{"id":7640,"date":"2012-05-25T16:37:08","date_gmt":"2012-05-25T13:37:08","guid":{"rendered":"http:\/\/hgpu.org\/?p=7640"},"modified":"2012-05-25T16:37:08","modified_gmt":"2012-05-25T13:37:08","slug":"using-compute-unified-device-architecture-cuda-in-parallelizing-different-digital-image-processing-techniques","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=7640","title":{"rendered":"Using Compute Unified Device Architecture (CUDA) in Parallelizing Different Digital Image Processing Techniques"},"content":{"rendered":"<p>Graphics Processing Units (GPUs) have been conventionally used in the acceleration of 2D, 3D graphics and video rendering. Because of its performance and capability, the GPU has evolved into a highly parallel programmable processor that specializes in memory bandwith utilization and intensive computation. For operations involving graphics, GPUs offer a lot of gigaflops of processing prowess. The programmability and competency of GPU in the field of general-purpose computing is exemplified through the implementation of image processing techniques using Compute Unified Device Architecture (CUDA) which makes image processing be implemented with a high-speed performance.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Graphics Processing Units (GPUs) have been conventionally used in the acceleration of 2D, 3D graphics and video rendering. Because of its performance and capability, the GPU has evolved into a highly parallel programmable processor that specializes in memory bandwith utilization and intensive computation. For operations involving graphics, GPUs offer a lot of gigaflops of processing [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[89,33,3],"tags":[14,1786,20,1314],"class_list":["post-7640","post","type-post","status-publish","format-standard","hentry","category-nvidia-cuda","category-image-processing","category-paper","tag-cuda","tag-image-processing","tag-nvidia","tag-nvidia-geforce-gt-520-m"],"views":2852,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/7640","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=7640"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/7640\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=7640"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=7640"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=7640"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}