• DocumentCode
    1828657
  • Title

    Parallel Position Weight Matrices Algorithms

  • Author

    Giraud, Mathieu ; Varré, Jean-Stéphane

  • Author_Institution
    LIFL, Univ. Lille 1, Lille, France
  • fYear
    2009
  • fDate
    June 30 2009-July 4 2009
  • Firstpage
    65
  • Lastpage
    72
  • Abstract
    Position weight matrices (PWMs) are broadly used in computational biology. The basic problem, Scan, aims to find the occurrences of a given PWM in large sequences. Some other PWM tasks share a common NP-hard subproblem, ScoreDistribution. The existing algorithms rely on the enumeration on a large set of scores or words, and they are mostly not suitable for parallelization.We propose a new algorithm, BucketScoreDistribution, that is both very efficient and suitable for parallelization. We bound the error induced by this algorithm. We realized a GPU prototype for Scan and BucketScoreDistribution with the CUDA libraries, and report for the different problems speedups of 21times and 77times on a Nvidia GTX 280.
  • Keywords
    biology computing; computational complexity; matrix algebra; BucketScoreDistribution; NP-hard subproblem; Scan; computational biology; position weight matrices; Biological system modeling; Computational biology; DNA; Databases; Distributed computing; Europe; Libraries; Prototypes; Pulse width modulation; Sequences; Bioinformatics; CUDA; GPU; Position Weight Matrices; Pvalue estimation; many-cores architectures; pattern matching; score distribution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Computing, 2009. ISPDC '09. Eighth International Symposium on
  • Conference_Location
    Lisbon
  • Print_ISBN
    978-0-7695-3680-4
  • Type

    conf

  • DOI
    10.1109/ISPDC.2009.31
  • Filename
    5284371