• DocumentCode
    2243843
  • Title

    Acceleration of a High Order Accurate Method for Compressible Flows on SDSM Based GPU Clusters

  • Author

    Karantasis, Konstantinos I. ; Polychronopoulos, Eleftherios D. ; Ekaterinaris, John A.

  • Author_Institution
    High Performance Infomation Syst. Lab., Univ. of Patras, Rio, Greece
  • fYear
    2010
  • fDate
    8-10 Dec. 2010
  • Firstpage
    460
  • Lastpage
    467
  • Abstract
    The recent advent of multicore processors, and especially the introduction of many-core GPUs, opens new horizons to large-scale, high-resolution, simulations for a broad range of scientific fields. Among them, the scientific area of CFD appears to be one of the candidates that could significantly benefit from the utilization of many-core GPUs. In o rder to investigate such a potential, we evaluate the performance of a high-order accurate method for the simulation of compressible flows. Current implementation is taking place on a GPU cluster. Nevertheless, a novel approach is followed concerning the utilization of GPU clusters that does not involve explicit message passing. Instead, the presented implementation resides on Software Distributed Shared Memory (SDSM) to propagate changes across the simulation phases. The first results prove to be emboldening and lay grounds for further research along the use of shared memory abstraction in order to utilize future GPU clusters.
  • Keywords
    compressible flow; computational fluid dynamics; computer graphic equipment; distributed shared memory systems; flow simulation; message passing; CFD; SDSM based GPU clusters; compressible flow simulation; high-order accurate method; large-scale high-resolution simulation; many-core GPU; message passing; multicore processor; shared memory abstraction; software distributed shared memory; CUDA; GPU Clusters; OpenMP; SDSM; WENO;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Systems (ICPADS), 2010 IEEE 16th International Conference on
  • Conference_Location
    Shanghai
  • ISSN
    1521-9097
  • Print_ISBN
    978-1-4244-9727-0
  • Electronic_ISBN
    1521-9097
  • Type

    conf

  • DOI
    10.1109/ICPADS.2010.107
  • Filename
    5695636