Please use this identifier to cite or link to this item: http://dspace.uniten.edu.my/jspui/handle/123456789/7252
Title: Parallel execution of SVM training using graphics processing units (SVMTrGPUs)
Authors: Salleh, N.S.M. 
Baharim, M.F. 
Issue Date: 2016
Abstract: 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. © 2015 IEEE.
URI: http://dspace.uniten.edu.my/jspui/handle/123456789/7252
Appears in Collections:CSIT Scholarly Publication

Show full item record

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.