A Non-Speculative Parallelization of Reverse Cuthill-McKee Algorithm for Sparse Matrices Reordering

Abstract

This work presents a new parallel non-speculative implementation of the Unordered Reverse Cuthill-McKee algorithm.Reordering quality (bandwidth reduction) and reordering performance (CPU time) are evaluated in comparison with a serial implementation of the algorithm made available by the state-of-the-art mathematical software library HSL.The bandwidth reductions reached by our parallel RCM were more than 90% for several large matrices out of the ones tested, and the time reordering improvement was up to 57.82%.Speedups higher than 3.0X were achieved with the parallel RCM.The underlying parallelism was supported by the OpenMP framework and three strategies for reducing idle threads were incorporated into the algorithm.