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Hardware accelerator for genomic sequence alignment.

Jason Chiang1, Michael Studniberg, Jack Shaw

  • 1Dept. of Electr. & Comput. Eng., Toronto Univ., ON, Canada.

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
|October 20, 2007
PubMed
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Accelerating the Smith-Waterman algorithm using FPGA hardware custom instructions significantly improved runtime by 287% for genomic database searching. This demonstrates FPGA acceleration as a promising approach for faster gene function inference.

Area of Science:

  • Bioinformatics
  • Computer Engineering

Background:

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

Purpose of the Study:

  • To accelerate the Smith-Waterman algorithm for efficient genomic database searching.
  • To investigate the use of FPGA hardware custom instructions for performance enhancement.

Main Methods:

  • Modified computationally intensive parts of the Smith-Waterman algorithm using FPGA hardware custom instructions.
  • Compared the runtime of the modified algorithm against a pure software implementation.

Main Results:

  • Achieved an average runtime acceleration of 287% compared to the software-only version.

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  • Demonstrated significant performance improvement through hardware acceleration.

    • Conclusions:

    • FPGA hardware acceleration offers a viable and effective strategy for improving the runtime of genomic database searching.
    • Further development in FPGA-designed hardware holds promise for advancing computational efficiency in bioinformatics.