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Representative Sampling Using SimPoint

  • Greg Hamerly
  • Erez Perelman
  • Timothy Sherwood
  • Brad Calder
Chapter

Abstract

SimPoint is a technique used to pick what parts of the program’s execution to simulate in order to have a complete picture of execution. SimPoint uses data clustering algorithms from machine learning to automatically find repetitive (similar) patterns in a program’s execution, and it chooses one sample to represent each unique repetitive behavior. Each sample is then simulated and weighted appropriately, and then together the results from these samples represent an accurate picture of the complete execution of the program.

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Copyright information

© Springer Science+business Media, LLC 2010

Authors and Affiliations

  • Greg Hamerly
    • 1
  • Erez Perelman
    • 2
  • Timothy Sherwood
    • 3
  • Brad Calder
    • 4
  1. 1.Baylor UniversityWacoUSA
  2. 2.IntelCupertinoUSA
  3. 3.University of CaliforniaSanta BarbaraUSA
  4. 4.MicrosoftBellevueUSA

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