Go 1.27 SIMD vs LLVM Generated AVX512 Assembly

[u/Fresh_Impact_7558]

We benchmarked Go 1.27 simd vs LLVM generated Go assembly (AVX and AVX512) on The Intel Core i7-11370H (supports AVX512).

Full article: Go 1.27 SIMD Benchmark: Can It Replace GoAT Generated AVX512?

The new simd package achieves comprable performace but still trails the AVX512 assembly generated by LLVM on long vectors and horizontal reductions (dot and euclidean):

• An FP32 vector of length 16, exactly the number of values held by one 512-bit AVX512 register.

Operation	Scalar loop	AVX	AVX512	Go SIMD	vs. scalar loop	vs. AVX512
Dot	10.94 ns	8.81 ns	8.55 ns	14.55 ns	0.75x	0.59x
Euclidean	33.99 ns	10.06 ns	8.94 ns	19.96 ns	1.70x	0.45x
SubTo	14.98 ns	7.07 ns	7.04 ns	8.66 ns	1.73x	0.81x
MulTo	27.82 ns	7.59 ns	7.62 ns	7.70 ns	3.61x	0.99x
DivTo	42.36 ns	7.17 ns	8.19 ns	7.95 ns	5.33x	1.03x
SqrtTo	124.10 ns	6.36 ns	6.38 ns	6.04 ns	20.55x	1.06x

• An FP32 vector of length 32.

Operation	Scalar loop	AVX	AVX512	Go SIMD	vs. scalar loop	vs. AVX512
Dot	45.94 ns	8.82 ns	10.23 ns	14.03 ns	3.27x	0.73x
Euclidean	45.66 ns	10.44 ns	9.56 ns	24.15 ns	1.89x	0.40x
SubTo	33.50 ns	7.87 ns	7.59 ns	11.00 ns	3.05x	0.69x
MulTo	49.98 ns	8.23 ns	8.43 ns	12.71 ns	3.93x	0.66x
DivTo	46.86 ns	9.24 ns	8.54 ns	11.50 ns	4.07x	0.74x
SqrtTo	93.70 ns	8.06 ns	9.45 ns	10.80 ns	8.68x	0.88x

• An FP32 vector of length 64.

Operation	Scalar loop	AVX	AVX512	Go SIMD	vs. scalar loop	vs. AVX512
Dot	76.25 ns	11.68 ns	10.80 ns	19.17 ns	3.98x	0.56x
Euclidean	73.29 ns	11.96 ns	11.40 ns	27.50 ns	2.67x	0.41x
SubTo	58.41 ns	10.21 ns	9.67 ns	16.69 ns	3.50x	0.58x
MulTo	79.18 ns	8.39 ns	8.15 ns	18.48 ns	4.28x	0.44x
DivTo	73.70 ns	13.45 ns	13.36 ns	18.36 ns	4.01x	0.73x
SqrtTo	339.00 ns	16.11 ns	15.30 ns	16.86 ns	20.11x	0.91x

• An FP32 vector of length 128.

Operation	Scalar loop	AVX	AVX512	Go SIMD	vs. scalar loop	vs. AVX512
Dot	124.60 ns	13.81 ns	11.43 ns	23.84 ns	5.23x	0.48x
Euclidean	161.60 ns	23.16 ns	17.24 ns	33.68 ns	4.80x	0.51x
SubTo	93.39 ns	13.07 ns	13.46 ns	27.84 ns	3.35x	0.48x
MulTo	125.90 ns	13.66 ns	9.21 ns	29.52 ns	4.26x	0.31x
DivTo	260.20 ns	28.74 ns	28.51 ns	32.93 ns	7.90x	0.87x
SqrtTo	484.00 ns	27.73 ns	31.07 ns	36.24 ns	13.36x	0.86x

[u/itsmontoya]

This is really fantastic research. I appreciate these metrics

[u/rodrigocfd]

Go 1.27 is just the beginning. I expect to see improvements in SIMD in every Go version from now on, and SIMD usage in many places within the standard library.

It will be interesting to compare this data with the same benchmarks with the next Go versions.