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Parallel execution of SVM training using graphics processing units (SVMTrGPUs)

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dc.citedby1
dc.contributor.authorSalleh N.S.M.en_US
dc.contributor.authorBaharim M.F.en_US
dc.contributor.authorid54946009300en_US
dc.contributor.authorid57190275900en_US
dc.date.accessioned2023-05-29T06:11:49Z
dc.date.available2023-05-29T06:11:49Z
dc.date.issued2016
dc.descriptionArray 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 machinesen_US
dc.description.abstractParallel 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.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo7482194
dc.identifier.doi10.1109/ICCSCE.2015.7482194
dc.identifier.epage263
dc.identifier.scopus2-s2.0-84978834001
dc.identifier.spage260
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84978834001&doi=10.1109%2fICCSCE.2015.7482194&partnerID=40&md5=a087d4e6d782bd93e437661111322b9d
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22720
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitleProceedings - 5th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2015
dc.titleParallel execution of SVM training using graphics processing units (SVMTrGPUs)en_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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