{"id":11509,"date":"2014-03-01T01:20:21","date_gmt":"2014-02-28T23:20:21","guid":{"rendered":"http:\/\/hgpu.org\/?p=11509"},"modified":"2014-03-01T01:20:21","modified_gmt":"2014-02-28T23:20:21","slug":"applications-of-linux-based-qt-cuda-parallel-architecture","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=11509","title":{"rendered":"Applications of Linux-Based QT-CUDA Parallel Architecture"},"content":{"rendered":"<p>Joint programming of QT and CUDA is a urgent problem on Linux, a Linux-based QT-CUDA parallel architecture has been built creatively. As an example, an fast parallel rendering algorithm for seismic and GPR imaging is proposed and implemented based on the Linux QT-CUDA parallel architecture. It is proved that the parallel rendering algorithm is about ten times faster than conventional algorithm, which can be widely applied to fast visualization of different kinds of 2D data.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Joint programming of QT and CUDA is a urgent problem on Linux, a Linux-based QT-CUDA parallel architecture has been built creatively. As an example, an fast parallel rendering algorithm for seismic and GPR imaging is proposed and implemented based on the Linux QT-CUDA parallel architecture. It is proved that the parallel rendering algorithm is about [&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":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[36,89,33,3],"tags":[1787,14,1786,20,1548,182,144,134],"class_list":["post-11509","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-nvidia-cuda","category-image-processing","category-paper","tag-algorithms","tag-cuda","tag-image-processing","tag-nvidia","tag-nvidia-geforce-g-105-m","tag-opengl","tag-rendering","tag-visualization"],"views":2924,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/11509","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=11509"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/11509\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=11509"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=11509"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=11509"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}