Performance Analysis of a Novel GPU Computation-to-core Mapping Scheme for Robust Facet Image Modeling

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dc.contributor.authorPark, Seung Inen
dc.contributor.authorCao, Yongen
dc.contributor.authorWatson, Layne T.en
dc.contributor.authorQuek, Francisen
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2013-06-19T14:36:32Zen
dc.date.available2013-06-19T14:36:32Zen
dc.date.issued2012en
dc.description.abstractThough the GPGPU concept is well-known in image processing, much more work remains to be done to fully exploit GPUs as an alternative computation engine. This paper investigates the computation-to-core mapping strategies to probe the efficiency and scalability of the robust facet image modeling algorithm on GPUs. Our fine-grained computation-to-core mapping scheme shows a significant performance gain over the standard pixel-wise mapping scheme. With in-depth performance comparisons across the two different mapping schemes, we analyze the impact of the level of parallelism on the GPU computation and suggest two principles for optimizing future image processing applications on the GPU platform.en
dc.format.mimetypeapplication/pdfen
dc.identifierhttp://eprints.cs.vt.edu/archive/00001187/en
dc.identifier.sourceurlhttp://eprints.cs.vt.edu/archive/00001187/01/RTIP12.pdfen
dc.identifier.trnumberTR-12-05en
dc.identifier.urihttp://hdl.handle.net/10919/19420en
dc.language.isoenen
dc.publisherDepartment of Computer Science, Virginia Polytechnic Institute & State Universityen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectParallel computationen
dc.titlePerformance Analysis of a Novel GPU Computation-to-core Mapping Scheme for Robust Facet Image Modelingen
dc.typeTechnical reporten
dc.type.dcmitypeTexten

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