Decomposing Irregularly Sparse Matrices for Parallel Matrix-Vector Multiplication

In this work we show the de ciencies of the graph model for decomposing sparse matrices for parallel matrix vector multiplica tion Then we propose two hypergraph models which avoid all de cien cies of the graph model The proposed models reduce the decomposition problem to the well known hypergraph partitioning problem widely en countered in circuit partitioning in VLSI We have implemented fast Kernighan Lin based graph and hypergraph partitioning heuristics and used the successful multilevel graph partitioning tool Metis for the ex perimental evaluation of the validity of the proposed hypergraph models We have also developed a multilevel hypergraph partitioning heuristic for experimenting the performance of the multilevel approach on hy pergraph partitioning Experimental results on sparse matrices selected from Harwell Boeing collection and NETLIB suite con rm both the va lidity of our proposed hypergraph models and appropriateness of the multilevel approach to hypergraph partitioning