Publication: Parallel execution of SVM training using graphics processing units (SVMTrGPUs)
Date
2016
Authors
Salleh N.S.M.
Baharim M.F.
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
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.
Description
Array processing; Benchmarking; Computer graphics; Control systems; Diagnosis; Parallel processing systems; Pattern recognition; Program processors; Search engines; Vectors; World Wide Web; Computational problem; CUDA; Graphics Processing Unit; Graphics processing units; Pattern classification techniques; Performance analysis; UCW dataset; Vector processors; Support vector machines