{"id":7816,"date":"2012-06-27T22:04:59","date_gmt":"2012-06-27T19:04:59","guid":{"rendered":"http:\/\/hgpu.org\/?p=7816"},"modified":"2012-06-27T22:04:59","modified_gmt":"2012-06-27T19:04:59","slug":"explicit-shallow-water-simulations-on-gpus-guidelines-and-best-practices","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=7816","title":{"rendered":"Explicit Shallow Water Simulations on GPUs: Guidelines and Best Practices"},"content":{"rendered":"<p>Graphics processing units have now been used for scientific calculations for over a decade, going from early proof-of-concepts to industrial use today. The inherent reason is that graphics processors are far more powerful than CPUs when it comes to both floating point operations and memory bandwidth, illustrated by the fact that three of the top 500 supercomputers in the world now use GPU acceleration. In this paper, we present guidelines and best practices for harvesting the power of graphics processing units for shallow water simulations through stencil computations.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Graphics processing units have now been used for scientific calculations for over a decade, going from early proof-of-concepts to industrial use today. The inherent reason is that graphics processors are far more powerful than CPUs when it comes to both floating point operations and memory bandwidth, illustrated by the fact that three of the top [&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":[1782,14,20,974],"class_list":["post-7816","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-gtx-580"],"views":1737,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/7816","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=7816"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/7816\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=7816"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=7816"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=7816"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}