Hypergraph-based data partitioning

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buir.advisorAykanat, Cevdet
dc.contributor.authorKayaaslan, Enver
dc.date.accessioned2016-01-08T18:25:40Z
dc.date.available2016-01-08T18:25:40Z
dc.date.issued2013
dc.descriptionAnkara : The Department of Computer Engineering and the Graduate School of Engineering and Science of Bilkent University, 2013.en_US
dc.descriptionThesis (Ph.D.) -- Bilkent University, 2013en_US
dc.descriptionIncludes bibliographical references leaves 96-103.en_US
dc.description.abstractA hypergraph is a general version of graph where the edges may connect any number of vertices. By this flexibility, hypergraphs has a larger modeling power that may allow accurate formulaion of many problems of combinatorial scientific computing. This thesis discusses the use of hypergraph-based approaches to solve problems that require data partitioning. The thesis is composed of three parts. In the first part, we show how to implement hypergraph partitioning efficiently using recursive graph bipartitioning. The remaining two parts show how to formulate two important data partitioning problems in parallel computing as hypergraph partitioning. The first problem is global inverted index partitioning for parallel query processing and the second one is row-columnwise sparse matrix partitioning for parallel matrix vector multiplication, where both multiplication and sparse matrix partitioning schemes has novelty. In this thesis, we show that hypergraph models achieve partitions with better quality.en_US
dc.description.provenanceMade available in DSpace on 2016-01-08T18:25:40Z (GMT). No. of bitstreams: 1 0006563.pdf: 2510713 bytes, checksum: 1ea35d6bc7c4406adf667eb3551bd671 (MD5)en
dc.description.statementofresponsibilityKayaaslan, Enveren_US
dc.format.extentxiii, 103 leaves, tables, illustrations, graphicsen_US
dc.identifier.urihttp://hdl.handle.net/11693/15861
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjecthypergraphen_US
dc.subjectdata partitioningen_US
dc.subjectcombinatorial algorithmsen_US
dc.subject.lccQA165 .K391 2013en_US
dc.subject.lcshPartitions (Mathematics)en_US
dc.subject.lcshHypergraphs.en_US
dc.subject.lcshCombinatorial analysis.en_US
dc.subject.lcshComputer graphics.en_US
dc.titleHypergraph-based data partitioningen_US
dc.typeThesisen_US
thesis.degree.disciplineComputer Engineering
thesis.degree.grantorBilkent University
thesis.degree.levelDoctoral
thesis.degree.namePh.D. (Doctor of Philosophy)

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