Performance analysis of a hybrid MPI/OpenMP application on multi-core clusters

The mixing of shared memory and message passing programming models within a single application has often been suggested as a method for improving scientific application performance on clusters of shared memory or multi-core systems. DL_POLY, a large scale molecular dynamics application programmed using message passing programming has been modified to add a layer of shared memory threading and the performance analysed on two multi-core clusters. At lower processor numbers, the extra overheads from shared memory threading in the hybrid code outweigh performance benefits gained over the pure MPI code. On larger core counts the hybrid model performs better than pure MPI, with reduced communication time decreasing the overall runtime.

Research highlights▶ Pure MPI faster than hybrid MPI + OpenMP when running on few nodes. ▶ Hybrid MPI + OpenMP outperforms pure MPI on larger numbers of nodes. ▶ Performance differences attributable to communication profile and threading overheads.