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Operation of the Collaborative Composite Manufacturing (CCM) System
10:09

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Published on: October 1, 2019

SHAKE parallelization.

Ron Elber1, A Peter Ruymgaart, Berk Hess

  • 1Institute for Computational Engineering and Sciences, Department of Chemistry and Biochemistry, University of Texas at Austin, TX 78712, USA.

The European Physical Journal. Special Topics
|February 28, 2012
PubMed
Summary
This summary is machine-generated.

The SHAKE algorithm enhances molecular dynamics simulations by enabling larger time steps. New parallelizable SHAKE alternatives are crucial for efficient, scalable simulations, overcoming limitations of the bond relaxation method.

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Area of Science:

  • Computational Chemistry
  • Molecular Dynamics Simulations
  • Biophysics

Background:

  • The SHAKE algorithm is essential for imposing holonomic constraints in molecular simulations, allowing for larger integration time steps and extended simulation lengths.
  • Parallelization is another key technique to accelerate molecular dynamics by speeding up force calculations, enabling longer trajectories and improved statistical averages.
  • Combining SHAKE with parallelization is highly desirable for enhanced computational efficiency in molecular dynamics.

Purpose of the Study:

  • To address the incompatibility of the standard SHAKE algorithm with parallelization.
  • To develop and evaluate alternative SHAKE algorithms suitable for parallel computing environments.
  • To ensure these new algorithms minimize communication, achieve good load balancing, and offer superior performance and scalability.

Main Methods:

  • Theoretical analysis of constrained dynamics algorithms on parallel systems.
  • Implementation and testing of alternative SHAKE algorithms on common parallel architectures.
  • Evaluation of communication overhead, load balancing, and performance scaling.

Main Results:

  • The widely used bond relaxation SHAKE method is not suitable for parallelization.
  • New SHAKE implementations are proposed that are designed for parallel environments.
  • These alternatives aim to minimize communication and improve load balancing for better performance.

Conclusions:

  • Developing parallelizable SHAKE algorithms is critical for advancing molecular dynamics simulations.
  • The presented alternatives offer a path towards more efficient and scalable simulations.
  • Further research and implementation on various architectures are needed to fully realize the benefits.