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Efficient magnetohydrodynamic simulations on graphics processing units with CUDA

delete2011-10-01
delete21
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OA
AI
H
Hon‐Cheng Wong *
U
Un‐Hong Wong
X
Xueshang Feng
Z
Zesheng Tang
DOI:10.1016/j.cpc.2011.05.011delete
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摘要

摘要

En 中文
Magnetohydrodynamic (MHD) simulations based on the ideal MHD equations have become a powerful tool for modeling phenomena in a wide range of applications including laboratory, astrophysical, and space plasmas. In general, high-resolution methods for solving the ideal MHD equations are computationally expensive and Beowulf clusters or even supercomputers are often used to run the codes that implemented these methods. With the advent of the Compute Unified Device Architecture (CUDA), modern graphics processing units (GPUs) provide an alternative approach to parallel computing for scientific simulations. In this paper we present, to the best of the author's knowledge, the first implementation of MHD simulations entirely on GPUs with CUDA, named GPU-MHD, to accelerate the simulation process. GPU-MHD supports both single and double precision computations. A series of numerical tests have been performed to validate the correctness of our code. Accuracy evaluation by comparing single and double precision computation results is also given. Performance measurements of both single and double precision are conducted on both the NVIDIA GeForce GTX 295 (GT200 architecture) and GTX 480 (Fermi architecture) graphics cards. These measurements show that our GPU-based implementation achieves between one and two orders of magnitude of improvement depending on the graphics card used, the problem size, and the precision when comparing to the original serial CPU MHD implementation. In addition, we extend GPU-MHD to support the visualization of the simulation results and thus the whole MHD simulation and visualization process can be performed entirely on GPUs. (C) 2011 Elsevier B.V. All rights reserved.
Keyword:
MHD simulations
GPUs
CUDA
Parallel computing
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期刊

Computer Physics Communications 封面图
Computer Physics Communications
IF:
3.4
论文数:
1.2W
被引数:
3.7W

机构

C
chinese academy of sciences
学者数:
56.7W
论文数: 45.0W
被引数: 704
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