• DocumentCode
    236555
  • Title

    Power Profiling of a Reduced Data Movement Algorithm for Neutron Cross Section Data in Monte Carlo Simulations

  • Author

    Tramm, John R. ; Yoshii, Kazutomo ; Siegel, Andrew R.

  • Author_Institution
    Math. & Comput. Sci. Div, Argonne Nat. Lab., Argonne, IL, USA
  • fYear
    2014
  • fDate
    17-17 Nov. 2014
  • Firstpage
    17
  • Lastpage
    24
  • Abstract
    Current Monte Carlo neutron transport applications use continuous energy cross section data to provide the statistical foundation for particle trajectories. This "classical" algorithm requires storage and random access of very large data structures. Recently, Forget et al.[1] reported on a fundamentally new approach, based on multipole expansions, that distills cross section data down to a more abstract mathematical format. Their formulation greatly reduces memory storage and improves data locality at the cost of also increasing floating point computation. In the present study we determine the hardware performance parameters, including power usage, of the multipole algorithm relative to the classical continuous energy algorithm. This study is done to guage the suitability of both algorithms for use on next-generation high performance computing platforms.
  • Keywords
    Monte Carlo methods; parallel processing; performance evaluation; power aware computing; statistical analysis; Monte Carlo neutron transport applications; Monte Carlo simulations; continuous energy algorithm; continuous energy cross section data; floating point computation; hardware performance parameters; memory storage; multipole expansions; neutron cross section data; next-generation high performance computing platforms; particle trajectories; power profiling; reduced data movement algorithm; statistical foundation; very large data structures; Algorithm design and analysis; Computational modeling; Data structures; Inductors; Materials; Microscopy; Neutrons;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Hardware-Software Co-Design for High Performance Computing (Co-HPC), 2014
  • Conference_Location
    New Orleans, LA
  • Type

    conf

  • DOI
    10.1109/Co-HPC.2014.9
  • Filename
    7017959