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Parallel pattern search energy minimization

D N White1

  • 1Department of Chemistry, University of Glasgow, Scotland.

Journal of Molecular Graphics & Modelling
|June 1, 1997
PubMed
Summary
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This study adapted a pattern search algorithm for molecular structure optimization to run on parallel computers. The parallel version shows efficiency and comparable convergence to the original sequential method.

Area of Science:

  • Computational chemistry
  • Parallel computing
  • Algorithm optimization

Background:

  • Molecular structure optimization is crucial in computational chemistry.
  • Traditional algorithms can be computationally intensive.
  • Parallel computing offers potential for accelerating these tasks.

Purpose of the Study:

  • To adapt a pattern search algorithm for parallel computation.
  • To evaluate the efficiency and convergence of the parallel algorithm.
  • To demonstrate parallelization strategies for stochastic procedures.

Main Methods:

  • Implementation of a pattern search algorithm on a parallel computer.
  • Analysis of parallel efficiency using speedup metrics.
  • Comparison of convergence rates between parallel and sequential algorithms.

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Main Results:

  • The adapted algorithm achieves significant parallel efficiency (speedup).
  • The parallel implementation maintains a comparable rate of convergence to the sequential version.
  • The study successfully parallelized a previously nonparallelizable stochastic procedure.

Conclusions:

  • Parallel computing is effective for optimizing molecular structures using pattern search algorithms.
  • Algorithm rearrangement can enable parallelization of inherently sequential processes.
  • This work provides a framework for accelerating computational chemistry tasks through parallelization.