• DocumentCode
    381288
  • Title

    Exploring advanced architectures using performance prediction

  • Author

    Kerbyson, Darren J. ; Wasserman, Harvey J. ; Hoisie, Adolfy

  • Author_Institution
    Parallel Architectures & Performance Team, Los Alamos Nat. Lab., NM, USA
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    27
  • Lastpage
    37
  • Abstract
    In this work we show how by the examination of the key characteristics of an application, analytical performance models can be formed. These models are parameterized in terms of computational and communication performances of an individual system and can be used to explore achievable performance of an application prior to system availability. Two applications are considered: an adaptive mesh refinement code on structured meshes, and an Sn transport code on unstructured meshes. These are representative of part of the ASCI workload. One of the models is utilized to validate the performance of a Compaq Alpha-server ES45 supercomputing system being built at Los Alamos, and expected to grow to 30 TFLOPS peak performance in the next year. In addition, the models are used to explore the achievable performance on hypothesized future systems with increased peak computation and communication performance.
  • Keywords
    parallel architectures; parallel machines; performance evaluation; 30 TFLOPS; ASCI workload; Compaq Alpha-server ES45; Sn transport code; adaptive mesh refinement code; advanced architectures; analytical performance models; communication performance; computational performance; performance prediction; structured meshes; supercomputing system; unstructured meshes; Adaptive mesh refinement; Analytical models; Computational modeling; Hardware; Laboratories; Parallel architectures; Performance analysis; Predictive models; Process design; Tin;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Architecture for Future Generation High-Performance Processors and Systems, 2002. International Workshop on
  • ISSN
    1537-3223
  • Print_ISBN
    0-7695-1635-1
  • Type

    conf

  • DOI
    10.1109/IWIA.2002.1035016
  • Filename
    1035016