• DocumentCode
    2503388
  • Title

    A Performance Model of the Krak Hydrodynamics Application

  • Author

    Barker, Kevin J. ; Pakin, Scott ; Kerbyson, Darren J.

  • Author_Institution
    Comput. & Comput. Sci., Los Alamos Nat. Lab., Los Almos, NM
  • fYear
    2006
  • fDate
    14-18 Aug. 2006
  • Firstpage
    245
  • Lastpage
    254
  • Abstract
    We present an analytic performance model of a large-scale hydrodynamics code developed at Los Alamos National Laboratory. This modeling work is part of an ongoing effort to develop models and modeling techniques for large-scale codes and systems of interest to Los Alamos and the national laboratory community (Kerbyson et al., 2001). Krak (Burton, 1994) comprises over 270,000 lines of source code and is capable of executing on a large number of parallel processors. Developing an accurate model is complicated by the irregular partitioning of input spatial grid cells to processors and the various material properties assigned to each cell. Model development proceeds by separating inter-processor communication from computation and modeling each individually. In addition, several approximations concerning subgrid size, shape, and material composition are made which reduce modeling complexity without adversely impacting prediction accuracy. We validate our model on several spatial grid sizes and processor configurations and demonstrate an accuracy at the largest scale on 512 processors to within a 3% error
  • Keywords
    grid computing; hydrodynamics; parallel processing; physics computing; Krak hydrodynamics application; analytic performance model; interprocessor communication; large-scale hydrodynamics code; model development; modeling complexity; parallel processor; processor configuration; spatial grid cells; Accuracy; Composite materials; Computational modeling; Hydrodynamics; Laboratories; Large-scale systems; Material properties; Performance analysis; Predictive models; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel Processing, 2006. ICPP 2006. International Conference on
  • Conference_Location
    Columbus, OH
  • ISSN
    0190-3918
  • Print_ISBN
    0-7695-2636-5
  • Type

    conf

  • DOI
    10.1109/ICPP.2006.11
  • Filename
    1690626