Scientific computation through a GPU

Genna Cummins, Rob Adams, Theodore Newell
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引用次数: 12

Abstract

A personal computer's graphics processing unit, or GPU, has been the seed of a growing interest in the academic and research communities of recent months. This paper investigates current technology that enables a GPU to process and solve linear algebra computations, in particular, matrix operations. Matrix operations of linear algebra are the basis of scientific computation, often used in modeling data and describing the forces of the universe. The author wished to compare the speed of the computation through the CPU and the GPU. Utilizing NVIDIA's CUDA technology, they demonstrated that calculations are preformed considerably faster through the GPU than through the CPU. The authors concluded that all computation in the research community has the potential to run significantly faster than current CPU's allow.
通过GPU进行科学计算
近几个月来,个人电脑的图形处理单元(GPU)在学术和研究界引发了越来越大的兴趣。本文研究了使GPU能够处理和解决线性代数计算,特别是矩阵运算的当前技术。线性代数的矩阵运算是科学计算的基础,经常用于数据建模和描述宇宙的力。作者希望通过CPU和GPU来比较计算速度。利用NVIDIA的CUDA技术,他们证明了通过GPU进行计算的速度要比通过CPU快得多。作者得出的结论是,研究社区中的所有计算都有可能比当前CPU允许的运行速度快得多。
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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