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Parallel execution of distributed SVM using MPI (CoDLib)

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dc.citedby10
dc.contributor.authorSalleh N.S.M.en_US
dc.contributor.authorSuliman A.en_US
dc.contributor.authorAhmad A.R.en_US
dc.contributor.authorid54946009300en_US
dc.contributor.authorid25825739000en_US
dc.contributor.authorid35589598800en_US
dc.date.accessioned2023-12-29T07:47:07Z
dc.date.available2023-12-29T07:47:07Z
dc.date.issued2011
dc.description.abstractSupport Vector Machine (SVM) is an efficient data mining approach for data classification. However, SVM algorithm requires very large memory requirement and computational time to deal with very large dataset. To reduce the computational time during the process of training the SVM, a combination of distributed and parallel computing method, CoDLib have been proposed. Instead of using a single machine for parallel computing, multiple machines in a cluster are used. Message Passing Interface (MPI) is used in the communication between machines in the cluster. The original dataset is split and distributed to the respective machines. Experiments results shows a great speed up on the training of the MNIST dataset where training time has been significantly reduced compared with standard LIBSVM without affecting the quality of the SVM. � 2011 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo6122723
dc.identifier.doi10.1109/ICIMU.2011.6122723
dc.identifier.scopus2-s2.0-84856509269
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84856509269&doi=10.1109%2fICIMU.2011.6122723&partnerID=40&md5=470fbba73be6d7a87fca32af9639f744
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/30371
dc.sourceScopus
dc.sourcetitle2011 International Conference on Information Technology and Multimedia: "Ubiquitous ICT for Sustainable and Green Living", ICIM 2011
dc.subjectDistributed SVM
dc.subjectLIBSVM
dc.subjectMessage Passing Interface (MPI)
dc.subjectSupport Vector Machine (SVM)
dc.subjectCluster computing
dc.subjectData mining
dc.subjectInformation technology
dc.subjectMessage passing
dc.subjectParallel architectures
dc.subjectComputational time
dc.subjectData classification
dc.subjectData sets
dc.subjectDistributed and parallel computing
dc.subjectDistributed SVM
dc.subjectLIBSVM
dc.subjectMemory requirements
dc.subjectMessage Passing Interface
dc.subjectMessage Passing Interface (MPI)
dc.subjectMultiple machine
dc.subjectParallel executions
dc.subjectSupport vector
dc.subjectSVM algorithm
dc.subjectTraining time
dc.subjectSupport vector machines
dc.titleParallel execution of distributed SVM using MPI (CoDLib)en_US
dc.typeConference paperen_US
dspace.entity.typePublication
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