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A Performance Study of Moving Particle Semi-Implicit Method for Incompressible Fluid Flow on GPU

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  • Kirankumar V. Kataraki

    (KLE Dr. M.S. Sheshgiri College of Engineering and Technology, Belgaum, India)

  • Satyadhyan Chickerur

    (KLE Technological University, Hubballi, India)

Abstract

The aim of moving particle semi-implicit (MPS) is to simulate the incompressible flow of fluids in free surface. MPS, when implemented, consumes a lot of time and thus, needs a very powerful computing system. Instead of using parallel computing system, the performance level of the MPS model can be improved by using graphics processing units (GPUs). The aim is to have a computing system that is capable of performing at high levels thereby enhancing the speed of processing the numerical computations required in MPS. The primary aim of the study is to build a GPU-accelerated MPS model using CUDA aimed at reducing the time taken to perform the search for neighboring particles. In order to increase the GPU processing speed, specific consideration is given towards the optimization of a neighboring particle search process. The numerical model of MPS is performed using the governing equations, notably the Navier-Stokes equation. The simulation model indicates that using GPU based MPS produce better performance compared to the traditional arrangement of using CPUs.

Suggested Citation

  • Kirankumar V. Kataraki & Satyadhyan Chickerur, 2020. "A Performance Study of Moving Particle Semi-Implicit Method for Incompressible Fluid Flow on GPU," International Journal of Distributed Systems and Technologies (IJDST), IGI Global, vol. 11(1), pages 83-94, January.
    • Handle: RePEc:igg:jdst00:v:11:y:2020:i:1:p:83-94
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