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Tools for High Performance Computing 2011 pp 13–25Cite as

Using Sampling to Understand Parallel Program Performance

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Abstract

Developing scalable parallel applications for extreme-scale systems is challenging. The challenge of developing scalable parallel applications is only partially addressed by existing languages, compilers, and autotuners. As a result, manual performance tuning is often necessary to obtain high application performance. Rice University’s HPCToolkit is a suite of performance tools that supports innovative techniques for pinpointing and quantifying performance bottlenecks in fully optimized parallel programs with a measurement overhead of only a few percent. Many of these techniques were designed to leverage sampling for performance measurement, attribution, analysis, and presentation. This paper surveys some of HPCToolkit’s most interesting techniques and argues that sampling-based performance analysis is surprisingly versatile and effective.

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Acknowledgements

HPCToolkit would not be what it is without the efforts of Mark Krentel, Laksono Adhianto, and Mike Fagan. Xu Liu developed our data-centric analysis.

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Authors and Affiliations

  1. Pacific Northwest National Laboratory, Richland, WA, 99352, USA

    Nathan R. Tallent

  2. Department of Computer Science, Rice University, Houston, TX, 77005, USA

    John Mellor-Crummey

Authors
  1. Nathan R. Tallent
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  2. John Mellor-Crummey
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Corresponding author

Correspondence to Nathan R. Tallent .

Editor information

Editors and Affiliations

  1. , Zentrum für Informationsdienste, Technische Universität Dresden, Dresden, 01062, Germany

    Holger Brunst

  2. , Zentrum für Informationsdienste, Technische Universität Dresden, Dresden, 01062, Germany

    Matthias S. Müller

  3. , Zentrum für Informationsdienste, Technische Universität Dresden, Dresden, 01062, Germany

    Wolfgang E. Nagel

  4. , Höchstleistungsrechenzentrum, Universität Stuttgart, Nobelstraße 19, Stuttgart, 70569, Germany

    Michael M. Resch

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Tallent, N.R., Mellor-Crummey, J. (2012). Using Sampling to Understand Parallel Program Performance. In: Brunst, H., Müller, M., Nagel, W., Resch, M. (eds) Tools for High Performance Computing 2011. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31476-6_2

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  • DOI: https://doi.org/10.1007/978-3-642-31476-6_2

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31475-9

  • Online ISBN: 978-3-642-31476-6

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