dc63e0ad9693e13390ba31b00d92ecccaf7605c3
32-bit loads with a 64-bit load during compression (it's not a win). The main target for this optimization is ARM, but 32-bit x86 gets a small gain, too, although there is noise in the microbenchmarks. It's a no-op for 64-bit x86. It does not affect decompression. Microbenchmark results on a Cortex-A9 1GHz, using g++ 4.6.2 (from Ubuntu/Linaro), -O2 -DNDEBUG -Wa,-march=armv7a -mtune=cortex-a9 -mthumb-interwork, minimum 1000 iterations: Benchmark Time(ns) CPU(ns) Iterations --------------------------------------------------- BM_ZFlat/0 1158277 1160000 1000 84.2MB/s html (23.57 %) [ +4.3%] BM_ZFlat/1 14861782 14860000 1000 45.1MB/s urls (50.89 %) [ +1.1%] BM_ZFlat/2 393595 390000 1000 310.5MB/s jpg (99.88 %) [ +0.0%] BM_ZFlat/3 650583 650000 1000 138.4MB/s pdf (82.13 %) [ +3.1%] BM_ZFlat/4 4661480 4660000 1000 83.8MB/s html4 (23.55 %) [ +4.3%] BM_ZFlat/5 491973 490000 1000 47.9MB/s cp (48.12 %) [ +2.0%] BM_ZFlat/6 193575 192678 1038 55.2MB/s c (42.40 %) [ +9.0%] BM_ZFlat/7 62343 62754 3187 56.5MB/s lsp (48.37 %) [ +2.6%] BM_ZFlat/8 17708468 17710000 1000 55.5MB/s xls (41.34 %) [ -0.3%] BM_ZFlat/9 3755345 3760000 1000 38.6MB/s txt1 (59.81 %) [ +8.2%] BM_ZFlat/10 3324217 3320000 1000 36.0MB/s txt2 (64.07 %) [ +4.2%] BM_ZFlat/11 10139932 10140000 1000 40.1MB/s txt3 (57.11 %) [ +6.4%] BM_ZFlat/12 13532109 13530000 1000 34.0MB/s txt4 (68.35 %) [ +5.0%] BM_ZFlat/13 4690847 4690000 1000 104.4MB/s bin (18.21 %) [ +4.1%] BM_ZFlat/14 830682 830000 1000 43.9MB/s sum (51.88 %) [ +1.2%] BM_ZFlat/15 84784 85011 2235 47.4MB/s man (59.36 %) [ +1.1%] BM_ZFlat/16 1293254 1290000 1000 87.7MB/s pb (23.15 %) [ +2.3%] BM_ZFlat/17 2775155 2780000 1000 63.2MB/s gaviota (38.27 %) [+12.2%] Core i7 in 32-bit mode (only one run and 100 iterations, though, so noisy): Benchmark Time(ns) CPU(ns) Iterations --------------------------------------------------- BM_ZFlat/0 227582 223464 3043 437.0MB/s html (23.57 %) [ +7.4%] BM_ZFlat/1 2982430 2918455 233 229.4MB/s urls (50.89 %) [ +2.9%] BM_ZFlat/2 46967 46658 15217 2.5GB/s jpg (99.88 %) [ +0.0%] BM_ZFlat/3 115298 114864 5833 783.2MB/s pdf (82.13 %) [ +1.5%] BM_ZFlat/4 913440 899743 778 434.2MB/s html4 (23.55 %) [ +0.3%] BM_ZFlat/5 110302 108571 7000 216.1MB/s cp (48.12 %) [ +0.0%] BM_ZFlat/6 44409 43372 15909 245.2MB/s c (42.40 %) [ +0.8%] BM_ZFlat/7 15713 15643 46667 226.9MB/s lsp (48.37 %) [ +2.7%] BM_ZFlat/8 2625539 2602230 269 377.4MB/s xls (41.34 %) [ +1.4%] BM_ZFlat/9 808884 811429 875 178.8MB/s txt1 (59.81 %) [ -3.9%] BM_ZFlat/10 709532 700000 1000 170.5MB/s txt2 (64.07 %) [ +0.0%] BM_ZFlat/11 2177682 2162162 333 188.2MB/s txt3 (57.11 %) [ -1.4%] BM_ZFlat/12 2849640 2840000 250 161.8MB/s txt4 (68.35 %) [ -1.4%] BM_ZFlat/13 849760 835476 778 585.8MB/s bin (18.21 %) [ +1.2%] BM_ZFlat/14 165940 164571 4375 221.6MB/s sum (51.88 %) [ +1.4%] BM_ZFlat/15 20939 20571 35000 196.0MB/s man (59.36 %) [ +2.1%] BM_ZFlat/16 239209 236544 2917 478.1MB/s pb (23.15 %) [ +4.2%] BM_ZFlat/17 616206 610000 1000 288.2MB/s gaviota (38.27 %) [ -1.6%] R=sanjay git-svn-id: https://snappy.googlecode.com/svn/trunk@60 03e5f5b5-db94-4691-08a0-1a8bf15f6143
Snappy, a fast compressor/decompressor. Introduction ============ Snappy is a compression/decompression library. It does not aim for maximum compression, or compatibility with any other compression library; instead, it aims for very high speeds and reasonable compression. For instance, compared to the fastest mode of zlib, Snappy is an order of magnitude faster for most inputs, but the resulting compressed files are anywhere from 20% to 100% bigger. (For more information, see "Performance", below.) Snappy has the following properties: * Fast: Compression speeds at 250 MB/sec and beyond, with no assembler code. See "Performance" below. * Stable: Over the last few years, Snappy has compressed and decompressed petabytes of data in Google's production environment. The Snappy bitstream format is stable and will not change between versions. * Robust: The Snappy decompressor is designed not to crash in the face of corrupted or malicious input. * Free and open source software: Snappy is licensed under a BSD-type license. For more information, see the included COPYING file. Snappy has previously been called "Zippy" in some Google presentations and the like. Performance =========== Snappy is intended to be fast. On a single core of a Core i7 processor in 64-bit mode, it compresses at about 250 MB/sec or more and decompresses at about 500 MB/sec or more. (These numbers are for the slowest inputs in our benchmark suite; others are much faster.) In our tests, Snappy usually is faster than algorithms in the same class (e.g. LZO, LZF, FastLZ, QuickLZ, etc.) while achieving comparable compression ratios. Typical compression ratios (based on the benchmark suite) are about 1.5-1.7x for plain text, about 2-4x for HTML, and of course 1.0x for JPEGs, PNGs and other already-compressed data. Similar numbers for zlib in its fastest mode are 2.6-2.8x, 3-7x and 1.0x, respectively. More sophisticated algorithms are capable of achieving yet higher compression rates, although usually at the expense of speed. Of course, compression ratio will vary significantly with the input. Although Snappy should be fairly portable, it is primarily optimized for 64-bit x86-compatible processors, and may run slower in other environments. In particular: - Snappy uses 64-bit operations in several places to process more data at once than would otherwise be possible. - Snappy assumes unaligned 32- and 64-bit loads and stores are cheap. On some platforms, these must be emulated with single-byte loads and stores, which is much slower. - Snappy assumes little-endian throughout, and needs to byte-swap data in several places if running on a big-endian platform. Experience has shown that even heavily tuned code can be improved. Performance optimizations, whether for 64-bit x86 or other platforms, are of course most welcome; see "Contact", below. Usage ===== Note that Snappy, both the implementation and the main interface, is written in C++. However, several third-party bindings to other languages are available; see the Google Code page at http://code.google.com/p/snappy/ for more information. Also, if you want to use Snappy from C code, you can use the included C bindings in snappy-c.h. To use Snappy from your own C++ program, include the file "snappy.h" from your calling file, and link against the compiled library. There are many ways to call Snappy, but the simplest possible is snappy::Compress(input.data(), input.size(), &output); and similarly snappy::Uncompress(input.data(), input.size(), &output); where "input" and "output" are both instances of std::string. There are other interfaces that are more flexible in various ways, including support for custom (non-array) input sources. See the header file for more information. Tests and benchmarks ==================== When you compile Snappy, snappy_unittest is compiled in addition to the library itself. You do not need it to use the compressor from your own library, but it contains several useful components for Snappy development. First of all, it contains unit tests, verifying correctness on your machine in various scenarios. If you want to change or optimize Snappy, please run the tests to verify you have not broken anything. Note that if you have the Google Test library installed, unit test behavior (especially failures) will be significantly more user-friendly. You can find Google Test at http://code.google.com/p/googletest/ You probably also want the gflags library for handling of command-line flags; you can find it at http://code.google.com/p/google-gflags/ In addition to the unit tests, snappy contains microbenchmarks used to tune compression and decompression performance. These are automatically run before the unit tests, but you can disable them using the flag --run_microbenchmarks=false if you have gflags installed (otherwise you will need to edit the source). Finally, snappy can benchmark Snappy against a few other compression libraries (zlib, LZO, LZF, FastLZ and QuickLZ), if they were detected at configure time. To benchmark using a given file, give the compression algorithm you want to test Snappy against (e.g. --zlib) and then a list of one or more file names on the command line. The testdata/ directory contains the files used by the microbenchmark, which should provide a reasonably balanced starting point for benchmarking. (Note that baddata[1-3].snappy are not intended as benchmarks; they are used to verify correctness in the presence of corrupted data in the unit test.) Contact ======= Snappy is distributed through Google Code. For the latest version, a bug tracker, and other information, see http://code.google.com/p/snappy/
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