SMVP Distribution Using Hypergraph Model and S-GBNZ Algorithm

Abstract

Sparse Matrix Vector Product (SMVP) is an important kernel in many scientific applications. Since the most common issues in parallel computing are communication and load balancing, our goal is to find a compromise to satisfy these two criteria. Thus, for distributing this kernel on a homogeneous multicore node cluster, we study a solution where we combine two different approaches: hyper graph model that reduces communication cost and S-GBNZ algorithm that ensures load balancing. Our theoretical contribution is validated through experimentations achieved on a multicore cluster within Grid5000.