Parallel Execution of SVM Training using Graphics Processing Units (SVMTrGPUs)

被引：0

作者：

Salleh, Nur Shakirah Md ^{[1
]}

Baharim, Muhammad Fahim ^{[1
]}

机构：

[1] Univ Tenaga Nas, Dept Syst & Networking, Shah Alam, Selangor, Malaysia

来源：

PROCEEDINGS 5TH IEEE INTERNATIONAL CONFERENCE ON CONTROL SYSTEM, COMPUTING AND ENGINEERING (ICCSCE 2015) | 2015年

关键词：

Parallel Computing; Support Vector Machine; CUDA; Vector Processor; Graphics Processing Units; UCW dataset;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Parallel computing is a simultaneous use of multiple compute resources, for example, processors to solve complex computational problems. It has been used in high-end computing areas such as pattern recognition, medical diagnosis, national defense, and web search engine. This paper focuses on the implementation of pattern classification technique, Support Vector Machine (SVM) using vector processor approach. We have carried out a performance analysis to benchmark the sequential SVM program against the Graphics Processing Units (GPUs) optimization. The result shows that the parallelization of SVM training duration achieves a better performance than the sequential code speedups by 6.40.

引用

页码：260 / 263

页数：4