Refactor 2 awq gemm kernels into m16nXk32#2723
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WoosukKwon merged 3 commits intovllm-project:mainfrom Feb 12, 2024
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zcnrex
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@WoosukKwon could you please help review? |
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@zcnrex Nice job refactoring the GEMM kernels. I am especially excited to see if the dequant + cublas can bring a speedup like we talked about. |
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LGTM! Thanks for the refactoring. Sorry for the late review 🙏
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[ROCm] Fix build problem resulted from previous commit related to FP8 kv-cache support (vllm-project#2790) Add documentation on how to do incremental builds (vllm-project#2796) [Ray] Integration compiled DAG off by default (vllm-project#2471) Disable custom all reduce by default (vllm-project#2808) add usage context removed usage_context from Engine_args Move IO to another process added http request [ROCm] support Radeon™ 7900 series (gfx1100) without using flash-attention (vllm-project#2768) Add documentation section about LoRA (vllm-project#2834) Refactor 2 awq gemm kernels into m16nXk32 (vllm-project#2723) Co-authored-by: Chunan Zeng <chunanzeng@Chunans-Air.attlocal.net> Added additional arg for from_engine_args comments
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Co-authored-by: Chunan Zeng <chunanzeng@Chunans-Air.attlocal.net>
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Merge
gemm_forward_4bit_cuda_m16n64k32andgemm_forward_4bit_cuda_m16n128k32into 1 function, and pass 64/128 as a parameterUsed the diff tool to facilitate identifying numbers to change:
https://www.diffchecker.com/VIc6ukUz/
Next PRs: add cuBlas as an alternative to awq-gemm as discussed in #2566 (comment)