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Validation of Hardware Events for Successful Performance Pattern Identification in High Performance Computing

In: Tools for High Performance Computing 2015

Author

Listed:
  • Thomas Röhl

    (University of Erlangen-Nuremberg, Erlangen Regional Computing Center (RRZE))

  • Jan Eitzinger

    (University of Erlangen-Nuremberg, Erlangen Regional Computing Center (RRZE))

  • Georg Hager

    (University of Erlangen-Nuremberg, Erlangen Regional Computing Center (RRZE))

  • Gerhard Wellein

    (University of Erlangen-Nuremberg, Erlangen Regional Computing Center (RRZE))

Abstract

Hardware performance monitoring (HPM) is a crucial ingredient of performance analysis tools. While there are interfaces like LIKWID, PAPI or the kernel interface perf_event which provide HPM access with some additional features, many higher level tools combine event counts with results retrieved from other sources like function call traces to derive (semi-)automatic performance advice. However, although HPM is available for x86 systems since the early 90s, only a small subset of the HPM features is used in practice. Performance patterns provide a more comprehensive approach, enabling the identification of various performance-limiting effects. Patterns address issues like bandwidth saturation, load imbalance, non-local data access in ccNUMA systems, or false sharing of cache lines. This work defines HPM event sets that are best suited to identify a selection of performance patterns on the Intel Haswell processor. We validate the chosen event sets for accuracy in order to arrive at a reliable pattern detection mechanism and point out shortcomings that cannot be easily circumvented due to bugs or limitations in the hardware.

Suggested Citation

  • Thomas Röhl & Jan Eitzinger & Georg Hager & Gerhard Wellein, 2016. "Validation of Hardware Events for Successful Performance Pattern Identification in High Performance Computing," Springer Books, in: Andreas Knüpfer & Tobias Hilbrich & Christoph Niethammer & José Gracia & Wolfgang E. Nagel & Michael (ed.), Tools for High Performance Computing 2015, chapter 0, pages 17-28, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-39589-0_2
    DOI: 10.1007/978-3-319-39589-0_2
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