[Kernel] add bfloat16 support for gptq kernel #4781
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@alexm-neuralmagic should we support bfloat16 here the same way as done for gptq_marlin? |
The bfloat16 gptq kernel have serious performance issue now, I may optimize it recently. |
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Some models would overflow when using fp16 inference (e.g. Deepseek-V2), so we should add bfloat16 support for quantization kernel. This PR add bfloat16 support for gptq kernel.
Related issue: #2149
main changes:
NOTE: Currently, bfloat16 kernel may be much slower than float16 on
>=sm80,<sm90device since the support foratomicAddwith bfloat16 is not native (see description ofatomicAdd). Increase the value ofBLOCK_KN_SIZEcan much improve the performance, but I don't sure if this will affect other situations.