A parallel trace-data interface for scalable performance analysis

  • Authors:

  • Markus Geimer;Felix Wolf;Andreas Knüpfer;Bernd Mohr;Brian J. N. Wylie

  • Affiliations:

  • John von Neumann Institute for Computing, Forschungszentrum Jülich, Jülich, Germany;John von Neumann Institute for Computing, Forschungszentrum Jülich, Jülich, Germany and Department of Computer Science, RWTH Aachen University, Aachen, Germany;Center for Information Services and High Performance Computing, Dresden University of Technology, Dresden, Germany;John von Neumann Institute for Computing, Forschungszentrum Jülich, Jülich, Germany;John von Neumann Institute for Computing, Forschungszentrum Jülich, Jülich, Germany

  • Venue:
  • PARA'06 Proceedings of the 8th international conference on Applied parallel computing: state of the art in scientific computing
  • Year:
  • 2006

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Abstract

Automatic trace analysis is an effective method of identifying complex performance phenomena in parallel applications. To simplify the development of complex trace-analysis algorithms, the earl library interface offers high-level access to individual events contained in a global trace file. However, as the size of parallel systems grows further and the number of processors used by individual applications is continuously raised, the traditional approach of analyzing a single global trace file becomes increasingly constrained by the large number of events. To enable scalable trace analysis, we present a new design of the aforementioned earl interface that accesses multiple local trace files in parallel while offering means to conveniently exchange events between processes. This article describes the modified view of the trace data as well as related programming abstractions provided by the new pearl library interface and discusses its application in performance analysis.