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dc.contributor.authorAsaduzzaman, Abu
dc.contributor.authorMartinez, Angel
dc.contributor.authorSepehri, Aras
dc.date.accessioned2016-04-09T22:19:22Z
dc.date.available2016-04-09T22:19:22Z
dc.date.issued2015
dc.identifier.citationA. Asaduzzaman, A. Martinez and A. Sepehri, "A time-efficient image processing algorithm for multicore/manycore parallel computing," Proceedings of the IEEE SoutheastCon 2015, Fort Lauderdale, FL, 2015, pp. 1-5en_US
dc.identifier.isbn978-1-4673-7300-5
dc.identifier.issn1091-0050
dc.identifier.otherWOS:000371393800058
dc.identifier.urihttp://dx.doi.org/10.1109/SECON.2015.7132924
dc.identifier.urihttp://hdl.handle.net/10057/12005
dc.descriptionClick on the DOI link to access the article (may not be free).en_US
dc.description.abstractTraditional methods for processing large images are extremely time intensive. Also, conventional image processing methods do not take advantage of available computing resources such as multicore central processing unit (CPU) and manycore general purpose graphics processing unit (GP-GPU). Studies suggest that applying parallel programming techniques to various image filters should improve the overall performance without compromising the existing resources. Recent studies also suggest that parallel implementation of image processing on compute unified device architecture (CUDA)-accelerated CPU/GPU system has potential to process the image very fast. In this paper, we introduce a CUDA-accelerated image processing method suitable for multicore/manycore systems. Using a bitmap file, we implement image processing and filtering through traditional sequential C and newly introduced parallel CUDA/C programs. A key step of the proposed algorithm is to load the pixel's bytes in a one dimensional array with length equal to matrix width * matrix height * bytes per pixel. This is done to process the image concurrently in parallel. According to experimental results, the proposed CUDA-accelerated parallel image processing algorithm provides benefit with a speedup factor up to 365 for an image with 8,192x8,192 pixels.en_US
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.relation.ispartofseriesIEEE Southeast Conference (IEEE SoutheastCon) 2015;
dc.subjectCUDAen_US
dc.subjectGPU computingen_US
dc.subjectImage filteringen_US
dc.subjectImage processingen_US
dc.subjectParallel programmingen_US
dc.subjectResearch Subject Categories::TECHNOLOGY::Information technology::Computer science::Software engineeringen_US
dc.titleA time-efficient image processing algorithm for multicore/manycore parallel computingen_US
dc.typeConference paperen_US
dc.rights.holder© Copyright 2016 IEEE - All rights reserved.en_US


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