GPU accelerated implementation of density functional theory for hybrid QM/MM simulations

The hybrid simulation tools (QM/MM) evolved into a fundamental methodology for studying chemical reactivity in complex environments. This paper presents an implementation of electronic structure calculations based on density functional theory. This development is optimized for performing hybrid mole...

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Autores principales: Nitsche, M.A., Ferreria, M., Mocskos, E.E., Lebrero, M.C.G.
Formato: JOUR
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_15499618_v10_n3_p959_Nitsche
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Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id todo:paper_15499618_v10_n3_p959_Nitsche
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spelling todo:paper_15499618_v10_n3_p959_Nitsche2023-10-03T16:23:16Z GPU accelerated implementation of density functional theory for hybrid QM/MM simulations Nitsche, M.A. Ferreria, M. Mocskos, E.E. Lebrero, M.C.G. The hybrid simulation tools (QM/MM) evolved into a fundamental methodology for studying chemical reactivity in complex environments. This paper presents an implementation of electronic structure calculations based on density functional theory. This development is optimized for performing hybrid molecular dynamics simulations by making use of graphic processors (GPU) for the most computationally demanding parts (exchange-correlation terms). The proposed implementation is able to take advantage of modern GPUs achieving acceleration in relevant portions between 20 to 30 times faster than the CPU version. The presented code was extensively tested, both in terms of numerical quality and performance over systems of different size and composition. © 2014 American Chemical Society. Fil:Mocskos, E.E. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_15499618_v10_n3_p959_Nitsche
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
description The hybrid simulation tools (QM/MM) evolved into a fundamental methodology for studying chemical reactivity in complex environments. This paper presents an implementation of electronic structure calculations based on density functional theory. This development is optimized for performing hybrid molecular dynamics simulations by making use of graphic processors (GPU) for the most computationally demanding parts (exchange-correlation terms). The proposed implementation is able to take advantage of modern GPUs achieving acceleration in relevant portions between 20 to 30 times faster than the CPU version. The presented code was extensively tested, both in terms of numerical quality and performance over systems of different size and composition. © 2014 American Chemical Society.
format JOUR
author Nitsche, M.A.
Ferreria, M.
Mocskos, E.E.
Lebrero, M.C.G.
spellingShingle Nitsche, M.A.
Ferreria, M.
Mocskos, E.E.
Lebrero, M.C.G.
GPU accelerated implementation of density functional theory for hybrid QM/MM simulations
author_facet Nitsche, M.A.
Ferreria, M.
Mocskos, E.E.
Lebrero, M.C.G.
author_sort Nitsche, M.A.
title GPU accelerated implementation of density functional theory for hybrid QM/MM simulations
title_short GPU accelerated implementation of density functional theory for hybrid QM/MM simulations
title_full GPU accelerated implementation of density functional theory for hybrid QM/MM simulations
title_fullStr GPU accelerated implementation of density functional theory for hybrid QM/MM simulations
title_full_unstemmed GPU accelerated implementation of density functional theory for hybrid QM/MM simulations
title_sort gpu accelerated implementation of density functional theory for hybrid qm/mm simulations
url http://hdl.handle.net/20.500.12110/paper_15499618_v10_n3_p959_Nitsche
work_keys_str_mv AT nitschema gpuacceleratedimplementationofdensityfunctionaltheoryforhybridqmmmsimulations
AT ferreriam gpuacceleratedimplementationofdensityfunctionaltheoryforhybridqmmmsimulations
AT mocskosee gpuacceleratedimplementationofdensityfunctionaltheoryforhybridqmmmsimulations
AT lebreromcg gpuacceleratedimplementationofdensityfunctionaltheoryforhybridqmmmsimulations
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