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dc.contributor.advisorHollingsworth, Jeffrey Ken_US
dc.contributor.authorLam, Michael Oneilen_US
dc.date.accessioned2014-06-24T05:38:35Z
dc.date.available2014-06-24T05:38:35Z
dc.date.issued2014en_US
dc.identifier.urihttp://hdl.handle.net/1903/15149
dc.description.abstractAs scientific computation continues to scale upward, correct and efficient use of floating-point arithmetic is crucially important. Users of floating-point arithmetic encounter many problems, including rounding error, cancellation, and a tradeoff between performance and accuracy. This dissertation addresses these issues by introducing techniques for automated floating-point precision analysis. The contributions include a software framework that enables floating-point program analysis at the binary level, as well as specific techniques for cancellation detection, mixed-precision configuration, and reduced-precision sensitivity analysis. This work demonstrates that automated, practical techniques can provide insights regarding floating-point behavior as well as guidance towards acceptable precision level reduction. The tools and techniques in this dissertation represent novel contributions to the fields of high performance computing and program analysis, and serve as the first major step towards the larger vision of automated floating-point precision and performance tuning.en_US
dc.language.isoenen_US
dc.titleAutomated Floating-Point Precision Analysisen_US
dc.typeDissertationen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.contributor.departmentComputer Scienceen_US
dc.subject.pqcontrolledComputer scienceen_US
dc.subject.pquncontrolledautotuningen_US
dc.subject.pquncontrolledbinary editingen_US
dc.subject.pquncontrolledfloating-pointen_US
dc.subject.pquncontrolledhigh-performance computingen_US
dc.subject.pquncontrolledprecisionen_US
dc.subject.pquncontrolledprogram analysisen_US


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