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International Workshop on OpenMP

IWOMP 2015: OpenMP: Heterogenous Execution and Data Movements pp 162–174Cite as

A Case Study of OpenMP Applied to Map/Reduce-Style Computations

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9342))

Abstract

As data analytics are growing in importance they are also quickly becoming one of the dominant application domains that require parallel processing. This paper investigates the applicability of OpenMP, the dominant shared-memory parallel programming model in high-performance computing, to the domain of data analytics. We contrast the performance and programmability of key data analytics benchmarks against Phoenix++, a state-of-the-art shared memory map/reduce programming system. Our study shows that OpenMP outperforms the Phoenix++ system by a large margin for several benchmarks. In other cases, however, the programming model is lacking support for this application domain.

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Acknowledgment

This work is supported by the European Community’s Seventh Framework Programme (FP7/2007–2013) under the ASAP project, grant agreement no. 619706, and by the United Kingdom EPSRC under grant agreement EP/L027402/1.

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Authors and Affiliations

  1. Queen’s University Belfast, Belfast, UK

    Mahwish Arif & Hans Vandierendonck

Authors
  1. Mahwish Arif
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  2. Hans Vandierendonck
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Corresponding author

Correspondence to Mahwish Arif .

Editor information

Editors and Affiliations

  1. RWTH Aachen University, Aachen, Germany

    Christian Terboven

  2. Lawrence Livermore National Laboratory, Livermore, California, USA

    Bronis R. de Supinski

  3. RWTH Aachen University, Aachen, Germany

    Pablo Reble

  4. University of Houston, Houston, California, USA

    Barbara M. Chapman

  5. RWTH Aachen University, Aachen, Germany

    Matthias S. Müller

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© 2015 Springer International Publishing Switzerland

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Arif, M., Vandierendonck, H. (2015). A Case Study of OpenMP Applied to Map/Reduce-Style Computations. In: Terboven, C., de Supinski, B., Reble, P., Chapman, B., Müller, M. (eds) OpenMP: Heterogenous Execution and Data Movements. IWOMP 2015. Lecture Notes in Computer Science(), vol 9342. Springer, Cham. https://doi.org/10.1007/978-3-319-24595-9_12

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  • DOI: https://doi.org/10.1007/978-3-319-24595-9_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24594-2

  • Online ISBN: 978-3-319-24595-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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