• DocumentCode
    2452616
  • Title

    Parallel Approaches for SWAMP Sequence Alignment

  • Author

    Steinfadt, Shannon ; Schaffer, Kevin

  • Author_Institution
    Dept. of Comput. Sci., Kent State Univ., Kent, OH, USA
  • fYear
    2009
  • fDate
    15-17 June 2009
  • Firstpage
    87
  • Lastpage
    92
  • Abstract
    This document is a summary and overview of several approaches to implement the local sequence alignment algorithms known as SWAMP and SWAMP+ on commercially available hardware. Using a Smith-Waterman style of alignment, these parallel algorithms have several innovative extensions that take advantage of the ASC associative computing model while maintaining speed, accuracy, and producing a richer set of results in an automated way that is not currently available. We consider four different hardware architectures for the realization of the ASC model. These are the ClearSpeed CSX processor, NVIDIA GPGPU graphics processors, IBM Cell Processors, and FPGAs.
  • Keywords
    bioinformatics; parallel algorithms; ASC model realization; ClearSpeed CSX processor; FPGA; GPGPU graphics processor; IBM cell processor; NVIDIA; SWAMP sequence alignment; SWAMP+; Smith-Waterman style; associative computing; bioinformatics sequence alignment; hardware architecture; local sequence alignment algorithm; parallel algorithm; Bioinformatics; Concurrent computing; Dynamic programming; Field programmable gate arrays; Graphics; Hardware; Heuristic algorithms; Parallel algorithms; Parallel processing; Sequences; Cell Processor; FPGAs; GPGPUs; associative SIMD; parallel computing; sequence alignment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics, 2009. OCCBIO '09. Ohio Collaborative Conference on
  • Conference_Location
    Cleveland, OH
  • Print_ISBN
    978-0-7695-3685-9
  • Type

    conf

  • DOI
    10.1109/OCCBIO.2009.12
  • Filename
    5159168