sparse matrix multiplication using MKL libraries

Question

I was looking to find a way to perform a symmetric sparse matrix - matrix multiplication: X = A B where the sparse matrix A was previously stored in CSR3 format (upper triangular), while the matrix B is a dense non-symmetric matrix. Is there a routine inside the MKL libraries to do it? or do they all need the full sparse matrix in CSR format (to get the handle from) instead of the triangular one (I built the triangular matrix because I need to use it in MKL Pardiso)? I know about the mkl_sparse_d_mv(...) routine, but I couldn't find a way to get the sparse matrix handle from a symmetric sparse matrix previously stored like an upper triangular matrix in CSR format. thank you in advance, Daniele

Answer 1

Could you try the mkl_sparse_?_mm, where [?] == s,d,c and z data types. This routine performs a matrix-matrix operation:

Y := alpha*op(A)X + betaY where alpha and beta are scalars, A is a sparse matrix, op is a matrix modifier for matrix A, and X and Y are dense matrices.

Answer 2

In most cases you can easily feed a CSR3-stored matrix into sparse_d_create_csr by passing appropriately offset pointers to your row index for pointerB and pointerE.

You can then tell mkl_sparse_d_mm the sparse matrix is triangular and you'd like it to be filled (I have never done this and can't promise that it works).

Answer 3

ok, I can now say the routine needs the full matrix in CSR format, the matrix struct description it will only tells the routine to take one triangle(upper/lower) from the input full CSR matrix, but still it needs it all.