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Related Experiment Videos

Parallelizing genetic linkage analysis: a case study for applying parallel computation in molecular biology.

P L Miller1, P Nadkarni, J E Gelernter

  • 1Yale University School of Medicine, New Haven, Connecticut 06510.

Computers and Biomedical Research, an International Journal
|June 1, 1991
PubMed
Summary
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Parallel computing accelerates genetic linkage analysis by converting the LINKMAP program. This study details a method for parallelizing iterative programs, improving computational speed on multiple processors.

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Computer Science

Background:

  • Conventional sequential programs in molecular biology face lengthy computation times.
  • Parallel computers can improve performance by performing computations simultaneously on multiple processors.
  • LINKMAP is a widely used sequential program for genetic linkage analysis.

Purpose of the Study:

  • To outline an approach for converting highly iterative sequential programs to a parallel form.
  • To present LINKMAP as a case study for parallelization.
  • To compare the performance of sequential and parallel versions of LINKMAP.

Main Methods:

  • Converted the sequential LINKMAP program to run on a parallel computer.
  • Utilized the machine-independent parallel programming language, Linda.

Related Experiment Videos

  • Developed an approach for converting existing iterative programs to parallel execution.

    • Main Results:

    • The parallel version of LINKMAP demonstrates performance improvements over the sequential version.
    • Benchmarks compare the performance of the parallel LINKMAP on different parallel machines.
    • The study discusses load balancing strategies for efficient parallel processing.

    Conclusions:

    • The parallelization of LINKMAP provides a viable method for accelerating genetic linkage analysis.
    • The outlined approach can be applied to parallelize other iterative programs.
    • Efficient load balancing is crucial for maximizing the benefits of parallel computing.