ -027 if (mp_isodd (b) == MP_YES) \{ -028 return fast_mp_invmod (a, b, c); -029 \} -030 #endif -031 -032 #ifdef BN_MP_INVMOD_SLOW_C -033 return mp_invmod_slow(a, b, c); -034 #else -035 return MP_VAL; -036 #endif -037 \} -038 #endif -039 -\end{alltt} -\end{small} - -\subsubsection{Odd Moduli} - -When the modulus $b$ is odd the variables $A$ and $C$ are fixed and are not required to compute the inverse. In particular by attempting to solve -the Diophantine $Cb + Da = 1$ only $B$ and $D$ are required to find the inverse of $a$. - -The algorithm fast\_mp\_invmod is a direct adaptation of algorithm mp\_invmod with all all steps involving either $A$ or $C$ removed. This -optimization will halve the time required to compute the modular inverse. - -\section{Primality Tests} - -A non-zero integer $a$ is said to be prime if it is not divisible by any other integer excluding one and itself. For example, $a = 7$ is prime -since the integers $2 \ldots 6$ do not evenly divide $a$. By contrast, $a = 6$ is not prime since $a = 6 = 2 \cdot 3$. - -Prime numbers arise in cryptography considerably as they allow finite fields to be formed. The ability to determine whether an integer is prime or -not quickly has been a viable subject in cryptography and number theory for considerable time. The algorithms that will be presented are all -probablistic algorithms in that when they report an integer is composite it must be composite. However, when the algorithms report an integer is -prime the algorithm may be incorrect. - -As will be discussed it is possible to limit the probability of error so well that for practical purposes the probablity of error might as -well be zero. For the purposes of these discussions let $n$ represent the candidate integer of which the primality is in question. - -\subsection{Trial Division} - -Trial division means to attempt to evenly divide a candidate integer by small prime integers. If the candidate can be evenly divided it obviously -cannot be prime. By dividing by all primes $1 < p \le \sqrt{n}$ this test can actually prove whether an integer is prime. However, such a test -would require a prohibitive amount of time as $n$ grows. - -Instead of dividing by every prime, a smaller, more mangeable set of primes may be used instead. By performing trial division with only a subset -of the primes less than $\sqrt{n} + 1$ the algorithm cannot prove if a candidate is prime. However, often it can prove a candidate is not prime. - -The benefit of this test is that trial division by small values is fairly efficient. Specially compared to the other algorithms that will be -discussed shortly. The probability that this approach correctly identifies a composite candidate when tested with all primes upto $q$ is given by -$1 - {1.12 \over ln(q)}$. The graph (\ref{pic:primality}, will be added later) demonstrates the probability of success for the range -$3 \le q \le 100$. - -At approximately $q = 30$ the gain of performing further tests diminishes fairly quickly. At $q = 90$ further testing is generally not going to -be of any practical use. In the case of LibTomMath the default limit $q = 256$ was chosen since it is not too high and will eliminate -approximately $80\%$ of all candidate integers. The constant \textbf{PRIME\_SIZE} is equal to the number of primes in the test base. The -array \_\_prime\_tab is an array of the first \textbf{PRIME\_SIZE} prime numbers. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_prime\_is\_divisible}. \\ -\textbf{Input}. mp\_int $a$ \\ -\textbf{Output}. $c = 1$ if $n$ is divisible by a small prime, otherwise $c = 0$. \\ -\hline \\ -1. for $ix$ from $0$ to $PRIME\_SIZE$ do \\ -\hspace{3mm}1.1 $d \leftarrow n \mbox{ (mod }\_\_prime\_tab_{ix}\mbox{)}$ \\ -\hspace{3mm}1.2 If $d = 0$ then \\ -\hspace{6mm}1.2.1 $c \leftarrow 1$ \\ -\hspace{6mm}1.2.2 Return(\textit{MP\_OKAY}). \\ -2. $c \leftarrow 0$ \\ -3. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_prime\_is\_divisible} -\end{figure} -\textbf{Algorithm mp\_prime\_is\_divisible.} -This algorithm attempts to determine if a candidate integer $n$ is composite by performing trial divisions. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_prime\_is\_divisible.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* determines if an integers is divisible by one -018 * of the first PRIME_SIZE primes or not -019 * -020 * sets result to 0 if not, 1 if yes -021 */ -022 int mp_prime_is_divisible (mp_int * a, int *result) -023 \{ -024 int err, ix; -025 mp_digit res; -026 -027 /* default to not */ -028 *result = MP_NO; -029 -030 for (ix = 0; ix < PRIME_SIZE; ix++) \{ -031 /* what is a mod LBL_prime_tab[ix] */ -032 if ((err = mp_mod_d (a, ltm_prime_tab[ix], &res)) != MP_OKAY) \{ -033 return err; -034 \} -035 -036 /* is the residue zero? */ -037 if (res == 0) \{ -038 *result = MP_YES; -039 return MP_OKAY; -040 \} -041 \} -042 -043 return MP_OKAY; -044 \} -045 #endif -046 -\end{alltt} -\end{small} - -The algorithm defaults to a return of $0$ in case an error occurs. The values in the prime table are all specified to be in the range of a -mp\_digit. The table \_\_prime\_tab is defined in the following file. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_prime\_tab.c -\vspace{-3mm} -\begin{alltt} -016 const mp_digit ltm_prime_tab[] = \{ -017 0x0002, 0x0003, 0x0005, 0x0007, 0x000B, 0x000D, 0x0011, 0x0013, -018 0x0017, 0x001D, 0x001F, 0x0025, 0x0029, 0x002B, 0x002F, 0x0035, -019 0x003B, 0x003D, 0x0043, 0x0047, 0x0049, 0x004F, 0x0053, 0x0059, -020 0x0061, 0x0065, 0x0067, 0x006B, 0x006D, 0x0071, 0x007F, -021 #ifndef MP_8BIT -022 0x0083, -023 0x0089, 0x008B, 0x0095, 0x0097, 0x009D, 0x00A3, 0x00A7, 0x00AD, -024 0x00B3, 0x00B5, 0x00BF, 0x00C1, 0x00C5, 0x00C7, 0x00D3, 0x00DF, -025 0x00E3, 0x00E5, 0x00E9, 0x00EF, 0x00F1, 0x00FB, 0x0101, 0x0107, -026 0x010D, 0x010F, 0x0115, 0x0119, 0x011B, 0x0125, 0x0133, 0x0137, -027 -028 0x0139, 0x013D, 0x014B, 0x0151, 0x015B, 0x015D, 0x0161, 0x0167, -029 0x016F, 0x0175, 0x017B, 0x017F, 0x0185, 0x018D, 0x0191, 0x0199, -030 0x01A3, 0x01A5, 0x01AF, 0x01B1, 0x01B7, 0x01BB, 0x01C1, 0x01C9, -031 0x01CD, 0x01CF, 0x01D3, 0x01DF, 0x01E7, 0x01EB, 0x01F3, 0x01F7, -032 0x01FD, 0x0209, 0x020B, 0x021D, 0x0223, 0x022D, 0x0233, 0x0239, -033 0x023B, 0x0241, 0x024B, 0x0251, 0x0257, 0x0259, 0x025F, 0x0265, -034 0x0269, 0x026B, 0x0277, 0x0281, 0x0283, 0x0287, 0x028D, 0x0293, -035 0x0295, 0x02A1, 0x02A5, 0x02AB, 0x02B3, 0x02BD, 0x02C5, 0x02CF, -036 -037 0x02D7, 0x02DD, 0x02E3, 0x02E7, 0x02EF, 0x02F5, 0x02F9, 0x0301, -038 0x0305, 0x0313, 0x031D, 0x0329, 0x032B, 0x0335, 0x0337, 0x033B, -039 0x033D, 0x0347, 0x0355, 0x0359, 0x035B, 0x035F, 0x036D, 0x0371, -040 0x0373, 0x0377, 0x038B, 0x038F, 0x0397, 0x03A1, 0x03A9, 0x03AD, -041 0x03B3, 0x03B9, 0x03C7, 0x03CB, 0x03D1, 0x03D7, 0x03DF, 0x03E5, -042 0x03F1, 0x03F5, 0x03FB, 0x03FD, 0x0407, 0x0409, 0x040F, 0x0419, -043 0x041B, 0x0425, 0x0427, 0x042D, 0x043F, 0x0443, 0x0445, 0x0449, -044 0x044F, 0x0455, 0x045D, 0x0463, 0x0469, 0x047F, 0x0481, 0x048B, -045 -046 0x0493, 0x049D, 0x04A3, 0x04A9, 0x04B1, 0x04BD, 0x04C1, 0x04C7, -047 0x04CD, 0x04CF, 0x04D5, 0x04E1, 0x04EB, 0x04FD, 0x04FF, 0x0503, -048 0x0509, 0x050B, 0x0511, 0x0515, 0x0517, 0x051B, 0x0527, 0x0529, -049 0x052F, 0x0551, 0x0557, 0x055D, 0x0565, 0x0577, 0x0581, 0x058F, -050 0x0593, 0x0595, 0x0599, 0x059F, 0x05A7, 0x05AB, 0x05AD, 0x05B3, -051 0x05BF, 0x05C9, 0x05CB, 0x05CF, 0x05D1, 0x05D5, 0x05DB, 0x05E7, -052 0x05F3, 0x05FB, 0x0607, 0x060D, 0x0611, 0x0617, 0x061F, 0x0623, -053 0x062B, 0x062F, 0x063D, 0x0641, 0x0647, 0x0649, 0x064D, 0x0653 -054 #endif -055 \}; -056 #endif -057 -\end{alltt} -\end{small} - -Note that there are two possible tables. When an mp\_digit is 7-bits long only the primes upto $127$ may be included, otherwise the primes -upto $1619$ are used. Note that the value of \textbf{PRIME\_SIZE} is a constant dependent on the size of a mp\_digit. - -\subsection{The Fermat Test} -The Fermat test is probably one the oldest tests to have a non-trivial probability of success. It is based on the fact that if $n$ is in -fact prime then $a^{n} \equiv a \mbox{ (mod }n\mbox{)}$ for all $0 < a < n$. The reason being that if $n$ is prime than the order of -the multiplicative sub group is $n - 1$. Any base $a$ must have an order which divides $n - 1$ and as such $a^n$ is equivalent to -$a^1 = a$. - -If $n$ is composite then any given base $a$ does not have to have a period which divides $n - 1$. In which case -it is possible that $a^n \nequiv a \mbox{ (mod }n\mbox{)}$. However, this test is not absolute as it is possible that the order -of a base will divide $n - 1$ which would then be reported as prime. Such a base yields what is known as a Fermat pseudo-prime. Several -integers known as Carmichael numbers will be a pseudo-prime to all valid bases. Fortunately such numbers are extremely rare as $n$ grows -in size. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_prime\_fermat}. \\ -\textbf{Input}. mp\_int $a$ and $b$, $a \ge 2$, $0 < b < a$. \\ -\textbf{Output}. $c = 1$ if $b^a \equiv b \mbox{ (mod }a\mbox{)}$, otherwise $c = 0$. \\ -\hline \\ -1. $t \leftarrow b^a \mbox{ (mod }a\mbox{)}$ \\ -2. If $t = b$ then \\ -\hspace{3mm}2.1 $c = 1$ \\ -3. else \\ -\hspace{3mm}3.1 $c = 0$ \\ -4. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_prime\_fermat} -\end{figure} -\textbf{Algorithm mp\_prime\_fermat.} -This algorithm determines whether an mp\_int $a$ is a Fermat prime to the base $b$ or not. It uses a single modular exponentiation to -determine the result. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_prime\_fermat.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* performs one Fermat test. -018 * -019 * If "a" were prime then b**a == b (mod a) since the order of -020 * the multiplicative sub-group would be phi(a) = a-1. That means -021 * it would be the same as b**(a mod (a-1)) == b**1 == b (mod a). -022 * -023 * Sets result to 1 if the congruence holds, or zero otherwise. -024 */ -025 int mp_prime_fermat (mp_int * a, mp_int * b, int *result) -026 \{ -027 mp_int t; -028 int err; -029 -030 /* default to composite */ -031 *result = MP_NO; -032 -033 /* ensure b > 1 */ -034 if (mp_cmp_d(b, 1) != MP_GT) \{ -035 return MP_VAL; -036 \} -037 -038 /* init t */ -039 if ((err = mp_init (&t)) != MP_OKAY) \{ -040 return err; -041 \} -042 -043 /* compute t = b**a mod a */ -044 if ((err = mp_exptmod (b, a, a, &t)) != MP_OKAY) \{ -045 goto LBL_T; -046 \} -047 -048 /* is it equal to b? */ -049 if (mp_cmp (&t, b) == MP_EQ) \{ -050 *result = MP_YES; -051 \} -052 -053 err = MP_OKAY; -054 LBL_T:mp_clear (&t); -055 return err; -056 \} -057 #endif -058 -\end{alltt} -\end{small} - -\subsection{The Miller-Rabin Test} -The Miller-Rabin (citation) test is another primality test which has tighter error bounds than the Fermat test specifically with sequentially chosen -candidate integers. The algorithm is based on the observation that if $n - 1 = 2^kr$ and if $b^r \nequiv \pm 1$ then after upto $k - 1$ squarings the -value must be equal to $-1$. The squarings are stopped as soon as $-1$ is observed. If the value of $1$ is observed first it means that -some value not congruent to $\pm 1$ when squared equals one which cannot occur if $n$ is prime. - -\begin{figure}[!here] -\begin{small} -\begin{center} -\begin{tabular}{l} -\hline Algorithm \textbf{mp\_prime\_miller\_rabin}. \\ -\textbf{Input}. mp\_int $a$ and $b$, $a \ge 2$, $0 < b < a$. \\ -\textbf{Output}. $c = 1$ if $a$ is a Miller-Rabin prime to the base $a$, otherwise $c = 0$. \\ -\hline -1. $a' \leftarrow a - 1$ \\ -2. $r \leftarrow n1$ \\ -3. $c \leftarrow 0, s \leftarrow 0$ \\ -4. While $r.used > 0$ and $r_0 \equiv 0 \mbox{ (mod }2\mbox{)}$ \\ -\hspace{3mm}4.1 $s \leftarrow s + 1$ \\ -\hspace{3mm}4.2 $r \leftarrow \lfloor r / 2 \rfloor$ \\ -5. $y \leftarrow b^r \mbox{ (mod }a\mbox{)}$ \\ -6. If $y \nequiv \pm 1$ then \\ -\hspace{3mm}6.1 $j \leftarrow 1$ \\ -\hspace{3mm}6.2 While $j \le (s - 1)$ and $y \nequiv a'$ \\ -\hspace{6mm}6.2.1 $y \leftarrow y^2 \mbox{ (mod }a\mbox{)}$ \\ -\hspace{6mm}6.2.2 If $y = 1$ then goto step 8. \\ -\hspace{6mm}6.2.3 $j \leftarrow j + 1$ \\ -\hspace{3mm}6.3 If $y \nequiv a'$ goto step 8. \\ -7. $c \leftarrow 1$\\ -8. Return(\textit{MP\_OKAY}). \\ -\hline -\end{tabular} -\end{center} -\end{small} -\caption{Algorithm mp\_prime\_miller\_rabin} -\end{figure} -\textbf{Algorithm mp\_prime\_miller\_rabin.} -This algorithm performs one trial round of the Miller-Rabin algorithm to the base $b$. It will set $c = 1$ if the algorithm cannot determine -if $b$ is composite or $c = 0$ if $b$ is provably composite. The values of $s$ and $r$ are computed such that $a' = a - 1 = 2^sr$. - -If the value $y \equiv b^r$ is congruent to $\pm 1$ then the algorithm cannot prove if $a$ is composite or not. Otherwise, the algorithm will -square $y$ upto $s - 1$ times stopping only when $y \equiv -1$. If $y^2 \equiv 1$ and $y \nequiv \pm 1$ then the algorithm can report that $a$ -is provably composite. If the algorithm performs $s - 1$ squarings and $y \nequiv -1$ then $a$ is provably composite. If $a$ is not provably -composite then it is \textit{probably} prime. - -\vspace{+3mm}\begin{small} -\hspace{-5.1mm}{\bf File}: bn\_mp\_prime\_miller\_rabin.c -\vspace{-3mm} -\begin{alltt} -016 -017 /* Miller-Rabin test of "a" to the base of "b" as described in -018 * HAC pp. 139 Algorithm 4.24 -019 * -020 * Sets result to 0 if definitely composite or 1 if probably prime. -021 * Randomly the chance of error is no more than 1/4 and often -022 * very much lower. -023 */ -024 int mp_prime_miller_rabin (mp_int * a, mp_int * b, int *result) -025 \{ -026 mp_int n1, y, r; -027 int s, j, err; -028 -029 /* default */ -030 *result = MP_NO; -031 -032 /* ensure b > 1 */ -033 if (mp_cmp_d(b, 1) != MP_GT) \{ -034 return MP_VAL; -035 \} -036 -037 /* get n1 = a - 1 */ -038 if ((err = mp_init_copy (&n1, a)) != MP_OKAY) \{ -039 return err; -040 \} -041 if ((err = mp_sub_d (&n1, 1, &n1)) != MP_OKAY) \{ -042 goto LBL_N1; -043 \} -044 -045 /* set 2**s * r = n1 */ -046 if ((err = mp_init_copy (&r, &n1)) != MP_OKAY) \{ -047 goto LBL_N1; -048 \} -049 -050 /* count the number of least significant bits -051 * which are zero -052 */ -053 s = mp_cnt_lsb(&r); -054 -055 /* now divide n - 1 by 2**s */ -056 if ((err = mp_div_2d (&r, s, &r, NULL)) != MP_OKAY) \{ -057 goto LBL_R; -058 \} -059 -060 /* compute y = b**r mod a */ -061 if ((err = mp_init (&y)) != MP_OKAY) \{ -062 goto LBL_R; -063 \} -064 if ((err = mp_exptmod (b, &r, a, &y)) != MP_OKAY) \{ -065 goto LBL_Y; -066 \} -067 -068 /* if y != 1 and y != n1 do */ -069 if ((mp_cmp_d (&y, 1) != MP_EQ) && (mp_cmp (&y, &n1) != MP_EQ)) \{ -070 j = 1; -071 /* while j <= s-1 and y != n1 */ -072 while ((j <= (s - 1)) && (mp_cmp (&y, &n1) != MP_EQ)) \{ -073 if ((err = mp_sqrmod (&y, a, &y)) != MP_OKAY) \{ -074 goto LBL_Y; -075 \} -076 -077 /* if y == 1 then composite */ -078 if (mp_cmp_d (&y, 1) == MP_EQ) \{ -079 goto LBL_Y; -080 \} -081 -082 ++j; -083 \} -084 -085 /* if y != n1 then composite */ -086 if (mp_cmp (&y, &n1) != MP_EQ) \{ -087 goto LBL_Y; -088 \} -089 \} -090 -091 /* probably prime now */ -092 *result = MP_YES; -093 LBL_Y:mp_clear (&y); -094 LBL_R:mp_clear (&r); -095 LBL_N1:mp_clear (&n1); -096 return err; -097 \} -098 #endif -099 -\end{alltt} -\end{small} - - - - -\backmatter -\appendix -\begin{thebibliography}{ABCDEF} -\bibitem[1]{TAOCPV2} -Donald Knuth, \textit{The Art of Computer Programming}, Third Edition, Volume Two, Seminumerical Algorithms, Addison-Wesley, 1998 - -\bibitem[2]{HAC} -A. Menezes, P. van Oorschot, S. Vanstone, \textit{Handbook of Applied Cryptography}, CRC Press, 1996 - -\bibitem[3]{ROSE} -Michael Rosing, \textit{Implementing Elliptic Curve Cryptography}, Manning Publications, 1999 - -\bibitem[4]{COMBA} -Paul G. Comba, \textit{Exponentiation Cryptosystems on the IBM PC}. IBM Systems Journal 29(4): 526-538 (1990) - -\bibitem[5]{KARA} -A. Karatsuba, Doklay Akad. Nauk SSSR 145 (1962), pp.293-294 - -\bibitem[6]{KARAP} -Andre Weimerskirch and Christof Paar, \textit{Generalizations of the Karatsuba Algorithm for Polynomial Multiplication}, Submitted to Design, Codes and Cryptography, March 2002 - -\bibitem[7]{BARRETT} -Paul Barrett, \textit{Implementing the Rivest Shamir and Adleman Public Key Encryption Algorithm on a Standard Digital Signal Processor}, Advances in Cryptology, Crypto '86, Springer-Verlag. - -\bibitem[8]{MONT} -P.L.Montgomery. \textit{Modular multiplication without trial division}. Mathematics of Computation, 44(170):519-521, April 1985. - -\bibitem[9]{DRMET} -Chae Hoon Lim and Pil Joong Lee, \textit{Generating Efficient Primes for Discrete Log Cryptosystems}, POSTECH Information Research Laboratories - -\bibitem[10]{MMB} -J. Daemen and R. Govaerts and J. Vandewalle, \textit{Block ciphers based on Modular Arithmetic}, State and {P}rogress in the {R}esearch of {C}ryptography, 1993, pp. 80-89 - -\bibitem[11]{RSAREF} -R.L. Rivest, A. Shamir, L. Adleman, \textit{A Method for Obtaining Digital Signatures and Public-Key Cryptosystems} - -\bibitem[12]{DHREF} -Whitfield Diffie, Martin E. Hellman, \textit{New Directions in Cryptography}, IEEE Transactions on Information Theory, 1976 - -\bibitem[13]{IEEE} -IEEE Standard for Binary Floating-Point Arithmetic (ANSI/IEEE Std 754-1985) - -\bibitem[14]{GMP} -GNU Multiple Precision (GMP), \url{http://www.swox.com/gmp/} - -\bibitem[15]{MPI} -Multiple Precision Integer Library (MPI), Michael Fromberger, \url{http://thayer.dartmouth.edu/~sting/mpi/} - -\bibitem[16]{OPENSSL} -OpenSSL Cryptographic Toolkit, \url{http://openssl.org} - -\bibitem[17]{LIP} -Large Integer Package, \url{http://home.hetnet.nl/~ecstr/LIP.zip} - -\bibitem[18]{ISOC} -JTC1/SC22/WG14, ISO/IEC 9899:1999, ``A draft rationale for the C99 standard.'' - -\bibitem[19]{JAVA} -The Sun Java Website, \url{http://java.sun.com/} - -\end{thebibliography} - -\input{tommath.ind} - -\end{document} |
