Parallelized Implementation of the Finite Particle Method for Explicit Dynamics in GPU

查看全文 作　　者：Jingzhe [1]Tang;Yanfeng [1]Zheng;Chao [1]Yang;Wei [1]Wang;Yaozhi [1]Luo

机构地区：[1]College of Civil Engineering and Architecture,Zhejiang University,Hangzhou,China

出　　处：《Computer Modeling in Engineering & Sciences》索引2020年第1期,共27页

基　　金：the financial support provided by the National Key Research and Development Program of China(Grant No.2016YFC0800200);the National Natural Science Foundation of China(Grant Nos.51578494 and 51778568);the Fundamental Research Funds for the Central Universities(Grant No.2019QNA4043). 摘　　要：As a novel kind of particle method for explicit dynamics,the finite particle method(FPM)does not require the formation or solution of global matrices,and the evaluations of the element equivalent forces and particle displacements are decoupled in nature,thus making this method suitable for parallelization.The FPM also requires an acceleration strategy to overcome the heavy computational burden of its explicit framework for time-dependent dynamic analysis.To this end,a GPU-accelerated parallel strategy for the FPM is proposed in this paper.By taking advantage of the independence of each step of the FPM workflow,a generic parallelized computational framework for multiple types of analysis is established.Using the Compute Unified Device Architecture(CUDA),the GPU implementations of the main tasks of the FPM,such as evaluating and assembling the element equivalent forces and solving the kinematic equations for particles,are elaborated through careful thread management and memory optimization.Performance tests show that speedup ratios of 8,25 and 48 are achieved for beams,hexahedral solids and triangular shells,respectively.For examples consisting of explicit dynamic analyses of shells and solids,comparisons with Abaqus using 1 to 8 CPU cores validate the accuracy of the results and demonstrate a maximum speed improvement of a factor of 11.2. 关键词：Finite particle method GPU parallel computing explicit dynamics

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Parallelized Implementation of the Finite Particle Method for Explicit Dynamics in GPU

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