{"id":3475,"date":"2011-04-06T20:20:06","date_gmt":"2011-04-06T20:20:06","guid":{"rendered":"http:\/\/hgpu.org\/?p=3475"},"modified":"2011-04-06T20:20:06","modified_gmt":"2011-04-06T20:20:06","slug":"high-speed-electromagnetic-field-simulation-by-hie-fdtd-method-with-gpgpu","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=3475","title":{"rendered":"High-speed electromagnetic field simulation by HIE-FDTD method with GPGPU"},"content":{"rendered":"<p>The HIE(Hybrid Implicit-Explicit)-FDTD method is very useful for the simulation of computational domain with thin cells. This paper describes the HIE-FDTD method with GPGPU(General Purpose computing on Graphic Processing Unit) for massively parallel electromagnetic field simulation. First, the properties of the HIE-FDTD method are explained. Next, 3D HIE-FDTD method with CUDA is implemented. Finally, it is shown that the performance of the HIE-FDTD method by GPGPU is much superior to the HIE-FDTD method with single CPU.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The HIE(Hybrid Implicit-Explicit)-FDTD method is very useful for the simulation of computational domain with thin cells. This paper describes the HIE-FDTD method with GPGPU(General Purpose computing on Graphic Processing Unit) for massively parallel electromagnetic field simulation. First, the properties of the HIE-FDTD method are explained. Next, 3D HIE-FDTD method with CUDA is implemented. Finally, it [&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":[89,319,3],"tags":[14,1802,322,20],"class_list":["post-3475","post","type-post","status-publish","format-standard","hentry","category-nvidia-cuda","category-electrodynamics","category-paper","tag-cuda","tag-electrodynamics","tag-finite-difference-time-domain","tag-nvidia"],"views":1769,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/3475","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=3475"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/3475\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3475"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3475"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3475"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}