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Leveraging Multicore Cluster Nodes by Adding OpenMP to Flow Solvers Parallelized with MPI

  • Christian Iwainsky
  • Samuel Sarholz
  • Dieter an Mey
  • Ralph Altenfeld
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5976)

Abstract

MPI is the predominant model for parallel programming in technical high performance computing. With an increasing number of cores and threads in cluster nodes the question arises whether pure MPI is an appropriate approach to utilize today’s compute clusters or if it is profitable to add another layer of parallelism within the nodes by applying OpenMP on a lower level. Investing a limited amount of manpower, we add OpenMP directives to three MPI production codes and compare and analyze the performance varying the number of MPI processes per node and the number of OpenMP threads per MPI process on current CMP/CMT architectures.

Keywords

Parallel Region Thread Level Parallelization Good Runtime OpenMP Thread OpenMP Implementation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    OpenMP Architecture Review Board: OpenMP application program interface (May 2008), http://www.openmp.org/mp-documents/spec30.pdf
  2. 2.
    Behr, M., Arora, D., Benedict, N.A., O’Neill, J.J.: Intel compilers on linux clusters. Intel Developer Services online publication (October 2002)Google Scholar
  3. 3.
    Rieber, M.: Numerische modellierung der dynamik freier grenzflächen in zweiphasenströmungen. In: Fortschritt-Berichte VDI: Reihe 7, Strömungstechnik 459 (2004)Google Scholar
  4. 4.
    Zeng, P., Sarholz, S., Iwainsky, C., Binninger, B., Peters, N., Herrmann, M.: Simulation of primary breakup for diesel spray with phase transition. In: Ropo, M., Westerholm, J., Dongarra, J. (eds.) EuroPVM/MPI 2009. LNCS, vol. 5759, pp. 313–320. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  5. 5.
    Ham, F., Mattsson, K., Iccarino, G.: Accurate and stable finite volume operators for unstructured flow solvers (2006)Google Scholar
  6. 6.
    Lin, Y., Terboven, C., an Mey, D., Copty, N.: Automatic Scoping of Variables in Parallel Regions of an OpenMP Program. In: Chapman, B.M. (ed.) WOMPAT 2004. LNCS, vol. 3349, pp. 83–97. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  7. 7.
    Rabenseifner, R.: Hybrid parallel programming HPC plattforms. In: Fifth European Workshop on OpenMP, Aachen, Germany (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Christian Iwainsky
    • 1
  • Samuel Sarholz
    • 1
  • Dieter an Mey
    • 1
  • Ralph Altenfeld
    • 1
  1. 1.Center for Computing and CommunicationJARA, RWTH Aachen UniversityAachenGermany

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