A Lattice-Boltzmann solver for 3D fluid simulation on GPU

Autores
Rinaldi, Pablo Rafael; Dari, Enzo Alberto; Venere, Marcelo Javier; Clausse, Alejandro
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
A three-dimensional Lattice-Boltzmann fluid model with nineteen discrete velocities was implemented using NVIDIA Graphic Processing Unit (GPU) programing language ‘‘Compute Unified Device Architecture’’ (CUDA). Previous LBM GPU implementations required two steps to maximize memory bandwidth due to memory access restrictions of earlier versions of CUDA toolkit and hardware capabilities. In this work, a new approach based on single-step algorithm with a reversed collision–propagation scheme is developed to maximize GPU memory bandwidth, taking advantage of the newer versions of CUDA programming model and newer NVIDIA Graphic Cards. The code was tested on the numerical calculation of lid driven cubic cavity flow at Reynolds number 100 and 1000 showing great precision and stability. Simulations running on low cost GPU cards can calculate 400 cell updates per second with more than 65% hardware bandwidth.
Fil: Rinaldi, Pablo Rafael. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina
Fil: Dari, Enzo Alberto. Comisión Nacional de Energía Atómica. Gerencia del Área de Energía Nuclear. Instituto Balseiro; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Venere, Marcelo Javier. Universidad Nacional del Centro de la Provincia de Buenos Aires; Argentina
Fil: Clausse, Alejandro. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
GPU
Lattice Boltzmann
Simulation
Three dimensional
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/239501
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/239501
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A Lattice-Boltzmann solver for 3D fluid simulation on GPURinaldi, Pablo RafaelDari, Enzo AlbertoVenere, Marcelo JavierClausse, AlejandroGPULattice BoltzmannSimulationThree dimensionalhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1A three-dimensional Lattice-Boltzmann fluid model with nineteen discrete velocities was implemented using NVIDIA Graphic Processing Unit (GPU) programing language ‘‘Compute Unified Device Architecture’’ (CUDA). Previous LBM GPU implementations required two steps to maximize memory bandwidth due to memory access restrictions of earlier versions of CUDA toolkit and hardware capabilities. In this work, a new approach based on single-step algorithm with a reversed collision–propagation scheme is developed to maximize GPU memory bandwidth, taking advantage of the newer versions of CUDA programming model and newer NVIDIA Graphic Cards. The code was tested on the numerical calculation of lid driven cubic cavity flow at Reynolds number 100 and 1000 showing great precision and stability. Simulations running on low cost GPU cards can calculate 400 cell updates per second with more than 65% hardware bandwidth.Fil: Rinaldi, Pablo Rafael. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; ArgentinaFil: Dari, Enzo Alberto. Comisión Nacional de Energía Atómica. Gerencia del Área de Energía Nuclear. Instituto Balseiro; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Venere, Marcelo Javier. Universidad Nacional del Centro de la Provincia de Buenos Aires; ArgentinaFil: Clausse, Alejandro. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaElsevier Science2012-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/239501Rinaldi, Pablo Rafael; Dari, Enzo Alberto; Venere, Marcelo Javier; Clausse, Alejandro; A Lattice-Boltzmann solver for 3D fluid simulation on GPU; Elsevier Science; Simulation Modelling Practice and Theory; 25; 4-2012; 163-1711569-190XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S1569190X1200038Xinfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.simpat.2012.03.004info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:52:18Zoai:ri.conicet.gov.ar:11336/239501instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 14:52:18.303CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A Lattice-Boltzmann solver for 3D fluid simulation on GPU
title A Lattice-Boltzmann solver for 3D fluid simulation on GPU
spellingShingle A Lattice-Boltzmann solver for 3D fluid simulation on GPU
Rinaldi, Pablo Rafael
GPU
Lattice Boltzmann
Simulation
Three dimensional
title_short A Lattice-Boltzmann solver for 3D fluid simulation on GPU
title_full A Lattice-Boltzmann solver for 3D fluid simulation on GPU
title_fullStr A Lattice-Boltzmann solver for 3D fluid simulation on GPU
title_full_unstemmed A Lattice-Boltzmann solver for 3D fluid simulation on GPU
title_sort A Lattice-Boltzmann solver for 3D fluid simulation on GPU
dc.creator.none.fl_str_mv Rinaldi, Pablo Rafael
Dari, Enzo Alberto
Venere, Marcelo Javier
Clausse, Alejandro
author Rinaldi, Pablo Rafael
author_facet Rinaldi, Pablo Rafael
Dari, Enzo Alberto
Venere, Marcelo Javier
Clausse, Alejandro
author_role author
author2 Dari, Enzo Alberto
Venere, Marcelo Javier
Clausse, Alejandro
author2_role author
author
author
dc.subject.none.fl_str_mv GPU
Lattice Boltzmann
Simulation
Three dimensional
topic GPU
Lattice Boltzmann
Simulation
Three dimensional
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv A three-dimensional Lattice-Boltzmann fluid model with nineteen discrete velocities was implemented using NVIDIA Graphic Processing Unit (GPU) programing language ‘‘Compute Unified Device Architecture’’ (CUDA). Previous LBM GPU implementations required two steps to maximize memory bandwidth due to memory access restrictions of earlier versions of CUDA toolkit and hardware capabilities. In this work, a new approach based on single-step algorithm with a reversed collision–propagation scheme is developed to maximize GPU memory bandwidth, taking advantage of the newer versions of CUDA programming model and newer NVIDIA Graphic Cards. The code was tested on the numerical calculation of lid driven cubic cavity flow at Reynolds number 100 and 1000 showing great precision and stability. Simulations running on low cost GPU cards can calculate 400 cell updates per second with more than 65% hardware bandwidth.
Fil: Rinaldi, Pablo Rafael. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina
Fil: Dari, Enzo Alberto. Comisión Nacional de Energía Atómica. Gerencia del Área de Energía Nuclear. Instituto Balseiro; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Venere, Marcelo Javier. Universidad Nacional del Centro de la Provincia de Buenos Aires; Argentina
Fil: Clausse, Alejandro. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description A three-dimensional Lattice-Boltzmann fluid model with nineteen discrete velocities was implemented using NVIDIA Graphic Processing Unit (GPU) programing language ‘‘Compute Unified Device Architecture’’ (CUDA). Previous LBM GPU implementations required two steps to maximize memory bandwidth due to memory access restrictions of earlier versions of CUDA toolkit and hardware capabilities. In this work, a new approach based on single-step algorithm with a reversed collision–propagation scheme is developed to maximize GPU memory bandwidth, taking advantage of the newer versions of CUDA programming model and newer NVIDIA Graphic Cards. The code was tested on the numerical calculation of lid driven cubic cavity flow at Reynolds number 100 and 1000 showing great precision and stability. Simulations running on low cost GPU cards can calculate 400 cell updates per second with more than 65% hardware bandwidth.
publishDate 2012
dc.date.none.fl_str_mv 2012-04
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/239501
Rinaldi, Pablo Rafael; Dari, Enzo Alberto; Venere, Marcelo Javier; Clausse, Alejandro; A Lattice-Boltzmann solver for 3D fluid simulation on GPU; Elsevier Science; Simulation Modelling Practice and Theory; 25; 4-2012; 163-171
1569-190X
CONICET Digital
CONICET
url http://hdl.handle.net/11336/239501
identifier_str_mv Rinaldi, Pablo Rafael; Dari, Enzo Alberto; Venere, Marcelo Javier; Clausse, Alejandro; A Lattice-Boltzmann solver for 3D fluid simulation on GPU; Elsevier Science; Simulation Modelling Practice and Theory; 25; 4-2012; 163-171
1569-190X
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S1569190X1200038X
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.simpat.2012.03.004
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.22299

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