Projects per year
Abstract
This paper presents a Graphics Processing Unit (GPU) acceleration of an iteration-based discrete velocity method (DVM) for gas-kinetic model equations. Unlike the previous GPU parallelization of explicit kinetic schemes, this work is based on a fast converging iterative scheme. The memory reduction techniques previously proposed for DVM are applied for GPU computing, enabling full three-dimensional (3D) solutions of kinetic model equations in the contemporary GPUs usually with a limited memory capacity that otherwise would need terabytes of memory. The GPU algorithm is validated against the direct simulation Monte Carlo (DSMC) simulation of the 3D lid-driven cavity flow and the supersonic rarefied gas flow past a cube with the phase-space grid points up to 0.7 trillion. The computing performance profiling on three models of GPUs shows that the two main kernel functions can utilize 56% ~ 79% of the GPU computing and memory resources. The performance of the GPU algorithm is compared with a typical parallel CPU implementation of the same algorithm using the Message Passing Interface (MPI). The comparison shows that the GPU program on K40 and K80 achieves 1.2 ~ 2.8 and 1.2 ~ 2.4 speedups for the 3D lid-driven cavity flow, respectively, compared with the MPI parallelized CPU program running on 96 CPU cores.
Original language | English |
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Article number | 106861 |
Number of pages | 14 |
Journal | Computer Physics Communications |
Volume | 245 |
Early online date | 14 Aug 2019 |
DOIs | |
Publication status | Published - 31 Dec 2019 |
Keywords
- GPU
- CUDA
- discrete velocity method
- gas-kinetic equation
- high performance computing
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Projects
- 3 Finished
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Efficient Pore-Scale Kinetic Simulation of Gas Flows in Ultra-Tight Porous Media (EPSKS) MSCA-IF-2017
Zhang, Y.
European Commission - Horizon 2020
15/07/18 → 14/07/20
Project: Research
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Pore-Scale Study of Gas Flows in Ultra-tight Porous Media
Zhang, Y. & Scanlon, T.
EPSRC (Engineering and Physical Sciences Research Council)
1/09/15 → 30/09/19
Project: Research
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UK Consortium on Mesoscale Engineering Sciences (UKCOMES)
Zhang, Y.
EPSRC (Engineering and Physical Sciences Research Council)
1/06/13 → 31/05/18
Project: Research