2013Modern MachineryRequires access

High speed molecular dynamics simulation approach based on CUDA

Chen Jie-ji

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Abstract

The Compute Unified Device Architecture(CUDA) and the rapidly promoting ability of data-parallel processing and data transferring of Graphic Processing Units(GPU) make an attractive area for high performance computation based on CUDA. As the efficiency of large scale molecular dynamics simulation is relative low, a new approach to the molecular dynamics simulations based on CUDA is proposed. The CUDA-based algorithm of molecular dynamics simulation is give. We have used the CUDA C to implement parallel algorithm. The results indicated that the performance of the GPU is compared to their main processor counterpart. We achieve speedups of up to near 200 folds.

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What this paper is about

The Compute Unified Device Architecture(CUDA) and the rapidly promoting ability of data-parallel processing and data transferring of Graphic Processing Units(GPU) make an attractive area for high performance computation based on CUDA. As the efficiency of large scale molecular dynamics simulation is relative low, a new approach to the molecular dynamics simulations based on CUDA is proposed. The CUDA-based algorithm of molecular dynamics simulation is give. We have used the CUDA C to implement parallel algorithm. The results indicated that the performance of the GPU is compared to their main processor counterpart. We achieve speedups of up to near 200 folds.

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Available abstract

The Compute Unified Device Architecture(CUDA) and the rapidly promoting ability of data-parallel processing and data transferring of Graphic Processing Units(GPU) make an attractive area for high performance computation based on CUDA. As the efficiency of large scale molecular dynamics simulation is relative low, a new approach to the molecular dynamics simulations based on CUDA is proposed. The CUDA-based algorithm of molecular dynamics simulation is give. We have used the CUDA C to implement parallel algorithm. The results indicated that the performance of the GPU is compared to their main processor counterpart. We achieve speedups of up to near 200 folds.

Key concepts: CUDA, Computer science, Parallel computing, Computation, Computational science, Molecular dynamics, Speedup, General-purpose computing on graphics processing units

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