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Add GEMM-based standard SDPA benchmark#18646

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Add GEMM-based standard SDPA benchmark#18646
kimishpatel wants to merge 2 commits intogh/kimishpatel/219/basefrom
gh/kimishpatel/219/head

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@kimishpatel kimishpatel commented Apr 1, 2026

Stack from ghstack (oldest at bottom):

Add bench_sdpa.cpp with a standalone GEMM-based SDPA implementation
(run_standard_sdpa) alongside ExecuTorch's tiled flash attention
(custom_sdpa_out) for comparative benchmarking.

The standalone SDPA uses full GEMM per head with 3-pass softmax and
supports both [B,S,H,D] and [B,H,S,D] layouts via BLAS leading
dimension parameters, allowing isolation of algorithm vs layout effects.

Includes validation tests that verify the GEMM-based implementation
matches custom_sdpa_out within tolerance.

Differential Revision: D96044313

Add bench_sdpa.cpp with a standalone GEMM-based SDPA implementation
(run_standard_sdpa) alongside ExecuTorch's tiled flash attention
(custom_sdpa_out) for comparative benchmarking.

The standalone SDPA uses full GEMM per head with 3-pass softmax and
supports both [B,S,H,D] and [B,H,S,D] layouts via BLAS leading
dimension parameters, allowing isolation of algorithm vs layout effects.

Includes validation tests that verify the GEMM-based implementation
matches custom_sdpa_out within tolerance.

Differential Revision: [D96044313](https://our.internmc.facebook.com/intern/diff/D96044313/)

[ghstack-poisoned]
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pytorch-bot bot commented Apr 1, 2026

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/18646

Note: Links to docs will display an error until the docs builds have been completed.

❌ 1 New Failure, 2 Cancelled Jobs

As of commit 5cbe9f5 with merge base fb1618e (image):

NEW FAILURE - The following job has failed:

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Review automatically exported from Phabricator review in Meta.

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github-actions bot commented Apr 1, 2026

This PR needs a release notes: label

If your change should be included in the release notes (i.e. would users of this library care about this change?), please use a label starting with release notes:. This helps us keep track and include your important work in the next release notes.

To add a label, you can comment to pytorchbot, for example
@pytorchbot label "release notes: none"

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Add bench_sdpa.cpp with a standalone GEMM-based SDPA implementation
(run_standard_sdpa) alongside ExecuTorch's tiled flash attention
(custom_sdpa_out) for comparative benchmarking.

The standalone SDPA uses full GEMM per head with 3-pass softmax and
supports both [B,S,H,D] and [B,H,S,D] layouts via BLAS leading
dimension parameters, allowing isolation of algorithm vs layout effects.

Includes validation tests that verify the GEMM-based implementation
matches custom_sdpa_out within tolerance.

Differential Revision: [D96044313](https://our.internmc.facebook.com/intern/diff/D96044313/)

[ghstack-poisoned]
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