Parallel sparse matrix vector multiply software for matrices with data locality

In this paper we describe general software utilities for performing unstructured sparse matrix-vector multiplications on distributed-memory message-passing computers. The matrix-vector multiply comprises an important kernel in the solution of large sparse linear systems by iterative methods. Our focus is to present the data structures and communication parameters necessary for these utilities for general sparse unstructured matrices with data locality. These type of matrices are commonly produced by finite difference and finite element approximations to systems of partial differential equations. In this discussion we also present representative examples and timings which demonstrate the utility and performance of the software.