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Early Experiences with the OpenMP Accelerator Model

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OpenMP in the Era of Low Power Devices and Accelerators (IWOMP 2013)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 8122))

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Abstract

A recent trend in mainstream computer nodes is the combined use of general-purpose multicore processors and specialized accelerators such as GPUs and DSPs in order to achieve better performance and to reduce power consumption. To support this trend, the OpenMP Language Committee has approved a set of extensions to OpenMP (referred to as the OpenMP accelerator model). The initial version is the subject of Technical Report 1 (TR1) while OpenMP 4.0 Release Candidate 2 (RC2) further refines the extensions.

In this paper, we examine the newly released accelerator directives and create an initial reference implementation, referred to as HOMP (Heterogeneous OpenMP). Focused on targeting NVIDIA GPUs, our work is based on an existing OpenMP implementation in the ROSE source-to-source compiler infrastructure. HOMP includes extensions to parse the new constructs and to represent them in the AST and other compiler translation details. Further we provide initial runtime support. For our evaluation, we have adapted a few existing OpenMP codes to use the accelerator model directives and present preliminary performance results. Finally, we critique the accelerator model in terms of its impact on developers and compiler writers and suggest possible improvements.

LLNL-CONF-636479. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. This work was also supported by the National Science Foundations Computer Research Infrastructure program under Award No. CNS-1205708.

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Liao, C., Yan, Y., de Supinski, B.R., Quinlan, D.J., Chapman, B. (2013). Early Experiences with the OpenMP Accelerator Model. In: Rendell, A.P., Chapman, B.M., Müller, M.S. (eds) OpenMP in the Era of Low Power Devices and Accelerators. IWOMP 2013. Lecture Notes in Computer Science, vol 8122. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40698-0_7

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  • DOI: https://doi.org/10.1007/978-3-642-40698-0_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40697-3

  • Online ISBN: 978-3-642-40698-0

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