A non-speculative parallelization of reverse cuthill-McKee algorithm for sparse matrices reordering

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.