• DocumentCode
    3174492
  • Title

    Static Average Case Analysis Fork-Join Framework Programs Based on MOQA Method

  • Author

    Gao, Ang ; Rea, Kenneth ; Schellekens, Michel

  • Author_Institution
    Dept. of Comput. Sci., Univ. Coll. Cork, Cork, Ireland
  • fYear
    2011
  • fDate
    3-7 April 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    With the advancement of multi-core processors, parallel algorithms especially multithreaded algorithms, are of increasing importance to developers. The requirement for parallel algorithm analysis also increased. In this paper we present a new way to analyze fork-join multithreaded algorithms. Our approach is based on a novel static average case analysis method named MOQA. By extending MOQA theory to a parallel field and using the traceability of the MOQA data structure, we show that multithreaded algorithms which satisfy MOQA theory can be easily analysed. Parallel quick sort is shown as an example for which we derived equations for its work and span, something that cannot be achieved by current tools. Finally we validate our claims by running the parallel program and by comparing the boundary predicted by static analysis with real speedup from the experiment and show that our method is much more accurate than asymptotic analysis.
  • Keywords
    multi-threading; multiprocessing systems; parallel algorithms; program diagnostics; MOQA method; fork-join framework programs; multicore processors; multithreaded algorithms; parallel algorithm analysis; parallel quick sort; static average case analysis; Algorithm design and analysis; Computational modeling; Data structures; Equations; Mathematical model; Measurement; Parallel processing; average-case analysis; efficiency; fork-join; multithreading; span; speedup; work;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel Computing in Electrical Engineering (PARELEC), 2011 6th International Symposium on
  • Conference_Location
    Luton
  • Print_ISBN
    978-1-4577-0078-1
  • Electronic_ISBN
    978-0-7695-4397-0
  • Type

    conf

  • DOI
    10.1109/PARELEC.2011.10
  • Filename
    5770392