Application of GPU to computational multiphase fluid dynamics

The MARS (Multi-interfaces Advection and Reconstruction Solver) [1] is one of the surface volume tracking methods for multi-phase flows. Nowadays, the performance of GPU (Graphics Processing Unit) is much higher than the CPU (Central Processing Unit). In this study, the GPU was applied to the MARS i...

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Bibliographic Details
Published in:IOP conference series. Materials Science and Engineering 2010-06, Vol.10 (1), p.012024-012024
Main Authors: Nagatake, T, Kunugi, T
Format: Article
Language:English
Subjects:
Advection
Algorithms
Central processing units
Computation
Computational fluid dynamics
Computing time
CPUs
Fluid flow
Graphics processing units
Mars
Multiphase flow
Parallel processing
Solvers
Tracking
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Summary:The MARS (Multi-interfaces Advection and Reconstruction Solver) [1] is one of the surface volume tracking methods for multi-phase flows. Nowadays, the performance of GPU (Graphics Processing Unit) is much higher than the CPU (Central Processing Unit). In this study, the GPU was applied to the MARS in order to accelerate the computation of multi-phase flows (GPU-MARS), and the performance of the GPU-MARS was discussed. From the performance of the interface tracking method for the analyses of one-directional advection problem, it is found that the computing time of GPU(single GTX280) was around 4 times faster than that of the CPU (Xeon 5040, 4 threads parallelized). From the performance of Poisson Solver by using the algorithm developed in this study, it is found that the performance of the GPU showed around 30 times faster than that of the CPU. Finally, it is confirmed that the GPU showed the large acceleration of the fluid flow computation (GPU-MARS) compared to the CPU. However, it is also found that the double-precision computation of the GPU must perform with very high precision.
ISSN:1757-899X
1757-8981
1757-899X
DOI:10.1088/1757-899X/10/1/012024