{"id":12363,"date":"2014-06-25T08:48:38","date_gmt":"2014-06-25T05:48:38","guid":{"rendered":"http:\/\/hgpu.org\/?p=12363"},"modified":"2014-06-25T08:48:38","modified_gmt":"2014-06-25T05:48:38","slug":"gpu-parallel-simulation-of-rigid-fibers-in-stokes-flow","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=12363","title":{"rendered":"GPU-Parallel simulation of rigid fibers in Stokes flow"},"content":{"rendered":"<p>The simulation of a fiber suspension requires that all interactions between the fibers involved are computed. This is a compute-intensive N-body problem that is highly data parallel. Using the GPU for these types of computations can be very beneficial. In this thesis an extension to a simulator, written in MATLAB, for rigid fibers in Stokes flow was designed and implemented to improve the performance of the simulator. A part of the simulator responsible for computing these fiber-to-fiber interactions was ported to the GPU using the CUDA programming language dedicated to general-purpose computing on GPUs. To accomplish this an interface to MATLAB was created and the portion of code to be ported was parallelized and adapted in a way suitable to the GPU. The ported code proved to be 16 times faster than the original implementation.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The simulation of a fiber suspension requires that all interactions between the fibers involved are computed. This is a compute-intensive N-body problem that is highly data parallel. Using the GPU for these types of computations can be very beneficial. In this thesis an extension to a simulator, written in MATLAB, for rigid fibers in Stokes [&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":[11,89,3],"tags":[1782,14,258,20,253,390],"class_list":["post-12363","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-paper","tag-computer-science","tag-cuda","tag-n-body-simulation","tag-nvidia","tag-nvidia-geforce-gtx-260","tag-thesis"],"views":2195,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/12363","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=12363"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/12363\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=12363"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=12363"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=12363"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}