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Implementation of Relativistic Coupled Cluster Theory for Massively Parallel GPU-Accelerated Computing Architectures

[Image: see text] In this paper, we report reimplementation of the core algorithms of relativistic coupled cluster theory aimed at modern heterogeneous high-performance computational infrastructures. The code is designed for parallel execution on many compute nodes with optional GPU coprocessing, ac...

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Autores principales: Pototschnig, Johann V., Papadopoulos, Anastasios, Lyakh, Dmitry I., Repisky, Michal, Halbert, Loïc, Severo Pereira Gomes, André, Jensen, Hans Jørgen Aa, Visscher, Lucas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2021
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8444343/
https://www.ncbi.nlm.nih.gov/pubmed/34370471
http://dx.doi.org/10.1021/acs.jctc.1c00260
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author Pototschnig, Johann V.
Papadopoulos, Anastasios
Lyakh, Dmitry I.
Repisky, Michal
Halbert, Loïc
Severo Pereira Gomes, André
Jensen, Hans Jørgen Aa
Visscher, Lucas
author_facet Pototschnig, Johann V.
Papadopoulos, Anastasios
Lyakh, Dmitry I.
Repisky, Michal
Halbert, Loïc
Severo Pereira Gomes, André
Jensen, Hans Jørgen Aa
Visscher, Lucas
author_sort Pototschnig, Johann V.
collection PubMed
description [Image: see text] In this paper, we report reimplementation of the core algorithms of relativistic coupled cluster theory aimed at modern heterogeneous high-performance computational infrastructures. The code is designed for parallel execution on many compute nodes with optional GPU coprocessing, accomplished via the new ExaTENSOR back end. The resulting ExaCorr module is primarily intended for calculations of molecules with one or more heavy elements, as relativistic effects on the electronic structure are included from the outset. In the current work, we thereby focus on exact two-component methods and demonstrate the accuracy and performance of the software. The module can be used as a stand-alone program requiring a set of molecular orbital coefficients as the starting point, but it is also interfaced to the DIRAC program that can be used to generate these. We therefore also briefly discuss an improvement of the parallel computing aspects of the relativistic self-consistent field algorithm of the DIRAC program.
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spelling pubmed-84443432021-09-20 Implementation of Relativistic Coupled Cluster Theory for Massively Parallel GPU-Accelerated Computing Architectures Pototschnig, Johann V. Papadopoulos, Anastasios Lyakh, Dmitry I. Repisky, Michal Halbert, Loïc Severo Pereira Gomes, André Jensen, Hans Jørgen Aa Visscher, Lucas J Chem Theory Comput [Image: see text] In this paper, we report reimplementation of the core algorithms of relativistic coupled cluster theory aimed at modern heterogeneous high-performance computational infrastructures. The code is designed for parallel execution on many compute nodes with optional GPU coprocessing, accomplished via the new ExaTENSOR back end. The resulting ExaCorr module is primarily intended for calculations of molecules with one or more heavy elements, as relativistic effects on the electronic structure are included from the outset. In the current work, we thereby focus on exact two-component methods and demonstrate the accuracy and performance of the software. The module can be used as a stand-alone program requiring a set of molecular orbital coefficients as the starting point, but it is also interfaced to the DIRAC program that can be used to generate these. We therefore also briefly discuss an improvement of the parallel computing aspects of the relativistic self-consistent field algorithm of the DIRAC program. American Chemical Society 2021-08-09 2021-09-14 /pmc/articles/PMC8444343/ /pubmed/34370471 http://dx.doi.org/10.1021/acs.jctc.1c00260 Text en © 2021 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 Pototschnig, Johann V.
Papadopoulos, Anastasios
Lyakh, Dmitry I.
Repisky, Michal
Halbert, Loïc
Severo Pereira Gomes, André
Jensen, Hans Jørgen Aa
Visscher, Lucas
Implementation of Relativistic Coupled Cluster Theory for Massively Parallel GPU-Accelerated Computing Architectures
title Implementation of Relativistic Coupled Cluster Theory for Massively Parallel GPU-Accelerated Computing Architectures
title_full Implementation of Relativistic Coupled Cluster Theory for Massively Parallel GPU-Accelerated Computing Architectures
title_fullStr Implementation of Relativistic Coupled Cluster Theory for Massively Parallel GPU-Accelerated Computing Architectures
title_full_unstemmed Implementation of Relativistic Coupled Cluster Theory for Massively Parallel GPU-Accelerated Computing Architectures
title_short Implementation of Relativistic Coupled Cluster Theory for Massively Parallel GPU-Accelerated Computing Architectures
title_sort implementation of relativistic coupled cluster theory for massively parallel gpu-accelerated computing architectures
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8444343/
https://www.ncbi.nlm.nih.gov/pubmed/34370471
http://dx.doi.org/10.1021/acs.jctc.1c00260
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