{"id":7081,"date":"2012-01-31T22:58:32","date_gmt":"2012-01-31T20:58:32","guid":{"rendered":"http:\/\/hgpu.org\/?p=7081"},"modified":"2012-01-31T22:58:32","modified_gmt":"2012-01-31T20:58:32","slug":"an-opencl-implementation-for-the-solution-of-tdse-on-gpu-and-cpu-architectures","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=7081","title":{"rendered":"An OpenCL implementation for the solution of TDSE on GPU and CPU architectures"},"content":{"rendered":"<p>Open Computing Language (OpenCL) is a parallel processing language that is ideally suited for running parallel algorithms on Graphical Processing Units (GPUs). In the present work we report the development of a generic parallel single-GPU code for the numerical solution of a system of first-order ordinary differential equations (ODEs) based on the openCL model. We have applied the code in the case of the time-dependent Schr&quot;{o}dinger equation of atomic hydrogen in a strong laser field and studied its performance to the two basic kinds of compute units (GPUs and CPUs) . We found an excellent scalability and a significant speed-up of the GPU over the CPU device tending to a value of about 40.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Open Computing Language (OpenCL) is a parallel processing language that is ideally suited for running parallel algorithms on Graphical Processing Units (GPUs). In the present work we report the development of a generic parallel single-GPU code for the numerical solution of a system of first-order ordinary differential equations (ODEs) based on the openCL model. We [&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":[36,90,3,12],"tags":[1787,7,1281,98,810,20,923,1793,922,1783,930,244],"class_list":["post-7081","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-opencl","category-paper","category-physics","tag-algorithms","tag-ati","tag-ati-firepro-v7800","tag-computational-physics","tag-differential-equations","tag-nvidia","tag-odes","tag-opencl","tag-ordinary-differential-equations","tag-physics","tag-quantum-physics","tag-tesla-s1070"],"views":2374,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/7081","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=7081"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/7081\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=7081"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=7081"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=7081"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}