Accelerate SDPA on Arm CPUs: Update OpenBLAS to v0.3.32#177012
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Accelerate SDPA on Arm CPUs: Update OpenBLAS to v0.3.32#177012fadara01 wants to merge 4 commits intogh/fadara01/12/basefrom
fadara01 wants to merge 4 commits intogh/fadara01/12/basefrom
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/177012
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (2 Unrelated Failures)As of commit a8a4728 with merge base 0951602 ( FLAKY - The following job failed but was likely due to flakiness present on trunk:
UNSTABLE - The following job is marked as unstable, possibly due to flakiness on trunk:
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OpenBLAS v0.3.31 adds support for BGEMM on SVE128, SVE256 machines and general optimizations for SBGEMM/BGEMM: OpenMathLib/OpenBLAS#5419, OpenMathLib/OpenBLAS#5399 among other things. OpenBLAS v0.3.32 accelerates SBGEMM/BGEMM on SVE128 machines by ~20%: OpenMathLib/OpenBLAS#5667 This accelerates SDPA, and will be capitalized on by #172945 further to accelerate linear,mm, bmm, etc PS: BGEMM means bf16 x bf16 -> bf16 and SBGEMM means: bf16 x bf16 -> fp32 ghstack-source-id: cf38a01 Pull-Request: #177012
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CI is expected to fail, OpenBLAS v0.3.32 hasn't been released yet. |
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OpenBLAS v0.3.31 adds support for BGEMM on SVE128, SVE256 machines and general optimizations for SBGEMM/BGEMM: OpenMathLib/OpenBLAS#5419, OpenMathLib/OpenBLAS#5399 among other things. OpenBLAS v0.3.32 accelerates SBGEMM/BGEMM on SVE128 machines by ~20%: OpenMathLib/OpenBLAS#5667 This accelerates SDPA, and will be capitalized on by #172945 further to accelerate linear,mm, bmm, etc PS: BGEMM means bf16 x bf16 -> bf16 and SBGEMM means: bf16 x bf16 -> fp32 ghstack-source-id: 952fd9e Pull-Request: #177012
fadara01
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OpenBLAS v0.3.31 adds support for BGEMM on SVE128, SVE256 machines and general optimizations for SBGEMM/BGEMM: OpenMathLib/OpenBLAS#5419, OpenMathLib/OpenBLAS#5399 among other things. OpenBLAS v0.3.32 accelerates SBGEMM/BGEMM on SVE128 machines by ~20%: OpenMathLib/OpenBLAS#5667 This accelerates SDPA, and will be capitalized on by #172945 further to accelerate linear,mm, bmm, etc PS: BGEMM means bf16 x bf16 -> bf16 and SBGEMM means: bf16 x bf16 -> fp32 ghstack-source-id: 596be25 Pull-Request: #177012
fadara01
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OpenBLAS v0.3.31 adds support for BGEMM on SVE128, SVE256 machines and general optimizations for SBGEMM/BGEMM: OpenMathLib/OpenBLAS#5419, OpenMathLib/OpenBLAS#5399 among other things. OpenBLAS v0.3.32 accelerates SBGEMM/BGEMM on SVE128 machines by ~20%: OpenMathLib/OpenBLAS#5667 This accelerates SDPA, and will be capitalized on by #172945 further to accelerate linear,mm, bmm, etc PS: BGEMM means bf16 x bf16 -> bf16 and SBGEMM means: bf16 x bf16 -> fp32 ghstack-source-id: 545189c Pull-Request: #177012
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OpenBLAS v0.3.32 has been released: https://github.com/OpenMathLib/OpenBLAS/tree/v0.3.32 @Skylion007 @jgong5 @aditew01 could you please have a look? |
jgong5
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Mar 27, 2026
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Stack from ghstack (oldest at bottom):
OpenBLAS v0.3.31 adds support for BGEMM on SVE128, SVE256 machines
and general optimizations for SBGEMM/BGEMM: OpenMathLib/OpenBLAS#5419, OpenMathLib/OpenBLAS#5399 ... among other things.
OpenBLAS v0.3.32 accelerates SBGEMM/BGEMM on SVE128 machines by ~20% through OpenMathLib/OpenBLAS#5667.
This accelerates SDPA, and will be capitalized on by #172945 further to accelerate linear,mm, bmm, etc
Performance
Using this SDPA benchmark, here are the scaled-dot-production-attention speedups achieved with 16 Neoverse-V2 cores:
PS: BGEMM means bf16 x bf16 -> bf16 and SBGEMM means: bf16 x bf16 -> fp32