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Abstract

In this paper, the graphic processing unit (GPU) parallel computing of dissipative particle dynamics (DPD) based on compute unified device architecture is carried out. Some issues involved, such as thread mapping, parallel cell-list array updating, generating pseudo-random number on GPU, memory access optimization and loading balancing are discussed in detail. Furthermore, Poiseuille flow and suddenly contracting and expanding flow are simulated to verify the correctness of GPU parallel computing. The results of GPU parallel computing of DPD show that the speedup ratio is about 20 times compared with central processing unit serial computing.

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Funds:Project supported by the Fundamental Scientific Research Foundation for the Central Universities of China (Grant No. 125065), the National Natural Science Foundation of China (Grant Nos. 51276130, 10872152), and the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20120072110037).

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Vol. 63, Issue 10 - 2014-05-20

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