共轭梯度法加速科学计算的研究进展

2015 International Conference on Electronic Design, Computer Networks & Automated Verification (EDCAV) Pub Date : 2015-03-16 DOI:10.1109/EDCAV.2015.7060557

Shreyasee Debnath, Manashwi Tamuli, Ashok Ray, G. Trivedi

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引用次数: 5

摘要

共轭梯度法是在实际科学计算应用中求解大型方程组的一种非常有效的迭代方法。本文简要介绍了共轭梯度法及其变体。我们还对该方法在适合高性能计算的fpga、gpu等不同平台上的实现进行了比较分析。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A review on accelerating scientific computations using the Conjugate Gradient method

Conjugate Gradient method is a very efficient iterative method for solving large systems of equations arising from real life scientific computing applications. In this paper we present the Conjugate Gradient method and its variants in brief. We also present a comparative analysis of implementations of this method on various platforms like FPGAs, GPUs etc which are suitable for High Performance Computing.

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2015 International Conference on Electronic Design, Computer Networks & Automated Verification (EDCAV)

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