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Parallel Implementation of Nonadditive Gaussian Process Potentials for Monte Carlo Simulations
[Image: see text] A strategy is presented to implement Gaussian process potentials in molecular simulations through parallel programming. Attention is focused on the three-body nonadditive energy, though all algorithms extend straightforwardly to the additive energy. The method to distribute pairs a...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10339671/ https://www.ncbi.nlm.nih.gov/pubmed/37368843 http://dx.doi.org/10.1021/acs.jctc.3c00113 |
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author | Broad, Jack Wheatley, Richard J. Graham, Richard S. |
author_facet | Broad, Jack Wheatley, Richard J. Graham, Richard S. |
author_sort | Broad, Jack |
collection | PubMed |
description | [Image: see text] A strategy is presented to implement Gaussian process potentials in molecular simulations through parallel programming. Attention is focused on the three-body nonadditive energy, though all algorithms extend straightforwardly to the additive energy. The method to distribute pairs and triplets between processes is general to all potentials. Results are presented for a simulation box of argon, including full box and atom displacement calculations, which are relevant to Monte Carlo simulation. Data on speed-up are presented for up to 120 processes across four nodes. A 4-fold speed-up is observed over five processes, extending to 20-fold over 40 processes and 30-fold over 120 processes. |
format | Online Article Text |
id | pubmed-10339671 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-103396712023-07-14 Parallel Implementation of Nonadditive Gaussian Process Potentials for Monte Carlo Simulations Broad, Jack Wheatley, Richard J. Graham, Richard S. J Chem Theory Comput [Image: see text] A strategy is presented to implement Gaussian process potentials in molecular simulations through parallel programming. Attention is focused on the three-body nonadditive energy, though all algorithms extend straightforwardly to the additive energy. The method to distribute pairs and triplets between processes is general to all potentials. Results are presented for a simulation box of argon, including full box and atom displacement calculations, which are relevant to Monte Carlo simulation. Data on speed-up are presented for up to 120 processes across four nodes. A 4-fold speed-up is observed over five processes, extending to 20-fold over 40 processes and 30-fold over 120 processes. American Chemical Society 2023-06-27 /pmc/articles/PMC10339671/ /pubmed/37368843 http://dx.doi.org/10.1021/acs.jctc.3c00113 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Broad, Jack Wheatley, Richard J. Graham, Richard S. Parallel Implementation of Nonadditive Gaussian Process Potentials for Monte Carlo Simulations |
title | Parallel Implementation
of Nonadditive Gaussian Process
Potentials for Monte Carlo Simulations |
title_full | Parallel Implementation
of Nonadditive Gaussian Process
Potentials for Monte Carlo Simulations |
title_fullStr | Parallel Implementation
of Nonadditive Gaussian Process
Potentials for Monte Carlo Simulations |
title_full_unstemmed | Parallel Implementation
of Nonadditive Gaussian Process
Potentials for Monte Carlo Simulations |
title_short | Parallel Implementation
of Nonadditive Gaussian Process
Potentials for Monte Carlo Simulations |
title_sort | parallel implementation
of nonadditive gaussian process
potentials for monte carlo simulations |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10339671/ https://www.ncbi.nlm.nih.gov/pubmed/37368843 http://dx.doi.org/10.1021/acs.jctc.3c00113 |
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