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Scalable Parallel Trace-Based Performance Analysis

  • Markus Geimer
  • Felix Wolf
  • Brian J. N. Wylie
  • Bernd Mohr
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4192)

Abstract

Automatic trace analysis is an effective method for identifying complex performance phenomena in parallel applications. However, as the size of parallel systems and the number of processors used by individual applications is continuously raised, the traditional approach of analyzing a single global trace file, as done by kojak’s expert trace analyzer, becomes increasingly constrained by the large number of events. In this article, we present a scalable version of the expert analysis based on analyzing separate local trace files with a parallel tool which ‘replays’ the target application’s communication behavior. We describe the new parallel analyzer architecture and discuss first empirical results.

Keywords

Parallel Analysis Parallel Application Target Application Execution Trace Collective Communication 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Markus Geimer
    • 1
  • Felix Wolf
    • 1
  • Brian J. N. Wylie
    • 1
  • Bernd Mohr
    • 1
  1. 1.John von Neumann Institute for Computing (NIC), Forschungszentrum JülichJülichGermany

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