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A Beginner’s Guide to Estimating and Improving Performance Portability

  • Henk DreuningEmail author
  • Roel Heirman
  • Ana Lucia Varbanescu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11203)

Abstract

Given the increasing diversity of multi- and many-core processors, portability is a desirable feature of applications designed and implemented for such platforms. Portability is unanimously seen as a productivity enabler, but it is also considered a major performance blocker. Thus, performance portability has emerged as the property of an application to preserve similar form and similar performance on a set of platforms; a first metric, based on extensive evaluation, has been proposed to quantify performance portability for a given application on a set of given platforms.

In this work, we explore the challenges and limitations of this performance portability metric (PPM) on two levels. We first use 5 OpenACC applications and 3 platforms, and we demonstrate how to compute and interpret PPM in this context. Our results indicate specific challenges in parameter selection and results interpretation. Second, we use controlled experiments to assess the impact of platform-specific optimizations on both performance and performance portability. Our results illustrate, for our 5 OpenACC applications, a clear tension between performance improvement and performance portability improvement.

Keywords

Performance portability metric Performance optimization OpenACC CPU GPU 

Notes

Acknowledgements

We would like to thank Jason Sewall and John Pennycook for their help in designing our experiments and interpreting the results.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Henk Dreuning
    • 1
    Email author
  • Roel Heirman
    • 1
  • Ana Lucia Varbanescu
    • 1
  1. 1.University of AmsterdamAmsterdamThe Netherlands

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