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I was curious what is the good way to store the best kernel implementation for GEMM after running the profiler, so I can port that to different use case / benchmarks? For example, link that to pytorch ...
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cutlass_profiler --operation=grouped_gemm --m=4096 --n=1024 --k=4096 --num_groups=28 --A=fe4m3:row --B=fe4m3:column the kernel listed in the "operation" column of the results does not include the ...