{"id":3458,"date":"2011-04-05T15:19:57","date_gmt":"2011-04-05T15:19:57","guid":{"rendered":"http:\/\/hgpu.org\/?p=3458"},"modified":"2011-04-05T15:19:57","modified_gmt":"2011-04-05T15:19:57","slug":"gpgpu-fdtd-method-for-2-dimensional-electromagnetic-field-simulation-and-its-estimation","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=3458","title":{"rendered":"GPGPU-FDTD method for 2-dimensional electromagnetic field simulation and its estimation"},"content":{"rendered":"<p>For signal\/power integrity analysis of the high density packages and printed circuit boards, the FDTD (Finite-Difference Time-Domain) method has been widely used. In order to apply to large-scale problems, a variety of acceleration techniques are required. This paper describes a GPGPU-FDTD (General Purpose computing on GPU (Graphic Processing Unit)-Finite-Difference Time-Domain) method for massively parallel electromagnetic field simulation. Finally, it is confirmed that GPGPU-FDTD method shows the high-performance when the computational algorithm is programmed suitably for the architecture of GPU.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>For signal\/power integrity analysis of the high density packages and printed circuit boards, the FDTD (Finite-Difference Time-Domain) method has been widely used. In order to apply to large-scale problems, a variety of acceleration techniques are required. This paper describes a GPGPU-FDTD (General Purpose computing on GPU (Graphic Processing Unit)-Finite-Difference Time-Domain) method for massively parallel electromagnetic [&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":[3],"tags":[514,323,322],"class_list":["post-3458","post","type-post","status-publish","format-standard","hentry","category-paper","tag-computational-engineering","tag-fdtd","tag-finite-difference-time-domain"],"views":1847,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/3458","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=3458"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/3458\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3458"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3458"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3458"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}