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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/239501
Ver los metadatos del registro completo
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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 Técnicas2025-09-29T09:57:01Zoai: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:34982025-09-29 09:57:02.141CONICET 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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13.070432 |