What is the API for writing a custom (Elementwise or Raw) kernel that works on cuSPARSE instances in CuPy? If I want to write a kernel that can take cupyx.scipy.sparse.csr_matrix instances as argument, what arguments does the underlying CUDA code need to take?
Found it (at least approximately). For a CSR sparse matrix s, the fields s.data, s.indices, and s.indptr contain a dense array of length s.nnz of nonzero entries, a dense array of length s.nnz of column indices, and a list of locations (relative addresses) of the beginnings of each row in indices respectively. These are all normal cupy.ndarrays and can be passed into a kernel and then to cuSPARSE functions as normal.