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Parallelizing a molecular dynamics algorithm on a multiprocessor workstation using OpenMP.

Konstantin B Tarmyshov1, Florian Müller-Plathe

  • 1School of Engineering and Science, International University Bremen, P.O. Box 750 561, 28725 Bremen, Germany. k.tarmyshov@iu-bremen.de

Journal of Chemical Information and Modeling
|November 29, 2005
PubMed
Summary

The YASP molecular dynamics program was parallelized for faster simulations on shared-memory systems. This optimization significantly speeds up calculations for large molecular systems, improving computational efficiency.

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Area of Science:

  • Computational Chemistry
  • Molecular Dynamics Simulations
  • High-Performance Computing

Background:

  • Atomistic molecular dynamics simulations are crucial for understanding molecular behavior.
  • The computational cost of these simulations often limits system size and simulation length.
  • Efficient parallelization strategies are needed to overcome these limitations.

Purpose of the Study:

  • To parallelize the YASP molecular dynamics program for shared-memory architectures.
  • To improve the computational performance of YASP for large-scale simulations.
  • To assess the scalability and speedup achieved through parallelization.

Main Methods:

  • Parallelization of CPU-time-intensive modules using OpenMP compiler directives.
  • Selective modification of the neighbor list data structure for parallel access.

Related Experiment Videos

  • Implementation on shared-memory computer architectures, including IBM Regatta p690+ and Xeon systems.

    • Main Results:

    • Achieved useful speedup for systems with several thousand atoms and above.
    • Observed throughput increase with up to 12-16 processors on an IBM Regatta p690+.
    • Demonstrated a speedup of approximately 1.7 on dual-processor Xeon systems.

    Conclusions:

    • The parallelized YASP program offers significant performance improvements for large molecular dynamics simulations.
    • OpenMP provides an effective means to parallelize existing scientific code with minimal modifications.
    • The parallel implementation enhances the feasibility of atomistic simulations on modern multi-processor systems.