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Parallel computation for biological sequence comparison: comparing a portable model to the native model for the Intel

P M Nadkarni1, P L Miller

  • 1Department of Anesthesiology, Yale School of Medicine, New Haven, CT 06510.

Proceedings. Symposium on Computer Applications in Medical Care
|January 1, 1991
PubMed
Summary
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This study compares two parallel programming approaches for biological sequence comparison. Machine-specific programming was efficient, while Linda offered portability but reduced efficiency with more processors.

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Parallel Computing

Background:

  • Inter-database sequence comparison is crucial for biological research.
  • Efficient parallel algorithms are needed for large-scale biological data analysis.
  • Evaluating different parallel programming models is essential for optimizing performance.

Purpose of the Study:

  • To develop and compare two parallel programming approaches for inter-database sequence comparison.
  • To assess the performance and efficiency of machine-specific vs. machine-independent parallel programming.
  • To evaluate the portability of parallel programs across different computing architectures.

Main Methods:

  • Developed a parallel program for sequence comparison on the Intel Hypercube.

Related Experiment Videos

  • Implemented two versions: one using machine-specific Hypercube commands, another using the Linda parallel programming language.
  • Conducted benchmark tests comparing the performance of both versions with varying numbers of processors.
  • Tested the Linda version on Network Linda, a virtual parallel machine.

    • Main Results:

    • Both parallel programming versions yielded comparable results with a small number of processors.
    • The Linda version showed decreased efficiency as the number of processors increased.
    • The Linda version demonstrated portability by running on Network Linda without modification.

    Conclusions:

    • Machine-specific parallel programming can offer higher efficiency for specific architectures.
    • Linda provides valuable machine independence and portability, crucial for diverse computing environments.
    • The choice of parallel programming model involves a trade-off between efficiency and portability for biological applications.