{"id":1286,"date":"2010-11-08T11:22:09","date_gmt":"2010-11-08T11:22:09","guid":{"rendered":"http:\/\/hgpu.org\/?p=1286"},"modified":"2010-11-08T11:22:09","modified_gmt":"2010-11-08T11:22:09","slug":"large-scale-mixer-simulations-using-massively-parallel-gpu-architectures","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=1286","title":{"rendered":"Large-scale mixer simulations using massively parallel GPU architectures"},"content":{"rendered":"<p>Granular flows are extremely important for the pharmaceutical and chemical industry, as well as for other scientific areas. Thus, the understanding of the impact of particle size and related effects on the mean, as well as on the fluctuating flow field, in granular flows is critical for design and optimization of powder processing operations. We use a specialized simulation tool written in C and CUDA (Compute Unified Device Architecture), a massive parallelization technique which runs on the Graphics Processing Unit (GPU). We focus on both, a new implementation approach using CUDA\/GPU, as well as on the flow fields and mixing properties obtained in the million<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Granular flows are extremely important for the pharmaceutical and chemical industry, as well as for other scientific areas. Thus, the understanding of the impact of particle size and related effects on the mean, as well as on the fluctuating flow field, in granular flows is critical for design and optimization of powder processing operations. We [&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":[66,89,3],"tags":[1790,14,20,558,620],"class_list":["post-1286","post","type-post","status-publish","format-standard","hentry","category-chemistry","category-nvidia-cuda","category-paper","tag-chemistry","tag-cuda","tag-nvidia","tag-pharmaceuticals","tag-powder-processing"],"views":2541,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/1286","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=1286"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/1286\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1286"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1286"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1286"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}