High performance computing using MPI and OpenMP on multi-core parallel systems

  • Authors:

  • Haoqiang Jin;Dennis Jespersen;Piyush Mehrotra;Rupak Biswas;Lei Huang;Barbara Chapman

  • Affiliations:

  • NAS Division, NASA Ames Research Center, Moffett Field, CA 94035, United States;NAS Division, NASA Ames Research Center, Moffett Field, CA 94035, United States;NAS Division, NASA Ames Research Center, Moffett Field, CA 94035, United States;NAS Division, NASA Ames Research Center, Moffett Field, CA 94035, United States;Department of Computer Sciences, University of Houston, Houston, TX 77004, United States;Department of Computer Sciences, University of Houston, Houston, TX 77004, United States

  • Venue:
  • Parallel Computing
  • Year:
  • 2011

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Abstract

The rapidly increasing number of cores in modern microprocessors is pushing the current high performance computing (HPC) systems into the petascale and exascale era. The hybrid nature of these systems - distributed memory across nodes and shared memory with non-uniform memory access within each node - poses a challenge to application developers. In this paper, we study a hybrid approach to programming such systems - a combination of two traditional programming models, MPI and OpenMP. We present the performance of standard benchmarks from the multi-zone NAS Parallel Benchmarks and two full applications using this approach on several multi-core based systems including an SGI Altix 4700, an IBM p575+ and an SGI Altix ICE 8200EX. We also present new data locality extensions to OpenMP to better match the hierarchical memory structure of multi-core architectures.