Flash Attention Buffer Compute Shader for Vulkan Backend Delegate #12654
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/12654
Note: Links to docs will display an error until the docs builds have been completed. ❌ 2 New Failures, 3 Pending, 1 Unrelated FailureAs of commit 2144c46 with merge base 154994c ( NEW FAILURES - The following jobs have failed:
FLAKY - The following job failed but was likely due to flakiness present on trunk:
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…torch#12654) Summary: Built flash attention compute shader for Vulkan backend delegate. The current implementation only supports buffer storage and is not fully optimized, but is functional. This shader should speed up the SDPA process in the attention block of transformer inferencing as the previous implementation used many i/o operations. The implementation includes proper multi-query attention support for models like LLaMA, uses tiled block processing to reduce memory usage, and replaces multiple separate operations (matmul, softmax, masking) with a single efficient compute shader. Differential Revision: D78586517
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…torch#12654) Summary: Built flash attention compute shader for Vulkan backend delegate. The current implementation only supports buffer storage and is not fully optimized, but is functional. This shader should speed up the SDPA process in the attention block of transformer inferencing as the previous implementation used many i/o operations. The implementation includes proper multi-query attention support for models like LLaMA, uses tiled block processing to reduce memory usage, and replaces multiple separate operations (matmul, softmax, masking) with a single efficient compute shader. Differential Revision: D78586517
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This pull request was exported from Phabricator. Differential Revision: D78586517 |
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…torch#12654) Summary: Pull Request resolved: pytorch#12654 Built flash attention compute shader for Vulkan backend delegate. The current implementation only supports buffer storage and is not fully optimized, but is functional. This shader should speed up the SDPA process in the attention block of transformer inferencing as the previous implementation used many i/o operations. The implementation includes proper multi-query attention support for models like LLaMA, uses tiled block processing to reduce memory usage, and replaces multiple separate operations (matmul, softmax, masking) with a single efficient compute shader. Differential Revision: D78586517
leafs1
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…torch#12654) Summary: Built flash attention compute shader for Vulkan backend delegate. The current implementation only supports buffer storage and is not fully optimized, but is functional. This shader should speed up the SDPA process in the attention block of transformer inferencing as the previous implementation used many i/o operations. The implementation includes proper multi-query attention support for models like LLaMA, uses tiled block processing to reduce memory usage, and replaces multiple separate operations (matmul, softmax, masking) with a single efficient compute shader. Differential Revision: D78586517
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This pull request was exported from Phabricator. Differential Revision: D78586517 |
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…torch#12654) Summary: Pull Request resolved: pytorch#12654 Built flash attention compute shader for Vulkan backend delegate. The current implementation only supports buffer storage and is not fully optimized, but is functional. This shader should speed up the SDPA process in the attention block of transformer inferencing as the previous implementation used many i/o operations. The implementation includes proper multi-query attention support for models like LLaMA, uses tiled block processing to reduce memory usage, and replaces multiple separate operations (matmul, softmax, masking) with a single efficient compute shader. Differential Revision: D78586517
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This pull request was exported from Phabricator. Differential Revision: D78586517 |
leafs1
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Jul 21, 2025
…torch#12654) Summary: Pull Request resolved: pytorch#12654 Built flash attention compute shader for Vulkan backend delegate. The current implementation only supports buffer storage and is not fully optimized, but is functional. This shader should speed up the SDPA process in the attention block of transformer inferencing as the previous implementation used many i/o operations. The implementation includes proper multi-query attention support for models like LLaMA, uses tiled block processing to reduce memory usage, and replaces multiple separate operations (matmul, softmax, masking) with a single efficient compute shader. Differential Revision: D78586517
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…torch#12654) Summary: Built flash attention compute shader for Vulkan backend delegate. The current implementation only supports buffer storage and is not fully optimized, but is functional. This shader should speed up the SDPA process in the attention block of transformer inferencing as the previous implementation used many i/o operations. The implementation includes proper multi-query attention support for models like LLaMA, uses tiled block processing to reduce memory usage, and replaces multiple separate operations (matmul, softmax, masking) with a single efficient compute shader. Reviewed By: SS-JIA Differential Revision: D78586517
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This pull request was exported from Phabricator. Differential Revision: D78586517 |
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…torch#12654) Summary: Built flash attention compute shader for Vulkan backend delegate. The current implementation only supports buffer storage and is not fully optimized, but is functional. This shader should speed up the SDPA process in the attention block of transformer inferencing as the previous implementation used many i/o operations. The implementation includes proper multi-query attention support for models like LLaMA, uses tiled block processing to reduce memory usage, and replaces multiple separate operations (matmul, softmax, masking) with a single efficient compute shader. Reviewed By: SS-JIA Differential Revision: D78586517
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This pull request was exported from Phabricator. Differential Revision: D78586517 |
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Jul 25, 2025
…torch#12654) Summary: Built flash attention compute shader for Vulkan backend delegate. The current implementation only supports buffer storage and is not fully optimized, but is functional. This shader should speed up the SDPA process in the attention block of transformer inferencing as the previous implementation used many i/o operations. The implementation includes proper multi-query attention support for models like LLaMA, uses tiled block processing to reduce memory usage, and replaces multiple separate operations (matmul, softmax, masking) with a single efficient compute shader. Differential Revision: D78586517 cc @SS-JIA @manuelcandales @cbilgin
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Summary: Built flash attention compute shader for Vulkan backend delegate. The current implementation only supports buffer storage and is not fully optimized, but is functional. This shader should speed up the SDPA process in the attention block of transformer inferencing as the previous implementation used many i/o operations. The implementation includes proper multi-query attention support for models like LLaMA, uses tiled block processing to reduce memory usage, and replaces multiple separate operations (matmul, softmax, masking) with a single efficient compute shader.
Differential Revision: D78586517
cc @SS-JIA @manuelcandales @cbilgin