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Evaluation iterative solver for pCDR on GPU accelerator

Chih-Wei Hsieh, Sheng-Hsiu Kuo, Chau-Yi Chou
National Center for High-Performance Computing, No. 7, R&D Rd. VI Hsinchu Science Park, Hsinchu, Taiwan, R.O.C. 30076
The 2011 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA’11), 2011

@article{hsieh2011evaluation,

   title={Evaluation iterative solver for pCDR on GPU accelerator},

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

   year={2011}

}

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In the past few years, the graphics processing units (GPU) has become trend in high performance computing (HPC). The newest Top500 list was showed three supercomputers contain GPU accelerator on Top10 in Nov. 2010. The role of the GPU accelerator has become more and more important for scientific computing and computational fluid dynamic (CFD) to obtain result quickly and efficiently. The GPU has become the world’s top driving force behind supercomputer. It has hundreds of processor cores in parallel, large-scale operations can be split and can simultaneously load. In this paper we implemented a parallel CDR (pCDR) library of using CUDA. The pCDR provides an easily highlevel interface for GPU programming that greatly enhance developer productivity. It was a set of code for solving a convection diffusion reaction (CDR) scalar transport equation. In this paper, we would evaluate the performance comparison of general purpose processor and GPU accelerator. As a result, the performance of pCDR-CG via CUDA C has 6 times faster than those on a sequential code in the problem size of 800×800.
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