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Off-Road Performance Modeling – How to Deal with Segmented Data

  • M. Kashif IlyasEmail author
  • Alexandru Calotoiu
  • Felix Wolf
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10417)

Abstract

Besides correctness, scalability is one of the top priorities of parallel programmers. With manual analytical performance modeling often being too laborious, developers increasingly resort to empirical performance modeling as a viable alternative, which learns performance models from a limited amount of performance measurements. Although powerful automatic techniques exist for this purpose, they usually struggle with the situation where performance data representing two or more different phenomena are conflated into a single performance model. This not only generates an inaccurate model for the given data, but can also either fail to point out existing scalability issues or create the appearance of such issues when none are present. In this paper, we present an algorithm to detect segmentation in a sequence of performance measurements and estimate the point where the behavior changes. Our method correctly identified segmentation in more than 80% of 5.2 million synthetic tests and confirmed expected segmentation in three application case studies.

Keywords

Parallel computing Performance tools Performance modeling 

Notes

Acknowledgements

This work was supported in part by the German Research Foundation (DFG) through the Priority Programme 1648 Software for Exascale Computing (SPPEXA) and the Programme Performance Engineering for Scientific Software. Additional support was provided by the German Federal Ministry of Education and Research (BMBF) under Grant No. 01IH16008, and by the US Department of Energy under Grant No. DE-SC0015524. Finally, we would like to thank the University Computing Center (Hochschulrechenzentrum) of TU Darmstadt for providing us with access to the Lichtenberg Cluster.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • M. Kashif Ilyas
    • 1
    Email author
  • Alexandru Calotoiu
    • 1
  • Felix Wolf
    • 1
  1. 1.Technische Universität DarmstadtDarmstadtGermany

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