Use a single warp per element instead of a single block per element if the K-dimension is small#13
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…f the K-dimension is small With tensor parallelism, the K-dimension of the FFN-down matrices is split, which makes it quite small, especially for MOEs. For example, Qwen3-30b-A3B has a K-dimension of 768, and Qwen3235B-A22B has k-dimension of 1536. The current heuristic uses a group of 4 warps irrespective of K-dimension size, resulting in some of the threads being idle. This results in poor performance for these matrices. This change uses a single warp for inner dot product and increases the number of output elements per block instead.
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Closing this PR, will file one on master. |
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With tensor parallelism, the K-dimension of the FFN-down matrices is split, which makes it quite small, especially for MOEs. For example, Qwen3-30b-A3B has a K-dimension of 768, and Qwen3235B-A22B has a k-dimension of 1536.
The current heuristic uses a group of 4 warps irrespective of K-dimension size, resulting in some of the threads being idle. This results in poor performance for these matrices.
This change uses a single warp for inner dot product and increases the number of output elements per block instead.
For Qwen3235B-A22B FFN-down GEMV kernel, it shows an improvement of 1.7x (18.88 microseconds to 11.088 microseconds).