Publication:
Performance Comparison of Parallel Execution Using GPU and CPU in SVM Training Session

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dc.citedby3
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.accessioned2023-05-29T06:11:50Z
dc.date.available2023-05-29T06:11:50Z
dc.date.issued2016
dc.descriptionApplication programming interfaces (API); Array processing; Artificial intelligence; Benchmarking; Computer graphics; Image coding; Learning systems; Multiprocessing systems; Parallel processing systems; Program processors; Vectors; CUDA; Graphics processing units; Machine learning approaches; OpenMP; Performance analysis; Performance comparison; Symmetric multi-processors; UCW dataset; Support vector machinesen_US
dc.description.abstractSupport Vector Machine (SVM) is a machine learning approach, which is used in a growing number of applications. SVM is a useful technique for data classification. This machine learning approach has been optimized using two (2) parallel computing approaches. This includes symmetric multiprocessor (SMP) approach and vector processor approach. The outcome performance of the implementation of symmetric multiprocessor approach and vector processor approach on SVM training session is the focus of this paper. We have carried out a performance analysis to benchmark between Central Processing Unit (CPU) and Graphics Processing Units (GPUs) optimization. The result shows the GPU optimization of SVM training duration achieves better performance than the CPU optimized program by 3.11 of speedup. � 2015 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo7478746
dc.identifier.doi10.1109/ACSAT.2015.31
dc.identifier.epage217
dc.identifier.scopus2-s2.0-84979074755
dc.identifier.spage214
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84979074755&doi=10.1109%2fACSAT.2015.31&partnerID=40&md5=ea598a0d5a870388369d83196bc16d3c
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22722
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitleProceedings - 2015 4th International Conference on Advanced Computer Science Applications and Technologies, ACSAT 2015
dc.titlePerformance Comparison of Parallel Execution Using GPU and CPU in SVM Training Sessionen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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