{"id":6998,"date":"2012-01-23T00:00:35","date_gmt":"2012-01-22T22:00:35","guid":{"rendered":"http:\/\/hgpu.org\/?p=6998"},"modified":"2012-01-23T00:00:35","modified_gmt":"2012-01-22T22:00:35","slug":"a-new-approach-to-rcuda","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=6998","title":{"rendered":"A New Approach to rCUDA"},"content":{"rendered":"<p>In this paper we propose a first step towards a general and open source approach for using GPGPU (General-Purpose Computation on GPUs) features within virtual machines (VMs). In particular, we describe the use of rCUDA, a GPGPU virtualization framework, to permit the execution of GPU-accelerated applications within VMs, thus enabling GPGPU capabilities on any virtualized environment. Our experiments with rCUDA in the context of KVM and VirtualBox on a system equipped with two NVIDIA GeForce 9800 GX2 cards illustrate the overhead introduced by the rCUDA middleware and prove the feasibility and scalability of this general virtualizing solution.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this paper we propose a first step towards a general and open source approach for using GPGPU (General-Purpose Computation on GPUs) features within virtual machines (VMs). In particular, we describe the use of rCUDA, a GPGPU virtualization framework, to permit the execution of GPU-accelerated applications within VMs, thus enabling GPGPU capabilities on any virtualized [&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":[11,89,3],"tags":[1782,14,20,311,167],"class_list":["post-6998","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-paper","tag-computer-science","tag-cuda","tag-nvidia","tag-nvidia-geforce-9800-gx2","tag-virtualization"],"views":2247,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/6998","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=6998"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/6998\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=6998"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=6998"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=6998"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}