• DocumentCode
    451209
  • Title

    Predictive Performance and Scalability Modeling of a Large-Scale Application

  • Author

    Kerbyson, D.J. ; Alme, H.J. ; Hoisie, A. ; Petrini, F. ; Wasserman, H.J. ; Gittings, M.

  • Author_Institution
    Los Alamos National Laboratory
  • fYear
    2001
  • fDate
    10-16 Nov. 2001
  • Firstpage
    39
  • Lastpage
    39
  • Abstract
    In this work we present a predictive analytical model that encompasses the performance and scaling characteristics of an important ASCI application. SAGE (SAIC’s Adaptive Grid Eulerian hydrocode) is a multidimensional hydrodynamics code with adaptive mesh refinement. The model is validated against measurements on several systems including ASCI Blue Mountain, ASCI White, and a Compaq Alphaserver ES45 system showing high accuracy. It is parametric - basic machine performance numbers (latency, MFLOPS rate, bandwidth) and application characteristics (problem size, decomposition method, etc.) serve as input. The model is applied to add insight into the performance of current systems, to reveal bottlenecks, and to illustrate where tuning efforts can be effective. We also use the model to predict performance on future systems.
  • Keywords
    Performance analysis; Teraflop scale computing; full application codes; parallel system architecture; Adaptive mesh refinement; Computer architecture; Government; Hydrodynamics; Laboratories; Large-scale systems; Multidimensional systems; Performance analysis; Predictive models; Scalability; Performance analysis; Teraflop scale computing; full application codes; parallel system architecture;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Supercomputing, ACM/IEEE 2001 Conference
  • Print_ISBN
    1-58113-293-X
  • Type

    conf

  • DOI
    10.1109/SC.2001.10011
  • Filename
    1592815