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Related Experiment Videos

160-fold acceleration of the Smith-Waterman algorithm using a field programmable gate array (FPGA).

Isaac T S Li1, Warren Shum, Kevin Truong

  • 1Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada. isaac.li@utoronto.ca <isaac.li@utoronto.ca>

BMC Bioinformatics
|June 9, 2007
PubMed
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Accelerating the Smith-Waterman (SW) algorithm using FPGA hardware significantly speeds up genomic database searching. This approach enhances computational efficiency for inferring gene function and homology by up to 160-fold.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • The Smith-Waterman (SW) algorithm is crucial for inferring homology and gene function by finding optimal local sequence alignments.
  • Searching large genomic databases with SW is computationally intensive and time-consuming.

Purpose of the Study:

  • To accelerate the Smith-Waterman algorithm for efficient genomic database searching.
  • To explore the use of FPGA-based hardware for computational improvement.

Main Methods:

  • Implemented a module on FPGA hardware to compute individual cells of the SW matrix.
  • Utilized a grid of these modules to compute the entire SW matrix at high speed.

Main Results:

  • Achieved a dramatic acceleration of the SW algorithm's computation time, up to 160-fold.

Related Experiment Videos

  • Outperformed pure software implementations on the same FPGA platform.

    • Conclusions:

    • FPGA-accelerated hardware presents a promising direction for enhancing genomic database search computations.
    • This approach offers significant computational improvements for bioinformatics tasks.