Parallel stochastic gradient descent with sub-iterations on distributed memory systems

buir.advisorÖzdal, M. Mustafa
dc.contributor.authorÇağlayan, Orhun
dc.date.accessioned2022-03-22T06:11:04Z
dc.date.available2022-03-22T06:11:04Z
dc.date.copyright2022-02
dc.date.issued2022-02
dc.date.submitted2022-03-04
dc.departmentDepartment of Computer Engineeringen_US
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionThesis (Master's): Bilkent University, Department of Computer Engineering, İhsan Doğramacı Bilkent University, 2022.en_US
dc.descriptionIncludes bibliographical references (leaves 41-43).en_US
dc.description.abstractWe investigate parallelization of the stochastic gradient descent (SGD) algorithm for solving the matrix completion problem. Applications in the literature show that stale data usage and communication costs are important concerns that affect the performance of parallel SGD applications. We first briefly visit the stochastic gradient descent algorithm and matrix partitioning for parallel SGD. Then we define the stale data problem and communication costs. In order to improve the performance of parallel SGD, we propose a new algorithm with intra-iteration synchronization (referred as sub-iterations) to decrease communication costs and stale data usage. Experimental results show that using sub-iterations can de-crease staleness up to 95% and communication volume up to 47%. Furthermore, using sub-iterations can improve test error up to 60% when compared to the conventional parallel SGD implementation that does not use sub-iterations.en_US
dc.description.degreeM.S.en_US
dc.description.statementofresponsibilityby Orhun Çağlayanen_US
dc.embargo.release2022-09-04
dc.format.extentx, 43 leaves : charts ; 30 cm.en_US
dc.identifier.itemidB160829
dc.identifier.urihttp://hdl.handle.net/11693/77841
dc.language.isoEnglishen_US
dc.publisherBilkent Universityen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectStochastic gradient descenten_US
dc.subjectMatrix completionen_US
dc.subjectParallel computingen_US
dc.subjectDistributed memory systemsen_US
dc.titleParallel stochastic gradient descent with sub-iterations on distributed memory systemsen_US
dc.title.alternativeDağıtık bellekli sistemlerde alt-iterasyonlu paralel olasılıksal gradyan alçalmaen_US
dc.typeThesisen_US

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