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diff --git a/Doc/library/decimal.rst b/Doc/library/decimal.rst index f2a677e..bcae55e 100644 --- a/Doc/library/decimal.rst +++ b/Doc/library/decimal.rst @@ -2115,3 +2115,23 @@ Alternatively, inputs can be rounded upon creation using the >>> Context(prec=5, rounding=ROUND_DOWN).create_decimal('1.2345678') Decimal('1.2345') + +Q. Is the CPython implementation fast for large numbers? + +A. Yes. In the CPython and PyPy3 implementations, the C/CFFI versions of +the decimal module integrate the high speed `libmpdec +<https://www.bytereef.org/mpdecimal/doc/libmpdec/index.html>`_ library for +arbitrary precision correctly-rounded decimal floating point arithmetic. +``libmpdec`` uses `Karatsuba multiplication +<https://en.wikipedia.org/wiki/Karatsuba_algorithm>`_ +for medium-sized numbers and the `Number Theoretic Transform +<https://en.wikipedia.org/wiki/Discrete_Fourier_transform_(general)#Number-theoretic_transform>`_ +for very large numbers. However, to realize this performance gain, the +context needs to be set for unrounded calculations. + + >>> c = getcontext() + >>> c.prec = MAX_PREC + >>> c.Emax = MAX_EMAX + >>> c.Emin = MIN_EMIN + +.. versionadded:: 3.3
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