• DocumentCode
    1050099
  • Title

    Evolutionary Benchmark Subsetting

  • Author

    Jin, Zhanpeng ; Cheng, Allen C.

  • Author_Institution
    Univ. of Pittsburgh, Pittsburgh, PA
  • Volume
    28
  • Issue
    6
  • fYear
    2008
  • Firstpage
    20
  • Lastpage
    36
  • Abstract
    To improve simulation efficiency and relieve burdened benchmarking efforts, this research proposes a survival-of-the-fittest evolutionary methodology. The goal is to subset any given benchmark suite based on its inherent workload characteristics, desired workload space coverage, and total execution time. Given a user-specified workload space coverage threshold, the proposed technique can systematically yield the "fittest" time-efficient benchmark subset.
  • Keywords
    benchmark testing; computer architecture; evolutionary computation; benchmark suite; evolutionary benchmark subsetting; fittest time-efficient benchmark subset; survival-of-the-fittest evolutionary; user-specified workload space coverage threshold; Biological information theory; Biological system modeling; Computational modeling; Energy consumption; Microarchitecture; Process design; Time factors;
  • fLanguage
    English
  • Journal_Title
    Micro, IEEE
  • Publisher
    ieee
  • ISSN
    0272-1732
  • Type

    jour

  • DOI
    10.1109/MM.2008.87
  • Filename
    4731172