{"id":4500,"date":"2011-06-29T20:26:03","date_gmt":"2011-06-29T20:26:03","guid":{"rendered":"http:\/\/hgpu.org\/?p=4500"},"modified":"2011-06-29T20:26:03","modified_gmt":"2011-06-29T20:26:03","slug":"hardware-accelerated-symmetric-condensed-node-tlm-procedure-for-nvidia-graphics-processing-units","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=4500","title":{"rendered":"Hardware accelerated symmetric condensed node TLM procedure for NVIDIA graphics processing units"},"content":{"rendered":"<p>Recent advances in graphics computing technology has brought highly parallel processing power to personal computers. This paper reports a hardware-accelerated symmetrical condensed node TLM procedure for the NVIDIA graphics processing units. The procedure has been tested on three NVIDIA processors, from laptop graphics card to workstation graphics processors.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Recent advances in graphics computing technology has brought highly parallel processing power to personal computers. This paper reports a hardware-accelerated symmetrical condensed node TLM procedure for the NVIDIA graphics processing units. The procedure has been tested on three NVIDIA processors, from laptop graphics card to workstation graphics processors.<\/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":[89,319,3],"tags":[14,1802,323,322,20,374,224,1011],"class_list":["post-4500","post","type-post","status-publish","format-standard","hentry","category-nvidia-cuda","category-electrodynamics","category-paper","tag-cuda","tag-electrodynamics","tag-fdtd","tag-finite-difference-time-domain","tag-nvidia","tag-nvidia-geforce-8800-ultra","tag-nvidia-quadro-fx-5600","tag-nvidia-quadro-fx-570-m"],"views":2268,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4500","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=4500"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4500\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4500"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4500"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4500"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}