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diff --git a/doc/html/IOPipe.html b/doc/html/IOPipe.html new file mode 100644 index 0000000..7c24e2c --- /dev/null +++ b/doc/html/IOPipe.html @@ -0,0 +1,114 @@ +<!DOCTYPE HTML PUBLIC "-//IETF//DTD HTML//EN"> +<html> + <head> + <title>The Raw Data I/O Pipeline</title> + </head> + + <body> + <h1>The Raw Data I/O Pipeline</h1> + + <p>The HDF5 raw data pipeline is a complicated beast that handles + all aspects of raw data storage and transfer of that data + between the file and the application. Data can be stored + contiguously (internal or external), in variable size external + segments, or regularly chunked; it can be sparse, extendible, + and/or compressible. Data transfers must be able to convert from + one data space to another, convert from one number type to + another, and perform partial I/O operations. Furthermore, + applications will expect their common usage of the pipeline to + perform well. + + <p>To accomplish these goals, the pipeline has been designed in a + modular way so no single subroutine is overly complicated and so + functionality can be inserted easily at the appropriate + locations in the pipeline. A general pipeline was developed and + then certain paths through the pipeline were optimized for + performance. + + <p>We describe only the file-to-memory side of the pipeline since + the memory-to-file side is a mirror image. We also assume that a + proper hyperslab of a simple data space is being read from the + file into a proper hyperslab of a simple data space in memory, + and that the data type is a compound type which may require + various number conversions on its members. + + <img alt="Figure 1" src="pipe1.gif"> + + <p>The diagrams should be read from the top down. The Line A + in the figure above shows that <code>H5Dread()</code> copies + data from a hyperslab of a file dataset to a hyperslab of an + application buffer by calling <code>H5D_read()</code>. And + <code>H5D_read()</code> calls, in a loop, + <code>H5S_simp_fgath()</code>, <code>H5T_conv_struct()</code>, + and <code>H5S_simp_mscat()</code>. A temporary buffer, TCONV, is + loaded with data points from the file, then data type conversion + is performed on the temporary buffer, and finally data points + are scattered out to application memory. Thus, data type + conversion is an in-place operation and data space conversion + consists of two steps. An additional temporary buffer, BKG, is + large enough to hold <em>N</em> instances of the destination + data type where <em>N</em> is the same number of data points + that can be held by the TCONV buffer (which is large enough to + hold either source or destination data points). + + <p>The application sets an upper limit for the size of the TCONV + buffer and optionally supplies a buffer. If no buffer is + supplied then one will be created by calling + <code>malloc()</code> when the pipeline is executed (when + necessary) and freed when the pipeline exits. The size of the + BKG buffer depends on the size of the TCONV buffer and if the + application supplies a BKG buffer it should be at least as large + as the TCONV buffer. The default size for these buffers is one + megabyte but the buffer might not be used to full capacity if + the buffer size is not an integer multiple of the source or + destination data point size (whichever is larger, but only + destination for the BKG buffer). + + + + <p>Occassionally the destination data points will be partially + initialized and the <code>H5Dread()</code> operation should not + clobber those values. For instance, the destination type might + be a struct with members <code>a</code> and <code>b</code> where + <code>a</code> is already initialized and we're reading + <code>b</code> from the file. An extra line, G, is added to the + pipeline to provide the type conversion functions with the + existing data. + + <img alt="Figure 2" src="pipe2.gif"> + + <p>It will most likely be quite common that no data type + conversion is necessary. In such cases a temporary buffer for + data type conversion is not needed and data space conversion + can happen in a single step. In fact, when the source and + destination data are both contiguous (they aren't in the + picture) the loop degenerates to a single iteration. + + + <img alt="Figure 3" src="pipe3.gif"> + + <p>So far we've looked only at internal contiguous storage, but by + replacing Line B in Figures 1 and 2 and Line A in Figure 3 with + Figure 4 the pipeline is able to handle regularly chunked + objects. Line B of Figure 4 is executed once for each chunk + which contains data to be read and the chunk address is found by + looking at a multi-dimensional key in a chunk B-tree which has + one entry per chunk. + + <img alt="Figure 4" src="pipe4.gif"> + + <p>If a single chunk is requested and the destination buffer is + the same size/shape as the chunk, then the CHUNK buffer is + bypassed and the destination buffer is used instead as shown in + Figure 5. + + <img alt="Figure 5" src="pipe5.gif"> + + <hr> + <address><a href="mailto:matzke@llnl.gov">Robb Matzke</a></address> +<!-- Created: Tue Mar 17 11:13:35 EST 1998 --> +<!-- hhmts start --> +Last modified: Wed Mar 18 10:38:30 EST 1998 +<!-- hhmts end --> + </body> +</html> |