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+
+ 1) Test Setup
+ *************
+
+ The tests were performed an a system with the following specifications:
+
+ AMD Ryzen 7 3700X
+ 32GiB DDR4 RAM
+ Fedora 32
+
+
+ An optimized build of squashfs-tools-ng was compiled and installed to a tmpfs:
+
+ $ mkdir /dev/shm/temp
+ $ ln -s /dev/shm/temp out
+ $ ./autogen.sh
+ $ ./configure CFLAGS="-O3 -Ofast -march=native -mtune=native" \
+ LDFLAGS="-O3 -Ofast" --prefix=$(pwd)/out
+ $ make -j install
+ $ cd out
+
+
+ This was done to eliminate any influence of I/O performance and I/O caching
+ side effects to the extend possible and only measure the actual processing
+ time.
+
+
+ For all benchmark tests, a Debian image extracted from the Debian 10.2 LiveDVD
+ for AMD64 with XFCE was used.
+
+ The Debian image is expected to contain realistic input data for a Linux
+ file system and also provide enough data for an interesting benchmark.
+
+
+ For all performed benchmarks, graphical representations of the results and
+ derived values can be seen in "benchmark.ods".
+
+
+ 1) Parallel Compression Benchmark
+ *********************************
+
+ 1.1) What was measured?
+
+ The Debian image was first converted to a tarball:
+
+ $ ./bin/sqfs2tar debian.sqfs > test.tar
+
+ The tarball was then repacked and time was measured as follows:
+
+ $ time ./bin/tar2sqfs -j <NUM_CPU> -c <COMPRESSOR> -f test.sqfs < test.tar
+
+
+ The repacking was repeated 4 times and the worst wall-clock time ("real") was
+ used for comparison.
+
+ Altough not relevant for this benchmark, the resulting image sizes where
+ for a specific compressor, so that the compression ratio could be estimated:
+
+ $ stat test.tar
+ $ stat test.sqfs
+
+
+
+ The <NUM_CPU> was varied from 1 to 16 and for <COMPRESSOR>, all available
+ compressors were used. All possible combinations <NUM_CPU> and <COMPRESSOR>
+ were measured.
+
+ In addition, a serial reference version was compiled by running configure
+ with the additional option --without-pthread and re-running the tests for
+ all compressors without the <NUM_CPU> option.
+
+
+ 1.2) What was computed from the results?
+
+ The relative and absolute speedup were determined as follows:
+
+ runtime_parallel(compressor, num_cpu)
+ spedup_rel(compressor, num_cpu) = -------------------------------------
+ runtime_parallel(compressor, 1)
+
+ runtime_parallel(compressor, num_cpu)
+ spedup_abs(compressor, num_cpu) = -------------------------------------
+ runtime_serial(compressor)
+
+
+ In addition, relative and absolute efficiency of the parellel implementation
+ was determined:
+
+ speedup_rel(compressor, num_cpu)
+ efficiency_rel(compressor, num_cpu) = --------------------------------
+ num_cpu
+
+ speedup_abs(compressor, num_cpu)
+ efficiency_abs(compressor, num_cpu) = --------------------------------
+ num_cpu
+
+
+ Furthermore, altough not relevant for this specific benchmark, having the
+ converted tarballs available, the compression ratio was computed as follows:
+
+ file_size(tarball)
+ compression_ratio(compressor) = ---------------------
+ file_size(compressor)
+
+
+ 1.3) What software versions were used?
+
+ squashfs-tools-ng v0.9
+
+ TODO: update data and write the *exact* commit hash here, as well as gcc and
+ Linux versions.
+
+
+ 1.4) Results
+
+ The raw timing results are as follows:
+
+ Jobs XZ lzma gzip LZO LZ4 zstd
+ serial 17m39.613s 16m10.710s 9m56.606s 13m22.337s 12.159s 9m33.600s
+ 1 17m38.050s 15m49.753s 9m46.948s 13m06.705s 11.908s 9m23.445s
+ 2 9m26.712s 8m24.706s 5m08.152s 6m53.872s 7.395s 5m 1.734s
+ 3 6m29.733s 5m47.422s 3m33.235s 4m44.407s 6.069s 3m30.708s
+ 4 5m02.993s 4m30.361s 2m43.447s 3m39.825s 5.864s 2m44.418s
+ 5 4m07.959s 3m40.860s 2m13.454s 2m59.395s 5.749s 2m16.745s
+ 6 3m30.514s 3m07.816s 1m53.641s 2m32.461s 5.926s 1m57.607s
+ 7 3m04.009s 2m43.765s 1m39.742s 2m12.536s 6.281s 1m43.734s
+ 8 2m45.050s 2m26.996s 1m28.776s 1m58.253s 6.395s 1m34.500s
+ 9 2m34.993s 2m18.868s 1m21.668s 1m50.461s 6.890s 1m29.820s
+ 10 2m27.399s 2m11.214s 1m15.461s 1m44.060s 7.225s 1m26.176s
+ 11 2m20.068s 2m04.592s 1m10.286s 1m37.749s 7.557s 1m22.566s
+ 12 2m13.131s 1m58.710s 1m05.957s 1m32.596s 8.127s 1m18.883s
+ 13 2m07.472s 1m53.481s 1m02.041s 1m27.982s 8.704s 1m16.218s
+ 14 2m02.365s 1m48.773s 1m00.337s 1m24.444s 9.494s 1m14.175s
+ 15 1m58.298s 1m45.079s 58.348s 1m21.445s 10.192s 1m12.134s
+ 16 1m55.940s 1m42.176s 56.615s 1m19.030s 10.964s 1m11.049s
+
+
+ The sizes of the tarball and the resulting images:
+
+ - LZ4 compressed SquashFS image: ~3.1GiB (3,381,751,808)
+ - LZO compressed SquashFS image: ~2.5GiB (2,732,015,616)
+ - zstd compressed SquashFS image: ~2.1GiB (2,295,017,472)
+ - gzip compressed SquashFS image: ~2.3GiB (2,471,276,544)
+ - lzma compressed SquashFS image: ~2.0GiB (2,102,169,600)
+ - XZ compressed SquashFS image: ~2.0GiB (2,098,466,816)
+ - raw tarball: ~6.5GiB (7,008,118,272)
+
+
+
+ 1.5) Discussion
+
+ Most obviously, the results indicate that LZ4, unlike the other compressors,
+ is clearly I/O bound and not CPU bound and doesn't benefit from parallelization
+ beyond 2-4 worker threads and even that benefit is marginal with efficiency
+ plummetting immediately.
+
+
+ The other compressors are clearly CPU bound. Speedup increases linearly until
+ about 8 cores, but with a slope < 1, as evident by efficiency linearly
+ decreasing and reaching 80% for 8 cores.
+
+ A reason for this sub-linear scaling may be the choke point introduced by the
+ creation of fragment blocks, that *requires* a synchronization. To test this
+ theory, a second benchmark should be performed with fragment block generation
+ completely disabled. This requires a new flag to be added to tar2sqfs (and
+ also gensquashfs).
+
+
+ Using more than 8 jobs causes a much slower increase in speedup and efficency
+ declines even faster. This is probably due to the fact that the test system
+ only has 8 physical cores and beyond that, SMT has to be used.
+
+
+ It should also be noted that the thread pool compressor with only a single
+ thread turns out to be *slightly* faster than the serial reference
+ implementation. A possible explanation for this might be that the fragment
+ blocks are actually assembled in the main thread, in parallel to the worker
+ that can still continue with other data blocks. Because of this decoupling
+ there is in fact some degree of parallelism, even if only one worker thread
+ is used.
+
+
+ As a side effect, this benchmark also produces some insights into the
+ compression ratio and throughput of the supported compressors. Indicating that
+ for the Debian live image, XZ clearly provides the highest data density, while
+ LZ4 is clearly the fastest compressor available.
+
+ The throughput of the zstd compressor is comparable to gzip, while the
+ resulting compression ratio is closer to LZMA.
+
+ Repeating the benchmark without tail-end-packing and with fragments completely
+ disabled would also show the effectiveness of tail-end-packing and fragment
+ packing as a side effect.
+
+
+ 2) Reference Decompression Benchmark
+ ************************************
+
+ 1.1) What was measured?
+
+ A SquashFS image was generated for each supported compressor:
+
+ $ ./bin/sqfs2tar debian.sqfs | ./bin/tar2sqfs -c <COMPRESSOR> test.sqfs
+
+ And then, for each compressor, the unpacking time was measured:
+
+ $ time ./bin/sqfs2tar test.sqfs > /dev/null
+
+
+ The unpacking step was repeated 4 times and the worst wall-clock time ("real")
+ was used for comparison.
+
+
+ 2.2) What software version was used?
+
+ squashfs-tools-ng commit cc1141984a03da003e15ff229d3b417f8e5a24ad
+
+ gcc version: 10.2.1 20201016 (Red Hat 10.2.1-6)
+ Linux version: 5.8.16-200.fc32.x86_64
+
+
+ 2.3) Results
+
+ gzip 20.466s
+ lz4 2.519s
+ lzma 1m58.455s
+ lzo 10.521s
+ xz 1m59.451s
+ zstd 7.833s
+
+
+ 2.4) Discussion
+
+ From the measurement, it becomes obvious that LZ4 and zstd are the two fastest
+ decompressors. Zstd is particularly noteworth here, because it is not far
+ behind LZ4 in speed, but also achievs a substantially better compression ratio
+ that is somewhere between gzip and lzma. LZ4, despite being the fastest in
+ decompression and beating the others in compression speed by orders of
+ magnitudes, has by far the worst compression ratio.
+
+ It should be noted that the actual number of actually compressed blocks has not
+ been determined. A worse compression ratio can lead to more blocks being stored
+ uncompressed, reducing the workload and thus affecting decompression time.
+
+ However, since zstd has a better compression ratio than gzip, takes only 30% of
+ the time to decompress, and in the serial compression benchmark only takes 2%
+ of the time to compress, we cane safely say that in this benchmark, zstd beats
+ gzip by every metric.
+
+ Furthermore, while XZ stands out as the compressor with the best compression
+ ratio, zstd only takes ~6% of the time to decompress the entire image, while
+ being ~17% bigger than XZ. Shaving off 17% is definitely signifficant,
+ especially considering that in absolute numbers it is in the 100MB range, but
+ it clearly comes at a substential performance cost.
+
+
+ Also interesting are the results for the LZO compressor. Its compression speed
+ is between gzip and LZMA, decompression speed is about 50% of gzip, and only a
+ little bit worse than zstd, but its compression ratio is the second worst only
+ after LZ4, which beats it by a factor of 5 in decompression speed and by ~60
+ in compression speed.
+
+
+ Concluding, for applications where a good compression ratio is most imporant,
+ XZ is obviously the best choice, but if speed is favoured, zstd is probably a
+ very good option to go with. LZ4 is much faster, but has a lot worse
+ compression ratio. It is probably best suited as transparent compression for a
+ read/write file system or network protocols.
+
+
+ Finally, it should be noted, that this serial decompression benchmark is not
+ representative of a real-life workload where only a small set of files are
+ accessed in a random access fashion. In that case, a caching layer can largely
+ mitigate the decompression cost, translating it into an initial or only
+ occasionally occouring cache miss latency. But this benchmark should in theory
+ give an approximate idea how those cache miss latencies are expected to
+ compare between the different compressors.