2012Journal of Computer-Aided Design & Computer GraphicsRequires access

CUDA Based Parallel Computation of BEM for 3D Elastostatics Problems

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Abstract

The low efficiency of the conventional boundary element method(BEM) is caused by the high computational complexity.In order to accelerate BEM computation,this paper presents a computing unified device architecture(CUDA) based GPU parallel algorithm which is applied in the BEM to solve 3D elastostatics problems.First,the parallelism of different coefficient integrals of the BEM in 3D elastostatics is analyzed and the corresponding GPU parallel algorithm is described.Then the solution method and its parallel strategy of the BEM equations are presented.The example results show that the GPU parallel algorithm is much faster than the conventional method.

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What this paper is about

The low efficiency of the conventional boundary element method(BEM) is caused by the high computational complexity.In order to accelerate BEM computation,this paper presents a computing unified device architecture(CUDA) based GPU parallel algorithm which is applied in the BEM to solve 3D elastostatics problems.First,the parallelism of different coefficient integrals of the BEM in 3D elastostatics is analyzed and the corresponding GPU parallel algorithm is described.Then the solution method and its parallel strategy of the BEM equations are presented.The example results show that the GPU parallel algorithm is much faster than the conventional method.

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Available abstract

The low efficiency of the conventional boundary element method(BEM) is caused by the high computational complexity.In order to accelerate BEM computation,this paper presents a computing unified device architecture(CUDA) based GPU parallel algorithm which is applied in the BEM to solve 3D elastostatics problems.First,the parallelism of different coefficient integrals of the BEM in 3D elastostatics is analyzed and the corresponding GPU parallel algorithm is described.Then the solution method and its parallel strategy of the BEM equations are presented.The example results show that the GPU parallel algorithm is much faster than the conventional method.

Key concepts: CUDA, Boundary element method, Computer science, Computation, Parallel computing, Computational science, Parallel algorithm, Scheme (mathematics)

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