An Efficient Algorithm for Parallel Computation of Rough Entropy Using CUDA

2017 13th International Conference on Computational Intelligence and Security (CIS) Pub Date : 2017-12-01 DOI:10.1109/CIS.2017.00009

Siyuan Jing, Caiming Liu, Gongliang Li, Gaorong Yan, Yan Zhang

引用次数: 5

Abstract

Continuously improving computation efficiency of rough entropy is very meaningful, because it is helpful to apply rough sets to some fields with high performance requirement. Recently, Graphics Processing Unit (GPU) has gained a lot of attention from scientific communities for its applicability in high performance computing. This paper proposes an efficient algorithm which is based on sorting technique to accelerate the computation of rough entropy using CUDA. The proposed algorithm is compared with a sorting-based serial algorithm. Experimental results prove the effectiveness of the proposed algorithm.

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基于CUDA的粗糙熵并行计算的高效算法

不断提高粗糙熵的计算效率，有助于将粗糙集应用于一些对性能要求较高的领域，具有十分重要的意义。近年来，图形处理单元(GPU)因其在高性能计算中的适用性受到了科学界的广泛关注。本文提出了一种基于排序技术的基于CUDA的粗糙熵快速计算算法。将该算法与基于排序的串行算法进行了比较。实验结果证明了该算法的有效性。

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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2017 13th International Conference on Computational Intelligence and Security (CIS)

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