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authorQuincey Koziol <koziol@hdfgroup.org>2002-07-24 18:56:48 (GMT)
committerQuincey Koziol <koziol@hdfgroup.org>2002-07-24 18:56:48 (GMT)
commit40df66ebd027351e48eea8b7499490c9654d3943 (patch)
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[svn-r5834] Purpose:
Large code cleanup/re-write Description: This is phase 1 of the data I/O re-architecture, with the following changes: - Changed the selection drivers to not actually do any I/O, they only generate the sequences of offset/length pairs needed for the I/O (or memory access, in the case of iterating or filling a selection in a memory buffer) - Wrote more abstract I/O routines which get the sequence of offset/ length pairs for each selection and access perform the I/O or memory access. Benefits of this change include: - Removed ~3400 lines of quite redundant code, with corresponding reduction in the size of library binary. - Any selection can now directly access memory when performing I/O, if no type conversions are required, instead of just "regular" hyperslab and 'all' selections, which speeds up I/O. - Sped up I/O for hyperslab selections which have contiguous lower dimensions by "flattening" them out into lesser dimensional objects for the I/O. No file format or API changes were necessary for this change. The next phase will be to create a "selection driver" for each type of selection, allowing each type of selection to directly call certain methods that only apply to that type of selection, instead of passing through dozens of functions which have switch statements to call the appropriate method for each selection type. This will also reduce the amount of code in the library and speed things up a bit more. Phase 3 will involve generating an MPI datatype for all types of selections, instead of only "regular" hyperslab and 'all' selections. This will allow collective parallel I/O for all I/O operations which don't require type conversions. It will also open up the door for allowing collective I/O on datasets which require type conversion. Phase 4 will involve changing the access pattern to deal with chunked datasets in a more optimal way (in serial). Phase 5 will deal with accessing chunked datasets more optimally for collective parallel I/O operations. Platforms tested: FreeBSD 4.6 (sleipnir) w/ parallel & C++ and IRIX64 6.5 (modi4) w/parallel
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