Research on classification of large-scale text on GPU platform

Computer Engineering and Applications ›› 2012, Vol. 48 ›› Issue (8): 141-143.

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Research on classification of large-scale text on GPU platform

LIU Yong1，2, WANG Zhiliang2, HUANG Yulong2

1.College of Physics and Electronic Engineering, Guangxi University for Nationalities, Nanning 530006, China
2.School of Computer Science & Engineering, South China University of Technology, Guangzhou 510006, China

Received:1900-01-01 Revised:1900-01-01 Online:2012-03-11 Published:2012-03-11

GPU平台上大规模文本分类的研究

刘勇1，2，王志亮2，黄玉龙2

1.广西民族大学物理与电子工程学院，南宁 530006
2.华南理工大学计算机科学与工程学院，广州 510006

Abstract

Abstract: To satisfy the need for fast classification of large scale texts, a new solution of parallel text classification is introduced, which is based on classical text classification solution and utilizes the powerful throughput of GPU. Extensive lab experiments are done in different platforms to verify the effectiveness of the solution. The result shows that it has 10X speedup compared with classical solution.

Key words: graphical processing unit, compute unified device architecture, native Bayes, parallel text categorization

摘要： 为满足大规模文本快速分类的需求，在传统文本分类方案基础上，利用GPU强大的并行吞吐量，提出了一种大规模并行文本分类方案。为验证该方案的有效性，在多个平台上进行充分的实验分析。结果表明，该方案比传统的分类方案具有10倍以上的加速比。

关键词: 图形处理器, 统一计算设备架构, 朴素贝叶斯, 并行文本分类

LIU Yong1，2, WANG Zhiliang2, HUANG Yulong2. Research on classification of large-scale text on GPU platform[J]. Computer Engineering and Applications, 2012, 48(8): 141-143.

刘勇1，2，王志亮2，黄玉龙2. GPU平台上大规模文本分类的研究[J]. 计算机工程与应用, 2012, 48(8): 141-143.

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Research on classification of large-scale text on GPU platform

GPU平台上大规模文本分类的研究

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