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On the Use of Probabilistic Worst-Case Execution Time Estimation for Parallel Applications in High Performance Systems

Author

Listed:
  • Matteo Fusi

    (Barcelona Supercomputing Center (BSC), Cr. Jordi Girona 31, 08034 Barcelona, Spain)

  • Fabio Mazzocchetti

    (Barcelona Supercomputing Center (BSC), Cr. Jordi Girona 31, 08034 Barcelona, Spain)

  • Albert Farres

    (Barcelona Supercomputing Center (BSC), Cr. Jordi Girona 31, 08034 Barcelona, Spain)

  • Leonidas Kosmidis

    (Barcelona Supercomputing Center (BSC), Cr. Jordi Girona 31, 08034 Barcelona, Spain)

  • Ramon Canal

    (Barcelona Supercomputing Center (BSC), Cr. Jordi Girona 31, 08034 Barcelona, Spain
    Department of Computer Architecture, Facultat d’Informàtica de Barcelona, Universitat Politècnica de Catalunya, Campus Nord UPC, Cr. Jordi Girona 1-3, 08034 Barcelona, Spain)

  • Francisco J. Cazorla

    (Barcelona Supercomputing Center (BSC), Cr. Jordi Girona 31, 08034 Barcelona, Spain)

  • Jaume Abella

    (Barcelona Supercomputing Center (BSC), Cr. Jordi Girona 31, 08034 Barcelona, Spain)

Abstract

Some high performance computing (HPC) applications exhibit increasing real-time requirements, which call for effective means to predict their high execution times distribution. This is a new challenge for HPC applications but a well-known problem for real-time embedded applications where solutions already exist, although they target low-performance systems running single-threaded applications. In this paper, we show how some performance validation and measurement-based practices for real-time execution time prediction can be leveraged in the context of HPC applications on high-performance platforms, thus enabling reliable means to obtain real-time guarantees for those applications. In particular, the proposed methodology uses coordinately techniques that randomly explore potential timing behavior of the application together with Extreme Value Theory (EVT) to predict rare (and high) execution times to, eventually, derive probabilistic Worst-Case Execution Time (pWCET) curves. We demonstrate the effectiveness of this approach for an acoustic wave inversion application used for geophysical exploration.

Suggested Citation

  • Matteo Fusi & Fabio Mazzocchetti & Albert Farres & Leonidas Kosmidis & Ramon Canal & Francisco J. Cazorla & Jaume Abella, 2020. "On the Use of Probabilistic Worst-Case Execution Time Estimation for Parallel Applications in High Performance Systems," Mathematics, MDPI, vol. 8(3), pages 1-21, March.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:3:p:314-:d:326736
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    References listed on IDEAS

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    1. Joan Del Castillo & Jalila Daoudi & Richard Lockhart, 2014. "Methods to Distinguish Between Polynomial and Exponential Tails," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 382-393, June.
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