go-simd
Make certain functions Go faster with SIMD, loop unrolling, c2goasm or other optimization techniques.
This package chooses the most appropriate implementation at runtime, based on the host CPU features, however,
it is possible to disable certain implementations using the INTEL_DISABLE_EXT environment variable.
See the cpu package README for
a description of this environment variable.
Benchmarks
SumFloat64
Benchmark various sum implementations, aggregating 1000 and 10000 element slices of float64 values.
Intrinsicsuses handwritten AVX intrinsics via clangAVX2uses plain C code, exploiting auto-vectorization and AVX2 architecture enabled via clangSSE4uses plain C code, exploiting auto-vectorization and SSE4 architecture enabled via clangGois an equivalent loop in GoUnroll4andUnroll8are unrolled versions
BenchmarkSumFloat64_1000-8 20000000 59 ns/op 134057.61 MB/s
BenchmarkSumFloat64_10000-8 2000000 842 ns/op 94949.30 MB/s
BenchmarkSumFloat64_Intrinsics_1000-8 5000000 245 ns/op 32550.11 MB/s
BenchmarkSumFloat64_Intrinsics_10000-8 500000 2913 ns/op 27460.17 MB/s
BenchmarkSumFloat64_AVX2_1000-8 30000000 56 ns/op 142336.45 MB/s
BenchmarkSumFloat64_AVX2_10000-8 2000000 847 ns/op 94426.99 MB/s
BenchmarkSumFloat64_SSE4_1000-8 5000000 277 ns/op 28806.44 MB/s
BenchmarkSumFloat64_SSE4_10000-8 500000 2903 ns/op 27556.33 MB/s
BenchmarkSumFloat64_Go_1000-8 1000000 1124 ns/op 7116.81 MB/s
BenchmarkSumFloat64_Go_10000-8 200000 11583 ns/op 6906.38 MB/s
BenchmarkSumFloat64_GoUnroll4_1000-8 5000000 287 ns/op 27790.03 MB/s
BenchmarkSumFloat64_GoUnroll4_10000-8 500000 2896 ns/op 27616.44 MB/s
BenchmarkSumFloat64_GoUnroll8_1000-8 10000000 188 ns/op 42341.91 MB/s
BenchmarkSumFloat64_GoUnroll8_10000-8 500000 2924 ns/op 27358.12 MB/s
unicode/utf8.Valid
Provide a fast implementation of utf8.Valid using SSE and AVX2 functions. Credit for these SIMD implementations go to
Daniel Lemire.
Read this post for more information on these SIMD optimized functions.
BenchmarkValid/utf8.Valid/ASCII/100-8 20000000 79 ns/op 1257.68 MB/s
BenchmarkValid/utf8.Valid/ASCII/10000-8 200000 6140 ns/op 1628.48 MB/s
BenchmarkValid/utf8.Valid/ASCII/1000000-8 2000 608369 ns/op 1643.74 MB/s
BenchmarkValid/utf8.Valid/UTF8/100-8 10000000 139 ns/op 724.09 MB/s
BenchmarkValid/utf8.Valid/UTF8/10000-8 50000 32722 ns/op 305.60 MB/s
BenchmarkValid/utf8.Valid/UTF8/1000000-8 500 3953426 ns/op 252.95 MB/s
BenchmarkValid/sse4.Valid/UTF8/100-8 30000000 43 ns/op 2311.65 MB/s
BenchmarkValid/sse4.Valid/UTF8/10000-8 500000 2436 ns/op 4104.65 MB/s
BenchmarkValid/sse4.Valid/UTF8/1000000-8 10000 243250 ns/op 4110.98 MB/s
BenchmarkValid/sse4.Valid/ASCII/100-8 30000000 43 ns/op 2294.62 MB/s
BenchmarkValid/sse4.Valid/ASCII/10000-8 500000 2439 ns/op 4099.68 MB/s
BenchmarkValid/sse4.Valid/ASCII/1000000-8 5000 246138 ns/op 4062.75 MB/s
BenchmarkValid/avx2.Valid/ASCII/100-8 50000000 24 ns/op 4042.96 MB/s
BenchmarkValid/avx2.Valid/ASCII/10000-8 5000000 256 ns/op 39043.62 MB/s
BenchmarkValid/avx2.Valid/ASCII/1000000-8 50000 30786 ns/op 32481.66 MB/s
BenchmarkValid/avx2.Valid/UTF8/100-8 50000000 35 ns/op 2864.81 MB/s
BenchmarkValid/avx2.Valid/UTF8/10000-8 1000000 1440 ns/op 6943.45 MB/s
BenchmarkValid/avx2.Valid/UTF8/1000000-8 10000 142939 ns/op 6995.97 MB/s
encoding/ascii.Valid
A fast implementation for determining if a buffer is valid ASCII data. Credit for SIMD implementations go to Daniel Lemire.
BenchmarkValid/go.Valid/100-8 20000000 52 ns/op 1911.59 MB/s
BenchmarkValid/go.Valid/10000-8 500000 3048 ns/op 3280.27 MB/s
BenchmarkValid/go.Valid/1000000-8 5000 303508 ns/op 3294.80 MB/s
BenchmarkValid/sse4.Valid/100-8 100000000 11 ns/op 8674.49 MB/s
BenchmarkValid/sse4.Valid/10000-8 5000000 379 ns/op 26379.43 MB/s
BenchmarkValid/sse4.Valid/1000000-8 50000 37061 ns/op 26982.04 MB/s
BenchmarkValid/avx2.Valid/100-8 200000000 8 ns/op 12437.12 MB/s
BenchmarkValid/avx2.Valid/10000-8 10000000 137 ns/op 72718.12 MB/s
BenchmarkValid/avx2.Valid/1000000-8 100000 17767 ns/op 56280.99 MB/s
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