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Research of the Algebraic Multigrid Method for Electron Optical Simulator

At present, electron optical simulator (EOS) takes a long time to solve linear FEM systems. The algebraic multigrid preconditioned conjugate gradient (AMGPCG) method can improve the efficiency of solving systems. This paper is focused on the implementation of the AMGPCG method in EOS. The aggregatio...

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Detalles Bibliográficos
Autores principales: Wang, Zhi, Hu, Quan, Zhu, Xiao-Fang, Li, Bin, Hu, Yu-Lu, Huang, Tao, Yang, Zhong-Hai, Li, Liang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9407372/
https://www.ncbi.nlm.nih.gov/pubmed/36010797
http://dx.doi.org/10.3390/e24081133
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author Wang, Zhi
Hu, Quan
Zhu, Xiao-Fang
Li, Bin
Hu, Yu-Lu
Huang, Tao
Yang, Zhong-Hai
Li, Liang
author_facet Wang, Zhi
Hu, Quan
Zhu, Xiao-Fang
Li, Bin
Hu, Yu-Lu
Huang, Tao
Yang, Zhong-Hai
Li, Liang
author_sort Wang, Zhi
collection PubMed
description At present, electron optical simulator (EOS) takes a long time to solve linear FEM systems. The algebraic multigrid preconditioned conjugate gradient (AMGPCG) method can improve the efficiency of solving systems. This paper is focused on the implementation of the AMGPCG method in EOS. The aggregation-based scheme, which uses two passes of a pairwise matching algorithm and the K-cyle scheme, is adopted in the aggregation-based algebraic multigrid method. Numerical experiments show the advantages and disadvantages of the AMG algorithm in peak memory and solving efficiency. The AMGPCG is more efficient than the iterative methods used in the past and only needs one coarsening when EOS computes the particle motion trajectory.
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spelling pubmed-94073722022-08-26 Research of the Algebraic Multigrid Method for Electron Optical Simulator Wang, Zhi Hu, Quan Zhu, Xiao-Fang Li, Bin Hu, Yu-Lu Huang, Tao Yang, Zhong-Hai Li, Liang Entropy (Basel) Article At present, electron optical simulator (EOS) takes a long time to solve linear FEM systems. The algebraic multigrid preconditioned conjugate gradient (AMGPCG) method can improve the efficiency of solving systems. This paper is focused on the implementation of the AMGPCG method in EOS. The aggregation-based scheme, which uses two passes of a pairwise matching algorithm and the K-cyle scheme, is adopted in the aggregation-based algebraic multigrid method. Numerical experiments show the advantages and disadvantages of the AMG algorithm in peak memory and solving efficiency. The AMGPCG is more efficient than the iterative methods used in the past and only needs one coarsening when EOS computes the particle motion trajectory. MDPI 2022-08-16 /pmc/articles/PMC9407372/ /pubmed/36010797 http://dx.doi.org/10.3390/e24081133 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wang, Zhi
Hu, Quan
Zhu, Xiao-Fang
Li, Bin
Hu, Yu-Lu
Huang, Tao
Yang, Zhong-Hai
Li, Liang
Research of the Algebraic Multigrid Method for Electron Optical Simulator
title Research of the Algebraic Multigrid Method for Electron Optical Simulator
title_full Research of the Algebraic Multigrid Method for Electron Optical Simulator
title_fullStr Research of the Algebraic Multigrid Method for Electron Optical Simulator
title_full_unstemmed Research of the Algebraic Multigrid Method for Electron Optical Simulator
title_short Research of the Algebraic Multigrid Method for Electron Optical Simulator
title_sort research of the algebraic multigrid method for electron optical simulator
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9407372/
https://www.ncbi.nlm.nih.gov/pubmed/36010797
http://dx.doi.org/10.3390/e24081133
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