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A pluggable framework for parallel pairwise sequence search.

Jeremy Archuleta1, Wu-chun Feng, Eli Tilevich

  • 1Department of Computer Science, Virginia Tech, Blacksburg, VA 24061, USA. jsarch@cs.vt.edu

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|November 16, 2007
PubMed
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This study introduces a novel framework to parallelize serial sequence-search tools, enhancing performance on modern multi-core processors. This approach maximizes hardware utilization for faster and more efficient sequence searching.

Area of Science:

  • Computer Science
  • Bioinformatics
  • Computational Biology

Background:

  • Modern computing relies on multi-core and multi-processor architectures.
  • Existing sequence-search tools are often designed for single-core systems, leading to underutilization of hardware capabilities.
  • This mismatch hinders the performance of critical bioinformatics and computational biology tasks.

Purpose of the Study:

  • To present a novel framework for converting serial sequence-search tools into parallel versions.
  • To enable full utilization of multi-core and multi-processor hardware for sequence searching.
  • To improve the performance and efficiency of sequence analysis.

Main Methods:

  • Development of a new software framework based on mixin layers with refined roles.

Related Experiment Videos

  • Implementation of a modular architecture allowing easy integration of new modules.
  • Conversion of existing serial sequence-search algorithms into a parallel framework.

    • Main Results:

    • The framework facilitates the conversion of serial tools to parallel versions.
    • Achieved significant improvements in sequence-search performance by leveraging multi-core processors.
    • Demonstrated efficient hardware utilization through parallel processing.

    Conclusions:

    • The proposed framework effectively addresses the performance bottleneck of serial sequence-search tools on modern hardware.
    • The modular design enhances maintainability and extensibility for future algorithmic development.
    • This approach opens avenues for advanced features in sequence analysis tools.