{"id":9660,"date":"2013-06-26T23:56:37","date_gmt":"2013-06-26T20:56:37","guid":{"rendered":"http:\/\/hgpu.org\/?p=9660"},"modified":"2013-06-26T23:56:37","modified_gmt":"2013-06-26T20:56:37","slug":"using-of-new-possibilities-of-fermi-architecture-by-development-of-gpgpu-programs","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=9660","title":{"rendered":"Using of New Possibilities of Fermi Architecture by Development of GPGPU Programs"},"content":{"rendered":"<p>Description of additional functions of hardware and software, which are presented in the structure of new architecture of FERMI graphic processors made by company NVIDIA, was given. Recommendations of their use within the realization of algorithms of scientific and technical calculations by means of the graphic processors were given. Application of the new possibilities of FERMI architecture and CUDA technologies (Compute Unified Device Architecture &#8211; unified hardware-software decision for parallel calculations on GPU) of NVIDIA Company was described. It was done for time reduction of applications&#8217; development which is using possibilities of GPGPU for acceleration of data processing.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Description of additional functions of hardware and software, which are presented in the structure of new architecture of FERMI graphic processors made by company NVIDIA, was given. Recommendations of their use within the realization of algorithms of scientific and technical calculations by means of the graphic processors were given. Application of the new possibilities of [&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":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[11,89,3],"tags":[1782,14,20,932],"class_list":["post-9660","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-paper","tag-computer-science","tag-cuda","tag-nvidia","tag-overview"],"views":1956,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/9660","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=9660"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/9660\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=9660"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=9660"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=9660"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}