Abstract

In this paper we present PMORSy—a new parallel software package for symmetric sparse matrix ordering on shared memory systems. The NP-complete fill-in minimization problem is solved by means of multilevel nested dissection algorithm with modifications for vertex separators. Parallel processing is done in a task-based fashion with the granularity tuning. We employ threading techniques on shared memory using OpenMP 3.0 technology as opposed to the Message Passing Interface-based approach widely used for parallel sparse matrix ordering. Experimental results on symmetric matrices from the University of Florida Sparse Matrix Collection and matrices from finite-element analysis of three-dimensional strength problems show that our implementation is competitive to the ParMETIS and PT-Scotch libraries both in ordering quality and performance. The PMORSy library is publicly available from the Lobachevsky State University Supercomputing Center web-site.

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