@Article{CiCP-23-980,
author = {Tai-Hsien Wu, Mohammadreza Khani, Lina Sawalha, James Springstead, John Kapenga and Dewei Qi},
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 = {<p style="text-align: justify;">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.</p>},
issn = {1991-7120},
doi = {https://doi.org/10.4208/cicp.OA-2016-0251},
url = {http://global-sci.org/intro/article_detail/cicp/11202.html}
}