吉林大学学报（理学版）Issue(1)：107-111,5.DOI:10.13413/j.cnki.jdxblxb.2015.01.23
基于 GPU 的多类支持向量机改进算法
Improvement of Multiclass Support Vector Machines Based on Graphic Processor
摘要
Abstract
According to the phenomenon that the support vector machine algorithm takes too much time,the idea of using parallel computation was used to solve this problem.Based on this,an improvement of the classic multiclass support vector machine algorithm first proposed by Crammer and Singer was made,and it was realized by using the great parallel ability of graphic processor. Technology of loop unrolling,data staying, cache and open computing language were used for implementing the improved algorithm.The original algorithm and the improved algorithm were executed on the same four datasets.And the experimental results show that the improved algorithm is much better than the original algorithm in performance of time.关键词
支持向量机/多分类/图形处理器/并行计算/开放运算语言Key words
support vector machine/multiclass/graphic processing unit/parallel computation/open computing language分类
信息技术与安全科学引用本文复制引用
顾德闯,杨永健..基于 GPU 的多类支持向量机改进算法[J].吉林大学学报（理学版）,2015,(1):107-111,5.基金项目
教育部博士学科点专项基金(批准号:20120061110044) （批准号:20120061110044）
