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[GH-ISSUE #171] Support grouped gemm bf16 tn/nn contiguous? #97

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opened 2026-10-26 21:12:31 +00:00 by bsakaguchi · 1 comment
bsakaguchi commented 2026-10-26 21:12:31 +00:00
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Originally created by @zfan2356 on GitHub (Aug 26, 2025).
Original GitHub issue: https://github.com/deepseek-ai/DeepGEMM/issues/171

Hello！Is there any current plans to support m_grouped_bf16_gemm_tn_contiguous and m_grouped_bf16_gemm_nn_contiguous in the near future. Thank you very much for your time and consideration.

If there are no current plans for this, I would be happy to contribute to the implementation.

Originally created by @zfan2356 on GitHub (Aug 26, 2025). Original GitHub issue: https://github.com/deepseek-ai/DeepGEMM/issues/171 Hello！Is there any current plans to support `m_grouped_bf16_gemm_tn_contiguous` and `m_grouped_bf16_gemm_nn_contiguous` in the near future. Thank you very much for your time and consideration. If there are no current plans for this, I would be happy to contribute to the implementation.
bsakaguchi commented 2026-10-26 21:12:32 +00:00
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@LyricZhao commented on GitHub (Aug 27, 2025):

Hi, we don't have such plans, such internally all BF16 training runs on A100 (another set of kernels, not DeepGEMM). Contribution is welcome! But I suggest you contribute after we push the BF16 (non-grouped, normal GEMMs) NT/TN/TT supports. Thanks!

<!-- gh-comment-id:3226419224 --> @LyricZhao commented on GitHub (Aug 27, 2025): Hi, we don't have such plans, such internally all BF16 training runs on A100 (another set of kernels, not DeepGEMM). Contribution is welcome! But I suggest you contribute after we push the BF16 (non-grouped, normal GEMMs) NT/TN/TT supports. Thanks!
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