Two Examples of GPGPU Acceleration of Memory-intensive Algorithms

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dc.contributor.authorMarras, Stefanoen_US
dc.contributor.authorMura, Claudioen_US
dc.contributor.authorGobbetti, Enricoen_US
dc.contributor.authorScateni, Riccardoen_US
dc.contributor.authorScopigno, Robertoen_US
dc.contributor.editorEnrico Puppo and Andrea Brogni and Leila De Florianien_US
dc.date.accessioned2014-01-27T16:34:09Z
dc.date.available2014-01-27T16:34:09Z
dc.date.issued2010en_US
dc.description.abstractThe advent of GPGPU technologies has allowed for sensible speed-ups in many high-dimension, memory-intensive computational problems. In this paper we demonstrate the e ectiveness of such techniques by describing two applications of GPGPU computing to two di erent subfields of computer graphics, namely computer vision and mesh processing. In the first case, CUDA technology is employed to accelerate the computation of approximation of motion between two images, known also as optical flow. As for mesh processing, we exploit the massivelyparallel architecture of CUDA devices to accelerate the face clustering procedure that is employed in many recent mesh segmentation algorithms. In both cases, the results obtained so far are presented and thoroughly discussed, along with the expected future development of the work.en_US
dc.description.seriesinformationEurographics Italian Chapter Conference 2010en_US
dc.identifier.isbn978-3-905673-80-7en_US
dc.identifier.urihttps://doi.org/10.2312/LocalChapterEvents/ItalChap/ItalianChapConf2010/049-056en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.3 [Computer Graphics]: Picture/Image Generation-Line and curve generationen_US
dc.titleTwo Examples of GPGPU Acceleration of Memory-intensive Algorithmsen_US
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