• DocumentCode
    762348
  • Title

    Measuring High-Performance Computing with Real Applications

  • Author

    Sayeed, Mohamed ; Bae, Hansang ; Zheng, Yili ; Armstrong, Brian ; Eigenmann, Rudolf ; Saied, Faisal

  • Author_Institution
    Purdue Univ., West Lafayette, IN
  • Volume
    10
  • Issue
    4
  • fYear
    2008
  • Firstpage
    60
  • Lastpage
    70
  • Abstract
    A good benchmarking methodology can save a tremendous amount of resources in terms of human effort, machine cycles, and cost. Such a methodology must consider the relevance and openness of the chosen codes, well-defined rules for executing and reporting the benchmarks, a review process to enforce the rules, and a public repository for the obtained information. For the methodology to be feasible, it must also be supported by adequate tools that enable the user to consistently execute the benchmarks and gather the requisite metrics. At the very least, reliable benchmarking results can help people make decisions about HPC acquisitions and assist scientists and engineers in system advances. By saving resources and enabling balanced designs and configurations, realistic benchmarking ultimately leads to increased competitiveness in both industry and academia.
  • Keywords
    benchmark testing; parallel processing; resource allocation; software metrics; software performance evaluation; benchmarking methodology; high-performance computing application measurement; resource saving; software metrics; Application software; Code standards; Computer applications; High performance computing; Kernel; Performance evaluation; Supercomputers; Testing; Weather forecasting; World Wide Web; high-performance computing; kernel benchmarks; performance analysis; performance evaluation; performance modeling; real application benchmarks;
  • fLanguage
    English
  • Journal_Title
    Computing in Science & Engineering
  • Publisher
    ieee
  • ISSN
    1521-9615
  • Type

    jour

  • DOI
    10.1109/MCSE.2008.98
  • Filename
    4548205