Please use this identifier to cite or link to this item: http://dspace2020.uniten.edu.my:8080/handle/123456789/8424
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMd Salleh, N.S.en_US
dc.contributor.authorBin Mohamad Shariff, A.S.en_US
dc.contributor.authorBin Kamsani, M.I.A.en_US
dc.contributor.authorNazeri, S.en_US
dc.date.accessioned2018-02-15T03:00:54Z-
dc.date.available2018-02-15T03:00:54Z-
dc.date.issued2015-
dc.identifier.urihttp://dspace.uniten.edu.my/jspui/handle/123456789/8424-
dc.description.abstractParallel computing is a simultaneous use of multiple compute resources such as processors to solve difficult computational problems. It has been used in high-end computing areas such as pattern recognition, defense, web search engine, and medical diagnosis. This paper focuses on the implementation of pattern classification technique, Support Vector Machine (SVM) using Symmetric Multi-Processor (SMP) approach. We have carried out a performance analysis to benchmark the sequential SVM program against the SMP approach. The result shows that the parallelization of SVM training achieves a better performance than the sequential code speed-ups by 15.9s. © 2014 IEEE.-
dc.language.isoenen_US
dc.titleParallel execution of SVM using Symmetrical Multi-Processor (LIBSVM-OMP)en_US
dc.typeArticleen_US
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairetypeArticle-
item.cerifentitytypePublications-
Appears in Collections:CCI Scholarly Publication
COE Scholarly Publication
Show simple item record

Google ScholarTM

Check


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