[GitHub] [incubator-tvm] Huyuwei commented on issue #4369: [Runtime] Add cusparse for sparse dense

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Huyuwei commented on issue #4369: [Runtime] Add cusparse for sparse dense
URL: https://github.com/apache/incubator-tvm/pull/4369#issuecomment-556551928
 
 
   Hi @cylinbao, thanks for the work! This PR uses cusparse csrmm routine. There is another routine csrmm2 which should be faster. According to its document [here](https://docs.nvidia.com/cuda/cusparse/index.html#csrmm2): “If op(B)=B, csrmm2() is the same as csrmm(); The motivation of transpose(B) is to improve the memory access of matrix B. The computational pattern of A * transpose(B) with matrix B in column-major order is equivalent to A * B with matrix B in row-major order.”
   
   I have done some benchmarking on reddit graph and csrmm2 with B transposed is 4x faster than not transposed.
   
   feature length   | csrmm2 with dense matrix not transposed, time in ms    | csrmm2 with dense matrix transposed, time in ms
   :--    | :--   | :--
   32 | 55.85 | 12.26
   64 | 111.51 | 25.16
   128 | 222.94 | 51.62
   256 | 445.66 | 104.77
   512 | 891.34 | 209.62
   
   

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