https://github.com/kelindar/simd
Package with auto-vectorized math functions for Go
https://github.com/kelindar/simd
Last synced: about 1 month ago
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Package with auto-vectorized math functions for Go
- Host: GitHub
- URL: https://github.com/kelindar/simd
- Owner: kelindar
- License: mit
- Created: 2022-06-05T11:42:40.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2022-06-05T18:22:58.000Z (almost 3 years ago)
- Last Synced: 2025-03-27T13:11:29.506Z (about 2 months ago)
- Language: Assembly
- Size: 4.3 MB
- Stars: 24
- Watchers: 2
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: LICENSE
Awesome Lists containing this project
README
## Vectorized Math Functions
This library contains a set of vectorized mathematical functions which were [auto-vectorized](https://llvm.org/docs/Vectorizers.html) using clang compiler and translated into PLAN9 assembly code for Go. Generic version is also provided for CPUs where vectorization is not available, or for which this library doesn't have a generated code.
It currently supports only `AVX2`, but `AVX512` and `SVE` (for `ARM`) should be easy enough to generate. Most of the code in this library is auto-generated, which helps with maintenance.
## Usage
Usage of this library is very straightforward, it simply exposes a set of non-opinionated functions. For example, if you want to sum up a slice of floating point numbers, you can use `SumFloat32s([]float32) float32` function to do so.
```go
sum := simd.SumFloat32s([]float32{1, 2, 3, 4, 5})
```
## Benchmarks
```go
goos: windows
goarch: amd64
pkg: github.com/kelindar/simd
cpu: Intel(R) Core(TM) i7-9700K CPU @ 3.60GHz
TYPE OP SIZE RATE SPEEDUP
float32 sum 256 8.96 ns/op 20.51x
float32 min 256 27.78 ns/op 4.15x
float32 max 256 25.94 ns/op 4.43x
float32 add 256 15.31 ns/op 7.46x
float32 sub 256 15.48 ns/op 7.34x
float32 mul 256 15.36 ns/op 7.54x
float32 div 256 27.88 ns/op 5.79x
float32 sum 4096 107.92 ns/op 31.60x
float32 min 4096 134.06 ns/op 13.01x
float32 max 4096 133.90 ns/op 12.94x
float32 add 4096 353.01 ns/op 4.90x
float32 sub 4096 353.62 ns/op 4.92x
float32 mul 4096 353.64 ns/op 4.87x
float32 div 4096 455.60 ns/op 5.68x
float32 sum 16384 469.18 ns/op 29.44x
float32 min 16384 497.91 ns/op 13.94x
float32 max 16384 500.43 ns/op 13.84x
float32 add 16384 1442.28 ns/op 4.82x
float32 sub 16384 1366.98 ns/op 5.07x
float32 mul 16384 1382.20 ns/op 4.97x
float32 div 16384 1821.82 ns/op 5.71x
TYPE OP SIZE RATE SPEEDUP
float64 sum 256 14.56 ns/op 12.61x
float64 min 256 24.51 ns/op 4.73x
float64 max 256 24.61 ns/op 3.71x
float64 add 256 25.81 ns/op 4.42x
float64 sub 256 25.84 ns/op 4.41x
float64 mul 256 25.66 ns/op 4.45x
float64 div 256 109.60 ns/op 1.97x
float64 sum 4096 220.98 ns/op 15.51x
float64 min 4096 229.76 ns/op 7.62x
float64 max 4096 227.68 ns/op 5.86x
float64 add 4096 707.07 ns/op 2.44x
float64 sub 4096 716.65 ns/op 2.45x
float64 mul 4096 699.45 ns/op 2.50x
float64 div 4096 1726.40 ns/op 2.01x
float64 sum 16384 930.43 ns/op 14.77x
float64 min 16384 930.08 ns/op 7.45x
float64 max 16384 938.31 ns/op 5.81x
float64 add 16384 5522.65 ns/op 1.45x
float64 sub 16384 5433.96 ns/op 1.55x
float64 mul 16384 5564.75 ns/op 1.51x
float64 div 16384 6913.10 ns/op 2.01x
TYPE OP SIZE RATE SPEEDUP
uint8 sum 100 5.94 ns/op 6.34x
uint8 min 100 7.09 ns/op 7.31x
uint8 max 100 7.82 ns/op 6.25x
uint8 add 100 9.13 ns/op 5.76x
uint8 sub 100 9.11 ns/op 5.73x
uint8 mul 100 11.15 ns/op 6.37x
uint8 div 100 186.89 ns/op 1.17x
TYPE OP SIZE RATE SPEEDUP
uint16 sum 256 6.13 ns/op 13.19x
uint16 min 256 10.00 ns/op 15.94x
uint16 max 256 11.11 ns/op 9.58x
uint16 add 256 10.04 ns/op 16.83x
uint16 sub 256 10.07 ns/op 16.77x
uint16 mul 256 10.45 ns/op 16.26x
uint16 div 256 438.34 ns/op 1.26x
uint16 sum 4096 38.15 ns/op 32.42x
uint16 min 4096 57.84 ns/op 44.50x
uint16 max 4096 58.61 ns/op 29.17x
uint16 add 4096 86.01 ns/op 30.29x
uint16 sub 4096 91.34 ns/op 30.54x
uint16 mul 4096 89.25 ns/op 29.65x
uint16 div 4096 7203.14 ns/op 1.26x
uint16 sum 16384 148.55 ns/op 34.66x
uint16 min 16384 231.87 ns/op 44.76x
uint16 max 16384 227.01 ns/op 31.32x
uint16 add 16384 722.47 ns/op 14.60x
uint16 sub 16384 737.93 ns/op 14.21x
uint16 mul 16384 711.59 ns/op 14.84x
uint16 div 16384 28084.66 ns/op 1.24x
TYPE OP SIZE RATE SPEEDUP
uint32 sum 256 8.06 ns/op 10.39x
uint32 min 256 22.96 ns/op 6.96x
uint32 max 256 26.21 ns/op 4.12x
uint32 add 256 15.91 ns/op 8.18x
uint32 sub 256 15.49 ns/op 7.98x
uint32 mul 256 16.81 ns/op 7.40x
uint32 div 256 436.08 ns/op 1.29x
uint32 sum 4096 75.90 ns/op 16.47x
uint32 min 4096 120.89 ns/op 21.54x
uint32 max 4096 125.33 ns/op 13.76x
uint32 add 4096 380.00 ns/op 5.16x
uint32 sub 4096 345.19 ns/op 5.69x
uint32 mul 4096 367.35 ns/op 4.91x
uint32 div 4096 6695.04 ns/op 1.29x
uint32 sum 16384 462.89 ns/op 10.85x
uint32 min 16384 475.29 ns/op 21.98x
uint32 max 16384 481.76 ns/op 14.43x
uint32 add 16384 1437.51 ns/op 5.49x
uint32 sub 16384 1427.22 ns/op 5.57x
uint32 mul 16384 1367.51 ns/op 5.71x
uint32 div 16384 26786.72 ns/op 1.30x
TYPE OP SIZE RATE SPEEDUP
uint64 sum 256 12.35 ns/op 9.18x
uint64 min 256 41.42 ns/op 3.84x
uint64 max 256 44.52 ns/op 2.55x
uint64 add 256 24.86 ns/op 4.92x
uint64 sub 256 25.35 ns/op 4.82x
uint64 mul 256 50.52 ns/op 2.37x
uint64 div 256 1250.57 ns/op 1.18x
uint64 sum 4096 145.98 ns/op 11.78x
uint64 min 4096 507.57 ns/op 5.11x
uint64 max 4096 508.87 ns/op 3.42x
uint64 add 4096 701.61 ns/op 2.79x
uint64 sub 4096 719.04 ns/op 2.74x
uint64 mul 4096 881.98 ns/op 2.18x
uint64 div 4096 20114.02 ns/op 1.18x
uint64 sum 16384 930.65 ns/op 7.44x
uint64 min 16384 2059.33 ns/op 5.08x
uint64 max 16384 2071.32 ns/op 3.34x
uint64 add 16384 6001.34 ns/op 1.45x
uint64 sub 16384 5713.91 ns/op 1.52x
uint64 mul 16384 6147.43 ns/op 1.44x
uint64 div 16384 80476.33 ns/op 1.17x
TYPE OP SIZE RATE SPEEDUP
int8 sum 100 5.89 ns/op 6.18x
int8 min 100 7.51 ns/op 6.81x
int8 max 100 7.46 ns/op 6.33x
int8 add 100 9.10 ns/op 5.74x
int8 sub 100 9.13 ns/op 5.75x
int8 mul 100 10.97 ns/op 6.46x
int8 div 100 480.25 ns/op 0.63x
TYPE OP SIZE RATE SPEEDUP
int16 sum 256 6.20 ns/op 13.04x
int16 min 256 10.80 ns/op 9.77x
int16 max 256 10.13 ns/op 10.53x
int16 add 256 9.99 ns/op 16.97x
int16 sub 256 10.00 ns/op 17.03x
int16 mul 256 10.47 ns/op 16.24x
int16 div 256 499.02 ns/op 1.53x
int16 sum 4096 37.97 ns/op 32.87x
int16 min 4096 59.55 ns/op 29.15x
int16 max 4096 58.42 ns/op 29.54x
int16 add 4096 85.73 ns/op 30.27x
int16 sub 4096 86.22 ns/op 30.07x
int16 mul 4096 86.61 ns/op 30.00x
int16 div 4096 7936.80 ns/op 1.52x
int16 sum 16384 144.40 ns/op 34.61x
int16 min 16384 226.17 ns/op 30.59x
int16 max 16384 222.39 ns/op 30.90x
int16 add 16384 708.78 ns/op 14.55x
int16 sub 16384 722.46 ns/op 14.33x
int16 mul 16384 715.68 ns/op 14.49x
int16 div 16384 31537.05 ns/op 1.52x
TYPE OP SIZE RATE SPEEDUP
int32 sum 256 8.04 ns/op 10.35x
int32 min 256 22.58 ns/op 4.72x
int32 max 256 22.80 ns/op 4.67x
int32 add 256 14.89 ns/op 8.29x
int32 sub 256 15.08 ns/op 8.20x
int32 mul 256 15.86 ns/op 7.61x
int32 div 256 490.90 ns/op 1.37x
int32 sum 4096 76.31 ns/op 16.23x
int32 min 4096 121.09 ns/op 14.37x
int32 max 4096 120.26 ns/op 14.35x
int32 add 4096 347.35 ns/op 5.64x
int32 sub 4096 351.04 ns/op 5.58x
int32 mul 4096 341.38 ns/op 5.34x
int32 div 4096 7849.51 ns/op 1.37x
int32 sum 16384 467.90 ns/op 10.59x
int32 min 16384 486.13 ns/op 14.18x
int32 max 16384 480.85 ns/op 14.48x
int32 add 16384 1426.40 ns/op 5.53x
int32 sub 16384 1421.44 ns/op 5.53x
int32 mul 16384 1448.81 ns/op 5.41x
int32 div 16384 31078.60 ns/op 1.38x
TYPE OP SIZE RATE SPEEDUP
int64 sum 256 12.13 ns/op 6.71x
int64 min 256 30.63 ns/op 3.47x
int64 max 256 31.69 ns/op 3.84x
int64 add 256 25.72 ns/op 5.17x
int64 sub 256 25.66 ns/op 5.45x
int64 mul 256 51.14 ns/op 2.38x
int64 div 256 1524.32 ns/op 1.18x
int64 sum 4096 145.87 ns/op 8.59x
int64 min 4096 327.28 ns/op 5.26x
int64 max 4096 331.75 ns/op 5.24x
int64 add 4096 696.99 ns/op 2.83x
int64 sub 4096 711.28 ns/op 2.76x
int64 mul 4096 890.62 ns/op 2.13x
int64 div 4096 24268.84 ns/op 1.18x
int64 sum 16384 933.71 ns/op 5.59x
int64 min 16384 1415.62 ns/op 4.90x
int64 max 16384 1419.97 ns/op 4.88x
int64 add 16384 5541.14 ns/op 1.53x
int64 sub 16384 5183.70 ns/op 1.62x
int64 mul 16384 6164.29 ns/op 1.36x
int64 div 16384 96899.48 ns/op 1.18x
```
# Acknowledgements
This library was originally inspired by the work of Valery Carey & Adrian Witas in [viant/vec](https://github.com/viant/vec) package, but instead of hand-rolled assembly and intrinsics I opted for using auto-vectorization for maintainability reasons.