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dc.contributor.advisorBecchi, Michelaeng
dc.contributor.authorButler, Michael (Michael Christian)eng
dc.date.issued2016eng
dc.date.submitted2016 Summereng
dc.description.abstract[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] As computers began to reach their limit on how fast a single processor could execute code, computer developers began to devise methods to process more code simultaneously. Since then, parallel systems have become commonplace and increasingly necessary for processing large quantities of data quickly. These distributed architectures come in many different flavors, ranging from a multi-core CPU to many-core General Purpose Graphics Processing Units (GPUs) all the way up to a large cluster of computers and the cloud. Unfortunately, whereas all code in the past was automatically accelerated by upgrading to a better processor, these new parallel systems require advanced compiler directives, libraries, and in some cases entirely new languages in order to effectively use these distributed architectures, and oftentimes expertise on each system is required to fully utilize these devices. My research focuses on removing some of the difficulty with programming heterogeneous CPU-GPU nodes by transparently optimizing application execution during runtime. The first part of this thesis describes Sync-Free GPU (SF-GPU) [1], a node-level runtime system which automatically and transparently improves application concurrency on GPUs by managing implicit and explicit synchronizations, and the second part describes FPU, a functional programming API which generates highly optimized code for both the CPU and for any number of GPUs and automatically performs load balancing between all compute devices at runtime, all with only a few lines of code from the user.eng
dc.description.bibrefIncludes bibliographical references (pages 80-81).eng
dc.format.extent1 online resource (ix, 81 pages) : illustrationseng
dc.identifier.merlinb118608046eng
dc.identifier.oclc985511687eng
dc.identifier.urihttps://hdl.handle.net/10355/57620
dc.identifier.urihttps://doi.org/10.32469/10355/57620eng
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcollectionUniversity of Missouri--Columbia. Graduate School. Theses and Dissertationseng
dc.rightsAccess is limited to the campuses of the University of Missouri.eng
dc.subject.FASTGraphics processing unitseng
dc.subject.FASTFunctional programming (Computer science)eng
dc.subject.FASTParallel programming (Computer science)eng
dc.titleDesign of runtime libraries to improve programmability and efficiency of heterogeneous CPU-GPU nodeseng
dc.typeThesiseng
thesis.degree.disciplineComputer engineering (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelMasterseng
thesis.degree.nameM.S.eng


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