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PERFORMANCE_GUIDE.md

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Spconv 2.x Performance Guide

Short Guide

  • If you train without Tensor Core (i.e. FP32 training), set all algo in convolution/maxpool to ConvAlgo.Native manually. Default Algorithm is ConvAlgo.MaskImplicitGemm, which is SLOWER than ConvAlgo.Native when use float32. this will be fixed in spconv 2.2.
  • If your GPU support Tensor Core, use FP16 (mixed precision training) if possible.
  • If you train with mixed precision training (use Tensor Core), you don't need to set algorithm manually.
  • Currently fast algorithm only support kernel volume (prod of kernel size) <= 32, so don't use large kernel size.
  • make sure your channel size is multiple of 8 when using fp16. multiple of 32 is better.
  • spconv 2.x in Windows 10 is 1.5x~2x slower than Linux. use Linux if possible.

See benchmark for more performance details of different algorithms.