Parallelization of the numerical simulation of motion of deformable objects within fluid domain on a GPU device

T. Djukic; N. Filipovic

Research Article

Parallelization of the numerical simulation of motion of deformable objects within fluid domain on a GPU device

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@ARTICLE{10.4108/eai.28-2-2018.154143,
    author={T. Djukic and N. Filipovic},
    title={Parallelization of the numerical simulation of motion of deformable objects within fluid domain on a GPU device},
    journal={EAI Endorsed Transactions on Pervasive Health and Technology},
    volume={4},
    number={13},
    publisher={EAI},
    journal_a={PHAT},
    year={2018},
    month={2},
    keywords={CUDA architecture, NVIDIA, lattice Boltzmann method, solid-fluid interaction, parallelization speed-up.},
    doi={10.4108/eai.28-2-2018.154143}
}

T. Djukic
N. Filipovic
Year: 2018
Parallelization of the numerical simulation of motion of deformable objects within fluid domain on a GPU device
PHAT
EAI
DOI: 10.4108/eai.28-2-2018.154143

T. Djukic¹^,*, N. Filipovic²

1: BioIRC R&D Bioengineering Center, Prvoslava Stojanovica 6, 34000, Kragujevac, Serbia
2: BioIRC R&D Bioengineering Center, Prvoslava Stojanovica 6, 34000, Kragujevac, Serbia, Faculty of Engineering, University of Kragujevac, Sestre Janjic 6, Kragujevac, 34000, Serbia

*Contact email: tijana@kg.ac.rs

Abstract

Computationally demanding numerical simulations can be significantly accelerated using GPU (Graphics Processing Unit) devices. This way, the results of the simulation can be observed in real time. In this paper, the principles of GPU programming are used to simulate the movement of deformable objects within fluid domain. Lattice Boltzmann (LB) method is used to simulate fluid flow. The solid-fluid interaction is modeled using the Immersed boundary method. The developed software was tested on a Tesla GPU device; the execution time of parallelized version and sequential version of the software are compared and significant speed-up is obtained. Fluid flow simulations in the field of biomedicine that needed up to several hours to be performed, can now be completed in just a few minutes.

Keywords: CUDA architecture, NVIDIA, lattice Boltzmann method, solid-fluid interaction, parallelization speed-up.

Received: 13th Jul 2017
Accepted: 6th Oct 2017
Published: 28th Feb 2018
Publisher: EAI

: http://dx.doi.org/10.4108/eai.28-2-2018.154143

Copyright © 2018 T. Djukic and N. Filipovic., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.