{"id":11771,"date":"2014-04-01T22:39:04","date_gmt":"2014-04-01T19:39:04","guid":{"rendered":"http:\/\/hgpu.org\/?p=11771"},"modified":"2014-04-01T22:39:04","modified_gmt":"2014-04-01T19:39:04","slug":"gpu-based-performance-acceleration-of-radar-imaging-algorithms","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=11771","title":{"rendered":"GPU Based Performance Acceleration of Radar Imaging Algorithms"},"content":{"rendered":"<p>We consider the performance acceleration of the conventional Time Domain Backprojection and Kirchhoff Migration algorithms for imaging concealed targets. The Compute Unified Device Architecture (CUDA) and Open Computing Language (OpenCL) are used here for accelerating these algorithms on Graphics Processing Units (GPUs). Data generated by means of analytical methods, simulation and experiment are used for validation and performance comparison.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We consider the performance acceleration of the conventional Time Domain Backprojection and Kirchhoff Migration algorithms for imaging concealed targets. The Compute Unified Device Architecture (CUDA) and Open Computing Language (OpenCL) are used here for accelerating these algorithms on Graphics Processing Units (GPUs). Data generated by means of analytical methods, simulation and experiment are used for [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"closed","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":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[36,89,319,90,3],"tags":[1787,14,1802,20,1494,1793],"class_list":["post-11771","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-nvidia-cuda","category-electrodynamics","category-opencl","category-paper","tag-algorithms","tag-cuda","tag-electrodynamics","tag-nvidia","tag-nvidia-geforce-gt-610","tag-opencl"],"views":2243,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/11771","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=11771"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/11771\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=11771"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=11771"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=11771"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}