{"id":10365,"date":"2013-08-21T23:45:05","date_gmt":"2013-08-21T20:45:05","guid":{"rendered":"http:\/\/hgpu.org\/?p=10365"},"modified":"2013-08-21T23:51:15","modified_gmt":"2013-08-21T20:51:15","slug":"comparative-analysis-of-openacc-openmp-and-cuda-using-sequential-and-parallel-algorithms","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=10365","title":{"rendered":"Comparative Analysis of OpenACC, OpenMP and CUDA using Sequential and Parallel Algorithms"},"content":{"rendered":"<p>With the increased processing required in the last years, and the search for devices with better performance, started in computing a need to parallelize processing, making it possible to support the performance of software and algorithms requiring high processing pattern. It&#8217;s possible to use the processing power of devices like the GPU to run parallel software with a better execution time. In this work, will be evaluated the performance of three programming parallel models using CUDA, OpenMP and OpenACC with three different applications.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>With the increased processing required in the last years, and the search for devices with better performance, started in computing a need to parallelize processing, making it possible to support the performance of software and algorithms requiring high processing pattern. It&#8217;s possible to use the processing power of devices like the GPU to run parallel [&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":[11,89,3],"tags":[1782,14,20,1452,1321,252,67],"class_list":["post-10365","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-paper","tag-computer-science","tag-cuda","tag-nvidia","tag-nvidia-geforce-gtx-650","tag-openacc","tag-openmp","tag-performance"],"views":2794,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/10365","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=10365"}],"version-history":[{"count":1,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/10365\/revisions"}],"predecessor-version":[{"id":10370,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/10365\/revisions\/10370"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=10365"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=10365"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=10365"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}