FULL GPU Implementation of Lattice-Boltzmann Methods with Immersed Boundary Conditions for Fast Fluid Simulations

Lattice Boltzmann Method (LBM) has shown great potential in fluid simulations, but performance issues and difficulties to manage complex boundary conditions have hindered a wider application. The upcoming of Graphic Processing Units (GPU) Computing offered a possible solution for the performance iss...

Full description

Bibliographic Details
Main Authors: G Boroni, J Dottori, P Rinaldi
Format: Article
Language:English
Published: Multi-Science Publishing 2017-03-01
Series:International Journal of Multiphysics
Online Access:http://journal.multiphysics.org/index.php/IJM/article/view/310
id doaj-1e5e66f9315546dc8927898854f3c272
record_format Article
spelling doaj-1e5e66f9315546dc8927898854f3c2722020-11-24T21:20:04ZengMulti-Science PublishingInternational Journal of Multiphysics1750-95482048-39612017-03-0111110.21152/1750-9548.11.1.1321FULL GPU Implementation of Lattice-Boltzmann Methods with Immersed Boundary Conditions for Fast Fluid SimulationsG Boroni0J Dottori1P Rinaldi2CONICET, PLADEMA UNCPBACICPBA, PLADEMA UNCPBACICPBA, PLADEMA UNCPBALattice Boltzmann Method (LBM) has shown great potential in fluid simulations, but performance issues and difficulties to manage complex boundary conditions have hindered a wider application. The upcoming of Graphic Processing Units (GPU) Computing offered a possible solution for the performance issue, and methods like the Immersed Boundary (IB) algorithm proved to be a flexible solution to boundaries. Unfortunately, the implicit IB algorithm makes the LBM implementation in GPU a non-trivial task. This work presents a fully parallel GPU implementation of LBM in combination with IB. The fluid-boundary interaction is implemented via GPU kernels, using execution configurations and data structures specifically designed to accelerate each code execution. Simulations were validated against experimental and analytical data showing good agreement and improving the computational time. Substantial reductions of calculation rates were achieved, lowering down the required time to execute the same model in a CPU to about two magnitude orders.http://journal.multiphysics.org/index.php/IJM/article/view/310
collection DOAJ
language English
format Article
sources DOAJ
author G Boroni
J Dottori
P Rinaldi
spellingShingle G Boroni
J Dottori
P Rinaldi
FULL GPU Implementation of Lattice-Boltzmann Methods with Immersed Boundary Conditions for Fast Fluid Simulations
International Journal of Multiphysics
author_facet G Boroni
J Dottori
P Rinaldi
author_sort G Boroni
title FULL GPU Implementation of Lattice-Boltzmann Methods with Immersed Boundary Conditions for Fast Fluid Simulations
title_short FULL GPU Implementation of Lattice-Boltzmann Methods with Immersed Boundary Conditions for Fast Fluid Simulations
title_full FULL GPU Implementation of Lattice-Boltzmann Methods with Immersed Boundary Conditions for Fast Fluid Simulations
title_fullStr FULL GPU Implementation of Lattice-Boltzmann Methods with Immersed Boundary Conditions for Fast Fluid Simulations
title_full_unstemmed FULL GPU Implementation of Lattice-Boltzmann Methods with Immersed Boundary Conditions for Fast Fluid Simulations
title_sort full gpu implementation of lattice-boltzmann methods with immersed boundary conditions for fast fluid simulations
publisher Multi-Science Publishing
series International Journal of Multiphysics
issn 1750-9548
2048-3961
publishDate 2017-03-01
description Lattice Boltzmann Method (LBM) has shown great potential in fluid simulations, but performance issues and difficulties to manage complex boundary conditions have hindered a wider application. The upcoming of Graphic Processing Units (GPU) Computing offered a possible solution for the performance issue, and methods like the Immersed Boundary (IB) algorithm proved to be a flexible solution to boundaries. Unfortunately, the implicit IB algorithm makes the LBM implementation in GPU a non-trivial task. This work presents a fully parallel GPU implementation of LBM in combination with IB. The fluid-boundary interaction is implemented via GPU kernels, using execution configurations and data structures specifically designed to accelerate each code execution. Simulations were validated against experimental and analytical data showing good agreement and improving the computational time. Substantial reductions of calculation rates were achieved, lowering down the required time to execute the same model in a CPU to about two magnitude orders.
url http://journal.multiphysics.org/index.php/IJM/article/view/310
work_keys_str_mv AT gboroni fullgpuimplementationoflatticeboltzmannmethodswithimmersedboundaryconditionsforfastfluidsimulations
AT jdottori fullgpuimplementationoflatticeboltzmannmethodswithimmersedboundaryconditionsforfastfluidsimulations
AT prinaldi fullgpuimplementationoflatticeboltzmannmethodswithimmersedboundaryconditionsforfastfluidsimulations
_version_ 1726004075155161088