Hi,
I have a big sparse matrix in CUDA and I need to multiply it by a dense vector; so I am looking for a sparse x dense -> dense operation, possibly using CUDA.
I have been searching for a while, but I can’t find any documentation for sparse x dense -> dense operation; I don’t know the difference between torch.mm 13, torch.spmm, torch.hsmm, torch.sspmm and all the functions detailed here: http://pytorch.org/docs/master/sparse.html#torch.sparse.FloatTensor.hspmm 180
What are these function doing? What function should I use in my situation?