[GitHub] [tvm] masahi commented on pull request #10110: [CUTLASS] Conv2d dgrad

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masahi commented on pull request #10110:
URL: https://github.com/apache/tvm/pull/10110#issuecomment-1026837332


   HUGE UPDATE: Thanks to a tip from @manishucsd and @hwu36, it turns out upgrading the CUDA version from 11.3 to 11.6 alone gives 2x speedup on cutlass strided dgrad (unreal). Moreover, there was a critical bug in the parameter `beta` initialization, which was causing unnecessary memory traffic. That was hurting a lot on batch 256 case. The result was still correct because the `C` tensor, which points to the output pointer, was initialized with zeros.
   
   Here are the updated results after these two fixes:
   
   * [Batch size 8](https://gist.github.com/masahi/90f68803ade90a5900029b128eb59dcf) 
   * [Batch size 256](https://gist.github.com/masahi/a373b06e76e9d228d45ffdddc1cd9f76)
   
   Now, cutlass is winning in ALL but one case in batch size 256, which is still 0.96 vs 0.94 difference. Note that activation fusion is not enabled for dgrad yet. So I expect the cutlass perf to be much better in practice for DL training use cases.  


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