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Characterizing the Impact of Prefetching on Scientific Application Performance

  • Collin McCurdy
  • Gabriel Marin
  • Jeffrey S. Vetter
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8551)

Abstract

In order to better understand the impact of hardware and software data prefetching on scientific application performance, this paper introduces two analysis techniques, one micro-architecture-centric and the other application-centric. We use these techniques to analyze representative full-scale production applications from five important Exascale target areas. We find that despite a great diversity in prefetching effectiveness across and even within applications, there is a strong correlation between regions where prefetching is most needed, due to high levels of memory traffic, and where it is most effective. We also observe that the application-centric analysis can explain many of the differences in prefetching effectiveness observed across the studied applications.

Keywords

Performance evaluation Data streaming Prefetching 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Collin McCurdy
    • 1
  • Gabriel Marin
    • 2
  • Jeffrey S. Vetter
    • 1
    • 3
  1. 1.Oak Ridge National LaboratoryOak RidgeUSA
  2. 2.University of TennesseeKnoxvilleUSA
  3. 3.Georgia Institute of TechnologyAtlantaUSA

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