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Supporting Indirect Data Mapping in OpenMP

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OpenMP: Heterogenous Execution and Data Movements (IWOMP 2015)

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

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Abstract

Code-passing abstractions based on lambdas and blocks are becoming increasingly popular to capture repetitive patterns that are amenable to parallelization. These abstractions improve code mantainability and simplify choosing from a range of mechanisms to implement parallelism. Several frameworks that use this model, including RAJA and Kokkos, employ OpenMP as one of their target parallel models. However, OpenMP inadequately supports the abstraction since it frequently requires information that is not available within the abstraction. Thus, OpenMP requires access to variables and parameters not directly supplied by the base language. This paper explores the issues with supporting these abstractions in OpenMP, with a particular focus on device constructs and the aggregation and passing of OpenMP state through base language abstractions. We propose mechanisms to improve support for these abstractions and also to reduce the burden of duplication in existing OpenMP applications.

This material is based upon work supported by the U.S. Department of Energy (LLNL-CONF-671602).

The rights of this work are transferred to the extent transferable according to title 17 §105 U.S.C.

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References

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Author information

Authors and Affiliations

  1. Lawrence Livermore National Laboratory, Livermore, USA

    Thomas R. W. Scogland, Jeff Keasler, John Gyllenhaal, Rich Hornung & Bronis R. de Supinski

  2. Argonne National Laboratory, Lemont, USA

    Hal Finkel

Authors
  1. Thomas R. W. Scogland
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  2. Jeff Keasler
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  3. John Gyllenhaal
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  4. Rich Hornung
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  5. Bronis R. de Supinski
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  6. Hal Finkel
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Corresponding author

Correspondence to Thomas R. W. Scogland .

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 (outside the US)

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Scogland, T.R.W., Keasler, J., Gyllenhaal, J., Hornung, R., de Supinski, B.R., Finkel, H. (2015). Supporting Indirect Data Mapping in OpenMP. 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_19

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  • DOI: https://doi.org/10.1007/978-3-319-24595-9_19

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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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