• DocumentCode
    983447
  • Title

    Benchmark evaluation of the IBM SP2 for parallel signal processing

  • Author

    Hwang, Kai ; Xu, Zhiwei ; Arakawa, Masahiro

  • Author_Institution
    Dept. of Comput. Sci., Hong Kong Univ., Hong Kong
  • Volume
    7
  • Issue
    5
  • fYear
    1996
  • fDate
    5/1/1996 12:00:00 AM
  • Firstpage
    522
  • Lastpage
    536
  • Abstract
    This paper evaluates the IBM SP2 architecture, the AIX parallel programming environment, and the IBM message-passing library (MPL) through STAP (Space-Time Adaptive Processing) benchmark experiments. Only coarse-grain parallelism was exploited on the SP2 due to its high communication overhead. A new parallelization scheme is developed for programming message passing multicomputers. Parallel STAP benchmark structures are illustrated with domain decomposition, efficient mapping of partitioned programs, and optimization of collective communication operations. We measure the SP2 performance in terms of execution time, Gflop/s rate, speedup over a single SP2 node, and overall system utilization. With 256 nodes, the Maul SP2 demonstrated the best performance of 23 Gflop/s in executing the High-Order Post-Doppler program, corresponding to a 34% system utilization. We have conducted a scalability analysis to reveal the performance growth rate as a function of machine size and STAP problem size. Important lessons learned from these parallel processing benchmark experiments are discussed in the context of real-time, adaptive, radar signal processing on massively parallel processors (MPP)
  • Keywords
    distributed memory systems; message passing; parallel architectures; performance evaluation; radar signal processing; real-time systems; AIX parallel programming environment; High-Order Post-Doppler program; IBM SP2 architecture; IBM message-passing library; Space-Time Adaptive Processing benchmark experiments; coarse-grain parallelism; collective communication operations; domain decomposition; massively parallel processors; message passing multicomputers; parallel signal processing; partitioned programs; radar signal processing; scalability analysis; Adaptive signal processing; Libraries; Message passing; Parallel processing; Parallel programming; Performance analysis; Scalability; Signal processing; Time measurement; Velocity measurement;
  • fLanguage
    English
  • Journal_Title
    Parallel and Distributed Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9219
  • Type

    jour

  • DOI
    10.1109/71.503777
  • Filename
    503777