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Visualizing More Performance Data Than What Fits on Your Screen

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Tools for High Performance Computing 2012

Abstract

High performance applications are composed of many processes that are executed in large-scale systems with possibly millions of computing units. A possible way to conduct a performance analysis of such applications is to register in trace files the behavior of all processes belonging to the same application. The large number of processes and the very detailed behavior that we can record about them lead to a trace size explosion both in space and time dimensions. The performance visualization of such data is very challenging because of the quantities involved and the limited screen space available to draw them all. If the amount of data is not properly treated for visualization, the analysis may give the wrong idea about the behavior registered in the traces. This paper is twofold: first, it details data aggregation techniques that are fully configurable by the user to control the level of details in both space and time dimensions; second, it presents two visualization techniques that take advantage of the aggregated data to scale. These features are part of the Viva open-source tool and framework, which is also briefly described in this paper.

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Notes

  1. 1.

    Part of Akypuera toolset, available at https://github.com/schnorr/akypuera

  2. 2.

    Part of PajeNG, available at https://github.com/schnorr/pajeng

  3. 3.

    Available at http://github.com/schnorr/viva/

  4. 4.

    Available at http://github.com/schnorr/pajeng/

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Acknowledgements

This work is partially funded by the french SONGS project (ANR-11-INFRA-13) of the Agence Nationale de la Recherche (ANR). We thank Augustin Degomme for providing the sweep3D MPI traces. We also thank the organizers of the 6th International Parallel Tools Workshop for the invitation.

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Authors and Affiliations

  1. INRIA MESCAL Research Team, CNRS LIG Laboratory, Grenoble, France

    Lucas M. Schnorr & Arnaud Legrand

Authors
  1. Lucas M. Schnorr
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  2. Arnaud Legrand
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Corresponding author

Correspondence to Lucas M. Schnorr .

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Editors and Affiliations

  1. Höchstleistungsrechenzentrum, Stuttgart (HLRS), Universität Stuttgart, Nobelstraße 19, Stuttgart, 70550, Germany

    Alexey Cheptsov

  2. Höchstleistungsrechenzentrum, Stuttgart (HLRS), Universität Stuttgart, Nobelstraße 19, Stuttgart, 70550, Germany

    Steffen Brinkmann

  3. Höchstleistungsrechenzentrum, Stuttgart (HLRS), Universität Stuttgart, Nobelstraße 19, Stuttgart, 70550, Germany

    José Gracia

  4. Höchstleistungsrechenzentrum, Stuttgart (HLRS), Universität Stuttgart, Nobelstrasße 19, Stuttgart, 70550, Germany

    Michael M. Resch

  5. Zentrum für Informationsdienste, und Hochleistungsrechnen (ZIH), Technische Universität Dresden, Helmholtzstr. 10, Dresden, 01062, Germany

    Wolfgang E. Nagel

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Schnorr, L.M., Legrand, A. (2013). Visualizing More Performance Data Than What Fits on Your Screen. In: Cheptsov, A., Brinkmann, S., Gracia, J., Resch, M., Nagel, W. (eds) Tools for High Performance Computing 2012. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37349-7_10

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