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Improving quantized matmul performance by devectorizing shader. #15274
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/15274
Note: Links to docs will display an error until the docs builds have been completed. ❗ 1 Active SEVsThere are 1 currently active SEVs. If your PR is affected, please view them below: ❌ 8 New Failures, 2 Unrelated FailuresAs of commit b831b18 with merge base 0a1dfb2 ( NEW FAILURES - The following jobs have failed:
FLAKY - The following job failed but was likely due to flakiness present on trunk:
BROKEN TRUNK - The following job failed but was present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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@trivedivivek has exported this pull request. If you are a Meta employee, you can view the originating Diff in D85023829. |
…rch#15274) Summary: This diff improves the performance of quantized matrix multiplication by devectorizing the shader. An example modification is shown below: ```glsl // Before VEC4_T sums[TILE_ROWS][TILE_TXCOLS]; // After T sums[TILE_ROWS * TILE_TXCOLS * 4]; // Before sums[r][${c}] = VEC4_T(0.0); // After for (int j = 0; j < 4; j++) { sums[r * TILE_TXCOLS * 4 + ${c} * 4 + j] = T(0.0); } ``` Differential Revision: D85023829
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Summary: The diff includes minor performance improvements to the quantized matrix multiplication shader. Differential Revision: D84998542
…rch#15274) Summary: This diff improves the performance of quantized matrix multiplication by devectorizing the shader. An example modification is shown below: ```glsl // Before VEC4_T sums[TILE_ROWS][TILE_TXCOLS]; // After T sums[TILE_ROWS * TILE_TXCOLS * 4]; // Before sums[r][${c}] = VEC4_T(0.0); // After for (int j = 0; j < 4; j++) { sums[r * TILE_TXCOLS * 4 + ${c} * 4 + j] = T(0.0); } ``` Differential Revision: D85023829
4913210
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Summary:
This diff improves the performance of quantized matrix multiplication by devectorizing the shader.
An example modification is shown below:
Differential Revision: D85023829