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Exploiting Auto-tuning to Analyze and Improve Performance Portability on Many-Core Architectures

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High Performance Computing (ISC High Performance 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10524))

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Abstract

Performance portability has rapidly become one of the key concerns for application developers targeting modern computer architectures. Although there are various programming models that can offer functional portability when moving application code between different devices, it remains an open research question as to whether it is possible to guarantee some degree of performance portability in these situations. Automatic performance tuning approaches have been shown to be effective tools for removing the burden of code optimization from the developer, but somewhat sidestep the issue of performance portability by enabling an environment where code is repeatedly optimized for each architecture individually.

In this work, we present an in-depth analysis of the performance portability of code that has been highly optimized for specific devices via auto-tuning. We perform this analysis across a wide range of modern, many-core architectures from multiple hardware vendors, examining performance portability both across different vendors and between devices from the same vendor. We then demonstrate how the auto-tuning process can be modified to bring performance portability into the equation, in order to automatically generate a single implementation that achieves high efficiency across many different devices.

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Notes

  1. 1.

    https://github.com/jrprice/jacobi-ocl.

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Acknowledgment

We would like to thank Imagination Technologies for providing funding for this work. We also give thanks to Tom Deakin from the University of Bristol for providing valuable feedback on this paper.

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Authors and Affiliations

  1. Department of Computer Science, University of Bristol, Bristol, UK

    James Price & Simon McIntosh-Smith

Authors
  1. James Price
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  2. Simon McIntosh-Smith
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Correspondence to James Price .

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Editors and Affiliations

  1. Deutsches Klimarechenzentrum (DKRZ), Hamburg, Hamburg, Germany

    Julian M. Kunkel

  2. TITECH, Tokyo, Japan

    Rio Yokota

  3. Department of Computer Science, University of Delaware, Newark, Delaware, USA

    Michela Taufer

  4. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    John Shalf

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Price, J., McIntosh-Smith, S. (2017). Exploiting Auto-tuning to Analyze and Improve Performance Portability on Many-Core Architectures. In: Kunkel, J., Yokota, R., Taufer, M., Shalf, J. (eds) High Performance Computing. ISC High Performance 2017. Lecture Notes in Computer Science(), vol 10524. Springer, Cham. https://doi.org/10.1007/978-3-319-67630-2_38

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  • DOI: https://doi.org/10.1007/978-3-319-67630-2_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67629-6

  • Online ISBN: 978-3-319-67630-2

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