TOWARDS A FAST PARALLEL SPARSE MATRIX-VECTOR MULTIPLICATION

ROMAN GEUS, STEFAN RÖLLIN
2000 Parallel Computing  
The sparse matrix-vector product is an important computational kernel that runs ineffectively on many computers with super-scalar RISC processors. In this paper we analyse the performance of the sparse matrix-vector product with symmetric matrices originating from the FEM and describe techniques that lead to a fast implementation. It is shown how these optimisations can be incorporated into an efficient parallel implementation using messagepassing. We conduct numerical experiments on many
more » ... ent machines and show that our optimisations speed up the sparse matrix-vector multiplication substantially.
doi:10.1142/9781848160170_0036 fatcat:o7dm23gijvfljedo4nsmwbjdxy