Jacobi迭代法在图形处理器上的实现

Tao Wang, Yuan Yao, Lin Han, Dan Zhang, Yuanyuan Zhang
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引用次数: 12

摘要

CUDA是NVIDIA公司针对GPU上的通用计算而推出的一种新的计算架构。该架构在计算密集型应用和数据密集型应用中具有强大的计算能力,因此近年来,如何将该框架应用于科学计算已成为研究热点。求解线性方程组的迭代法在工程和科学计算中有着非常广泛的应用。该算法具有较高的计算强度和并行性,非常适合于CUDA架构。本文在支持cuda的GPU上实现了Jacobi迭代法。实验结果表明,该迭代方法可以有效地利用支持cuda的GPU计算能力,并取得良好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementation of Jacobi iterative method on graphics processor unit
CUDA is a new computing architecture introduced by NVIDIA Corporation, aiming at general purpose computation on GPU. The architecture has strong compute power in the compute-intensive applications and data-intensive applications, so in recent years, how the framework is applied to the scientific computing has become a hot research. The iterative method for solving systems of linear equations in engineering and scientific computing has a very far-ranging application. The algorithm provided with high computing intensity and parallelism is very suitable for CUDA architecture. In this paper, Jacobi iterative method is implemented on CUDA-enable GPU. The experimental results show that this iterative method can effectively make use of the CUDA-enable GPU computing power and achieve good performance.
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