{"id":11708,"date":"2014-03-22T20:42:09","date_gmt":"2014-03-22T18:42:09","guid":{"rendered":"http:\/\/hgpu.org\/?p=11708"},"modified":"2014-03-22T20:42:09","modified_gmt":"2014-03-22T18:42:09","slug":"cuda-implementation-of-a-lattice-boltzmann-method-and-code-optimization","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=11708","title":{"rendered":"CUDA Implementation of a Lattice Boltzmann Method and Code Optimization"},"content":{"rendered":"<p>We study fluid flow in a 2D lid driven cavity for large Reynolds numbers using multirelaxation time &#8211; Lattice Boltzmann Method(LBM). LBM is an alternative to conventional CFD methods that solve Navier-Stokes equations to simulate incompressible fluid dynamics. In LBM, one solves the linearized  Boltzmann equation on a discrete lattice to study spatio-temporal evolution of flow field. The data parallel implementation of the Lattice Boltzmann Method makes the GPGPU as a platform of choice for such computation. Several CUDA optimizations are implemented to achieve desired performance, these are discussed below.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We study fluid flow in a 2D lid driven cavity for large Reynolds numbers using multirelaxation time &#8211; Lattice Boltzmann Method(LBM). LBM is an alternative to conventional CFD methods that solve Navier-Stokes equations to simulate incompressible fluid dynamics. In LBM, one solves the linearized Boltzmann equation on a discrete lattice to study spatio-temporal evolution 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":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[89,104,3],"tags":[14,1795,108,20,1226],"class_list":["post-11708","post","type-post","status-publish","format-standard","hentry","category-nvidia-cuda","category-fluid-dynamics","category-paper","tag-cuda","tag-fluid-dynamics","tag-lattice-boltzmann-model","tag-nvidia","tag-tesla-c2075"],"views":2539,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/11708","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=11708"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/11708\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=11708"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=11708"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=11708"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}