An Application-Oriented Approach for Accelerating Data-Parallel Computation with Graphics Processing Unit

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dc.contributor.authorPonce, Seanen
dc.contributor.authorJing, Huangen
dc.contributor.authorPark, Seung Inen
dc.contributor.authorKhoury, Chaseen
dc.contributor.authorQuek, Francisen
dc.contributor.authorCao, Yongen
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2013-06-19T14:35:53Zen
dc.date.available2013-06-19T14:35:53Zen
dc.date.issued2009-03-01en
dc.description.abstractThis paper presents a novel parallelization and quantitative characterization of various optimization strategies for data-parallel computation on a graphics processing unit (GPU) using NVIDIA's new GPU programming framework, Compute Unified Device Architecture (CUDA). CUDA is an easy-to-use development framework that has drawn the attention of many different application areas looking for dramatic speed-ups in their code. However, the performance tradeoffs in CUDA are not yet fully understood, especially for data-parallel applications. Consequently, we study two fundamental mathematical operations that are common in many data-parallel applications: convolution and accumulation. Specifically, we profile and optimize the performance of these operations on a 128-core NVIDIA GPU. We then characterize the impact of these operations on a video-based motion-tracking algorithm called vector coherence mapping, which consists of a series of convolutions and dynamically weighted accumulations, and present a comparison of different implementations and their respective performance profiles.en
dc.format.mimetypeapplication/pdfen
dc.identifierhttp://eprints.cs.vt.edu/archive/00001064/en
dc.identifier.sourceurlhttp://eprints.cs.vt.edu/archive/00001064/01/paper.pdfen
dc.identifier.trnumberTR-09-05en
dc.identifier.urihttp://hdl.handle.net/10919/20162en
dc.language.isoenen
dc.publisherDepartment of Computer Science, Virginia Polytechnic Institute & State Universityen
dc.relation.ispartofComputer Science Technical Reportsen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectParallel computationen
dc.subjectAlgorithmsen
dc.subjectData structuresen
dc.titleAn Application-Oriented Approach for Accelerating Data-Parallel Computation with Graphics Processing Uniten
dc.typeTechnical reporten
dc.type.dcmitypeTexten

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