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Event Flow Graphs for MPI Performance Monitoring and Analysis

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Tools for High Performance Computing 2015

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Abstract

Classical performance analysis methodologies use either execution traces with fine-grained data or profiles with aggregates. Event traces provide the finest level of detail on application behavior, however, they are infeasible at extreme scales due to the huge amount of information they contain. In contrast, profiles are much more scalable but they lack the temporal order between events. In this paper, we present the use of event flow graphs for performance characterization of MPI applications. Event flow graphs capture statistics on the events performed by the application while preserving the temporal order of such events. Thus, they stand in between tracing and profiling, and are a good complement for classical performance analysis approaches such as event traces or profiles. Furthermore, event flow graphs can be used for means other than visual exploration of performance data. For example, graphs can be utilized as compressed representations of event traces, or to automatically detect the program structure of iterative applications at runtime without any source code analysis.

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Author information

Authors and Affiliations

  1. High Performance Computing and Visualization Department (HPCViz), and Swedish E-Science Research Center (SeRC), KTH Royal Institute of Technology, Lindstedvägen 5, 10044, Stockholm, Sweden

    Xavier Aguilar & Erwin Laure

  2. Computer Science Department, MNM Team, Ludwig-Maximilians-Universität (LMU) Munich, Oettingenstr. 67, 80538, Munich, Germany

    Karl Fürlinger

Authors
  1. Xavier Aguilar
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  2. Karl Fürlinger
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  3. Erwin Laure
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Corresponding author

Correspondence to Xavier Aguilar .

Editor information

Editors and Affiliations

  1. Zentrum für Informationsdienste und Hochleistungsrechnen (ZIH), Technische Universität Dresden Zentrum für Informationsdienste, Dresden, Germany

    Andreas Knüpfer

  2. Zentrum für Informationsdienste und Hochleistungsrechnen (ZIH), Technische Universitat Dresden Zentrum Fur Informationsdienste, Dresden, Germany

    Tobias Hilbrich

  3. Höchstleistungszentrum , Stuttgart (HLRS) Universität Stuttgart, Stuttgart, Germany

    Christoph Niethammer

  4. Höchstleistungszentrum Stuttgart (HLRS), Universität Stuttgart Höchstleistungsrechenzentrum, Stuttgart, Baden-Württemberg, Germany

    José Gracia

  5. Zentrum für Informationsdienste und Hochleistungsrechnen (ZIH), Technische Universität Dresden Zentrum für Informationsdienste, Dresden, Germany

    Wolfgang E. Nagel

  6. Höchstleistungszentrum Stuttgart (HLRS), Universität Stuttgart Höchstleistungsrechenzentrum, Stuttgart, Germany

    Michael M. Resch

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© 2016 Springer International Publishing Switzerland

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Aguilar, X., Fürlinger, K., Laure, E. (2016). Event Flow Graphs for MPI Performance Monitoring and Analysis. In: Knüpfer, A., Hilbrich, T., Niethammer, C., Gracia, J., Nagel, W., Resch, M. (eds) Tools for High Performance Computing 2015. Springer, Cham. https://doi.org/10.1007/978-3-319-39589-0_8

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