3718

Solving Parabolic Problems Using Multithread and GPU

Chih-Wei Hsieh, Sheng-Hsiu Kuo, Fang-An Kuo, Chau-Yi Chou
National Center for High-Performance Comput., Hsinchu, Taiwan
International Symposium on Parallel and Distributed Processing with Applications (ISPA), 2010

@conference{hsieh2010solving,

   title={Solving Parabolic Problems Using Multithread and GPU},

   author={Hsieh, C.W. and Kuo, S.H. and Kuo, F.A. and Chou, C.Y.},

   booktitle={International Symposium on Parallel and Distributed Processing with Applications},

   pages={75–80},

   year={2010},

   organization={IEEE}

}

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Multi-core platform enters the territory of high performance computing (HPC). Moreover, the NVIDA GT200 has 240 cores and performs thousands upon thousands of threads simultaneously. The role of the Graphics Processing Units (GPU)accelerator has become more and more important for scientific computing and computational fluid dynamic (CFD) to obtain result quickly and efficiently. In this paper we presented efficient computational scheme for solving parabolic partial differential equations on Multithreading and GPU accelerator. The purpose of this paper is to obtain the solutions as accurate and high speed-up using implicit scheme is convection-diffusion-reaction(CDR). In this paper we propose to CUDA-CDR solver to quickly solve big problem on GPU accelerator. The NVIDIA CUDATM is an extension of C language and has been implemented as a veteran environment since 2006. Our multithread version illustrates 2.5 times faster than those on a sequential code in Model Problem 1 with the problem size of 400×400. The performance of parallel version via CUDA C is 11 times faster than those on a sequential code in Model Problem 1 with the problem size of 400×400.
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