Performance characteristics of hybrid MPI/OpenMP scientific applications on a large-scale multithreaded BlueGene/Q supercomputer

Abstract

Many/multi-core supercomputers provide a natural programming paradigm for hybrid MPI/OpenMP scientific applications. In this paper, we investigate the performance characteristics of five hybrid MPI/OpenMP scientific applications (two NAS Parallel benchmarks Multi-Zone SP-MZ and BT-MZ, an earthquake simulation PEQdyna, an aerospace application PMLB and a 3D particle-in-cell application GTC) on a large-scale multithreaded BlueGene/Q supercomputer at Argonne National laboratory, and quantify the performance gap resulting from using different number of threads per node. We use performance tools and MPI profile and trace libraries available on the supercomputer to analyze and compare the performance of these hybrid scientific applications with increasing the number OpenMP threads per node, and find that increasing the number of threads to some extent saturates or worsens performance of these hybrid applications. For the strong-scaling hybrid scientific applications such as SP-MZ, BT-MZ, PEQdyna and PLMB, using 32 threads per node results in much better application efficiency than using 64 threads per node, and as increasing the number of threads per node, the FPU percentage decreases, and the MPI percentage (except PMLB) and IPC per core (except BT-MZ) increase. For the weak-scaling hybrid scientific application such as GTC, the performance trend (relative speedup) is very similar with increasing number of threads per node no matter how many nodes (32, 128, 512) are used.