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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/15888
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dc.contributor.authorSingh A.-
dc.contributor.authorGupta M.-
dc.contributor.authorMisra, Manoj-
dc.contributor.editorChakrabarti S.-
dc.contributor.editorSaha H.N.-
dc.date.accessioned2020-12-02T11:41:54Z-
dc.date.available2020-12-02T11:41:54Z-
dc.date.issued2018-
dc.identifier.citationProceedings of 2018 IEEE 8th Annual Computing and Communication Workshop and Conference, CCWC 2018, (2018), 294- 300-
dc.identifier.isbn9.78154E+12-
dc.identifier.urihttps://doi.org/10.1109/CCWC.2018.8301747-
dc.identifier.urihttp://repository.iitr.ac.in/handle/123456789/15888-
dc.description.abstractSequential pattern mining is one of the most important fields in data mining. The progressive sequential pattern mining problem explores the effect of deleting old data from the sequences in the database as well as adding new data to the sequences when sequential patterns are generated and hence generates the most accurate results in data mining applications. With the increasing amount of data, traditional algorithms running on uniprocessors have scalability troubles. We present a novel algorithm to optimize and scale the progressive mining of sequential patterns (PISA) problem on GPUs and achieve a speedup of more than 10× by efficiently utilizing coalesced memory accesses and SIMD execution on GPUs. © 2018 IEEE.-
dc.description.sponsorshipIEEE Region 6;IEEE USA;Institute of Engineering and Management (IEM);University of Engineering and Management (UEM);University of Nevada-
dc.language.isoen_US-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.-
dc.relation.ispartofProceedings of 2018 IEEE 8th Annual Computing and Communication Workshop and Conference, CCWC 2018-
dc.subjectCUDA-
dc.subjectdata mining-
dc.subjectGPU-
dc.subjectparallel computing-
dc.subjectps tree-
dc.titleParallel progressive sequential pattern (PPSP) mining-
dc.typeConference Paper-
dc.scopusid55487577400-
dc.scopusid57203756628-
dc.scopusid56223635000-
dc.affiliationSingh, A., Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, United States-
dc.affiliationGupta, M., Department of Computer Science and Engineering, Indian Institute of Technology, Roorkee, India-
dc.affiliationMisra, M., Department of Computer Science and Engineering, Indian Institute of Technology, Roorkee, India-
dc.identifier.conferencedetails8th IEEE Annual Computing and Communication Workshop and Conference, CCWC 2018, 8-10 January 2018-
Appears in Collections:Conference Publications [CS]

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