Do you mean A * X where A is sparse and X is dense where the result is dense or X * A where the result is dense?
We have code for A * X that is reasonably efficient. The second case I don't know how to do efficient. > On Jun 11, 2019, at 9:03 AM, Chih-Chuen Lin via petsc-users > <[email protected]> wrote: > > Dear PETSc users, > > I am Ian. I trying to implement a solver which involves a sparse symmetric > matrix A multiplied by a dense matrix X. And because of the nature of the > problem, the bandwidth of the matrix A would be kind of large.For A*X, I am > thinking using reverse Cuthill-Mckee algorithm to reduce the bandwidth. > > Are the following approach reasonable, or do you have a better advice? > > 1. Use MatGetOrdering to get a MATORDERINGRCM ordering, and MatPermute to > create a new with it. > > 2. What’s the difference by using MATAIJ and MATBAIJ in terms of the entry > insertion and computation and MPI efficiency for a sparse-dense matrix > multiplication? Would it be better to use MATSBAIJ in terms of the > computational efficiency? > > Thanks, > Ian
