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Volume 23, Issue 4
A CUDA-Based Implementation of a Fluid-Solid Interaction Solver: The Immersed Boundary Lattice-Boltzmann Lattice-Spring Method

Tai-Hsien Wu, Mohammadreza Khani, Lina Sawalha, James Springstead, John Kapenga & Dewei Qi

Commun. Comput. Phys., 23 (2018), pp. 980-1011.

Published online: 2018-04

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  • Abstract

The immersed boundary lattice-Boltzmann lattice-spring method (IBLLM) has previously been implemented to solve several systems involving deformable and moving solid bodies suspended in Navier-Stokes fluids, but these studies have generally been limited in scope by a lack of computing power. In this study a Graphics Processing Unit (GPU) in CUDA Fortran is implemented to solve a variety of systems, including a flexible beam, stretching of a red blood cell (RBC), and an ellipsoid under shear flow. A series of simulations is run to validate implementation of the IBLLM and analyze computing performance. Results demonstrate that an Intel Xeon E5645 fitted with an NVIDIA Tesla K40 graphics card running on a GPU improves computational speed by a maximum of over 80-fold increase in speed when compared with the same processor running on a CPU for solving a system of moderately sized solid and fluid particles. These studies represent the first report on using a single GPU device with CUDA Fortran in the implementation of the IBLLM solver. Incorporation of a GPU while solving with the versatile IBLLM technique will expand the range of complex fluid-solid interaction (FSI) problems that can be solved in a variety of fields.

  • AMS Subject Headings

68U20, 74S30, 76Z99, 92C99

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COPYRIGHT: © Global Science Press

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@Article{CiCP-23-980, author = {}, title = {A CUDA-Based Implementation of a Fluid-Solid Interaction Solver: The Immersed Boundary Lattice-Boltzmann Lattice-Spring Method}, journal = {Communications in Computational Physics}, year = {2018}, volume = {23}, number = {4}, pages = {980--1011}, abstract = {

The immersed boundary lattice-Boltzmann lattice-spring method (IBLLM) has previously been implemented to solve several systems involving deformable and moving solid bodies suspended in Navier-Stokes fluids, but these studies have generally been limited in scope by a lack of computing power. In this study a Graphics Processing Unit (GPU) in CUDA Fortran is implemented to solve a variety of systems, including a flexible beam, stretching of a red blood cell (RBC), and an ellipsoid under shear flow. A series of simulations is run to validate implementation of the IBLLM and analyze computing performance. Results demonstrate that an Intel Xeon E5645 fitted with an NVIDIA Tesla K40 graphics card running on a GPU improves computational speed by a maximum of over 80-fold increase in speed when compared with the same processor running on a CPU for solving a system of moderately sized solid and fluid particles. These studies represent the first report on using a single GPU device with CUDA Fortran in the implementation of the IBLLM solver. Incorporation of a GPU while solving with the versatile IBLLM technique will expand the range of complex fluid-solid interaction (FSI) problems that can be solved in a variety of fields.

}, issn = {1991-7120}, doi = {https://doi.org/10.4208/cicp.OA-2016-0251}, url = {http://global-sci.org/intro/article_detail/cicp/11202.html} }
TY - JOUR T1 - A CUDA-Based Implementation of a Fluid-Solid Interaction Solver: The Immersed Boundary Lattice-Boltzmann Lattice-Spring Method JO - Communications in Computational Physics VL - 4 SP - 980 EP - 1011 PY - 2018 DA - 2018/04 SN - 23 DO - http://doi.org/10.4208/cicp.OA-2016-0251 UR - https://global-sci.org/intro/article_detail/cicp/11202.html KW - Lattice Boltzmann method, lattice spring model, immersed boundary method, CUDA, red blood cell, fluid-solid interaction. AB -

The immersed boundary lattice-Boltzmann lattice-spring method (IBLLM) has previously been implemented to solve several systems involving deformable and moving solid bodies suspended in Navier-Stokes fluids, but these studies have generally been limited in scope by a lack of computing power. In this study a Graphics Processing Unit (GPU) in CUDA Fortran is implemented to solve a variety of systems, including a flexible beam, stretching of a red blood cell (RBC), and an ellipsoid under shear flow. A series of simulations is run to validate implementation of the IBLLM and analyze computing performance. Results demonstrate that an Intel Xeon E5645 fitted with an NVIDIA Tesla K40 graphics card running on a GPU improves computational speed by a maximum of over 80-fold increase in speed when compared with the same processor running on a CPU for solving a system of moderately sized solid and fluid particles. These studies represent the first report on using a single GPU device with CUDA Fortran in the implementation of the IBLLM solver. Incorporation of a GPU while solving with the versatile IBLLM technique will expand the range of complex fluid-solid interaction (FSI) problems that can be solved in a variety of fields.

Tai-Hsien Wu, Mohammadreza Khani, Lina Sawalha, James Springstead, John Kapenga & Dewei Qi. (2020). A CUDA-Based Implementation of a Fluid-Solid Interaction Solver: The Immersed Boundary Lattice-Boltzmann Lattice-Spring Method. Communications in Computational Physics. 23 (4). 980-1011. doi:10.4208/cicp.OA-2016-0251
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