Alignment-Based Metrics for Trace Comparison

  • Matthias Weber
  • Kathryn Mohror
  • Martin Schulz
  • Bronis R. de Supinski
  • Holger Brunst
  • Wolfgang E. Nagel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8097)


Due to the complexity of today’s architectures and applications, performance analysis and optimization are essential, and tracebased techniques have proven to be a powerful approach. However, a manual comparison of traces is difficult and time consuming because of the large volume of detailed data and the need to correctly line up trace events. Our solution is a set of techniques that automatically align traces so they can be compared, along with novel metrics that quantify the differences between traces, both in terms of differences in the event stream and timing differences across events. Further, we introduce visualization techniques that highlight and facilitate understanding of the sources of the differences. We demonstrate the effectiveness of our solution by showing automatically detected performance and code differences across different versions of two real-world applications.


High Performance Computing Alignment Algorithm Event Stream Event Trace Process Pair 
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 2013

Authors and Affiliations

  • Matthias Weber
    • 1
    • 2
  • Kathryn Mohror
    • 2
  • Martin Schulz
    • 2
  • Bronis R. de Supinski
    • 2
  • Holger Brunst
    • 1
  • Wolfgang E. Nagel
    • 1
  1. 1.Center for Information Services and High Performance ComputingTechnische Universität DresdenGermany
  2. 2.Center for Applied Scientific ComputingLawrence Livermore National LaboratoryUSA

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