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Vendor the upstream changes with Avx512 (#7225)

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Thanks to @fwessels we have Avx512 support with 4x improvement
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Harshavardhana
2019-02-12 04:02:27 -08:00
committed by Nitish Tiwari
parent fef5416b3c
commit 118270d76f
10 changed files with 847 additions and 32 deletions
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vendor/github.com/klauspost/reedsolomon/README.md
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@@ -24,6 +24,10 @@ go get -u github.com/klauspost/reedsolomon
# Changes
## February 8, 2019
AVX512 accelerated version added for Intel Skylake CPUs. This can give up to a 4x speed improvement as compared to AVX2. See [here](https://github.com/klauspost/reedsolomon#performance-on-avx512) for more details.
## December 18, 2018
Assembly code for ppc64le has been contributed, this boosts performance by about 10x on this platform.
@@ -253,6 +257,25 @@ BenchmarkReconstruct50x20x1M-8 1364.35 4189.79 3.07x
BenchmarkReconstruct10x4x16M-8 1484.35 5779.53 3.89x
```
# Performance on AVX512
The performance on AVX512 has been accelerated for Intel CPUs. This gives speedups on a per-core basis of up to 4x compared to AVX2 as can be seen in the following table:
```
$ benchcmp avx2.txt avx512.txt
benchmark AVX2 MB/s AVX512 MB/s speedup
BenchmarkEncode8x8x1M-72 1681.35 4125.64 2.45x
BenchmarkEncode8x4x8M-72 1529.36 5507.97 3.60x
BenchmarkEncode8x8x8M-72 791.16 2952.29 3.73x
BenchmarkEncode8x8x32M-72 573.26 2168.61 3.78x
BenchmarkEncode12x4x12M-72 1234.41 4912.37 3.98x
BenchmarkEncode16x4x16M-72 1189.59 5138.01 4.32x
BenchmarkEncode24x8x24M-72 690.68 2583.70 3.74x
BenchmarkEncode24x8x48M-72 674.20 2643.31 3.92x
```
This speedup has been achieved by computing multiple parity blocks in parallel as opposed to one after the other. In doing so it is possible to minimize the memory bandwidth required for loading all data shards. At the same time the calculations are performed in the 512-bit wide ZMM registers and the surplus of ZMM registers (32 in total) is used to keep more data around (most notably the matrix coefficients).
# Performance on ARM64 NEON
By exploiting NEON instructions the performance for ARM has been accelerated. Below are the performance numbers for a single core on an ARM Cortex-A53 CPU @ 1.2GHz (Debian 8.0 Jessie running Go: 1.7.4):
@@ -287,7 +310,6 @@ BenchmarkGaloisXor1M-160 784.60 6296.65 8.03x
* [Reed-Solomon Erasure Coding in Haskell](https://github.com/NicolasT/reedsolomon). Haskell port of the package with similar performance.
* [reed-solomon-erasure](https://github.com/darrenldl/reed-solomon-erasure). Compatible Rust implementation.
* [go-erasure](https://github.com/somethingnew2-0/go-erasure). A similar library using cgo, slower in my tests.
* [rsraid](https://github.com/goayame/rsraid). A similar library written in Go. Slower, but supports more shards.
* [Screaming Fast Galois Field Arithmetic](http://www.snia.org/sites/default/files2/SDC2013/presentations/NewThinking/EthanMiller_Screaming_Fast_Galois_Field%20Arithmetic_SIMD%20Instructions.pdf). Basis for SSE3 optimizations.
# License