Graph/hypergraph partitioning models for simultaneous load balancing on computation and data

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buir.advisorAykanat, Cevdet
dc.contributor.authorÇeliktuğ, Mestan Fırat
dc.date.accessioned2019-01-09T07:14:12Z
dc.date.available2019-01-09T07:14:12Z
dc.date.copyright2018-12
dc.date.issued2018-12
dc.date.submitted2019-01-04
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionThesis (M.S.): Bilkent University, Department of Computer Engineering, İhsan Doğramacı Bilkent University, 2018.en_US
dc.descriptionIncludes bibliographical references (leaves 57-64).en_US
dc.description.abstractIn the literature, several successful partitioning models and methods have been proposed and used for computational load balancing of irregularly sparse applications on distributed-memory architectures. However, the literature lacks partitioning models and methods that encode both computational and data load balancing of processors. In this thesis, we try to close this gap by proposing graph and hypergraph partitioning models and methods that simultaneously encode computational and data load balancing of processors. The validity of the proposed models and methods are tested on two widely-used irregularly sparse applications: parallel mesh simulations and parallel sparse matrix sparse matrix multiplication.
dc.description.provenanceSubmitted by Betül Özen (ozen@bilkent.edu.tr) on 2019-01-09T07:14:12Z No. of bitstreams: 1 Signed_Thesis.pdf: 2484056 bytes, checksum: 5bc879ae8ed95b2d7de3ef6c7eccb1a1 (MD5)en
dc.description.provenanceMade available in DSpace on 2019-01-09T07:14:12Z (GMT). No. of bitstreams: 1 Signed_Thesis.pdf: 2484056 bytes, checksum: 5bc879ae8ed95b2d7de3ef6c7eccb1a1 (MD5) Previous issue date: 2019-01en
dc.description.statementofresponsibilityby Mestan Fırat Çeliktuğ.en_US
dc.embargo.release2019-07-04
dc.format.extentxii, 72 leaves : illustrations (some color), charts (some color) ; 30 cm.en_US
dc.identifier.itemidB159511
dc.identifier.urihttp://hdl.handle.net/11693/48228
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectComputation Load Balancingen_US
dc.subjectData Load Balancingen_US
dc.subjectSimultaneous Computation And Data Load Balancingen_US
dc.subjectMulti-Constraint Graph Partitioningen_US
dc.subjectMulticonstraint Hypergraph Partitioningen_US
dc.titleGraph/hypergraph partitioning models for simultaneous load balancing on computation and dataen_US
dc.title.alternativeEş zamanlı hesaplama ve veri yükü dengeleme için çizge/hiperçizge bölümleme modellerien_US
dc.typeThesisen_US
thesis.degree.disciplineComputer Engineering
thesis.degree.grantorBilkent University
thesis.degree.levelMaster's
thesis.degree.nameMS (Master of Science)

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