{"id":10108,"date":"2013-07-22T22:50:50","date_gmt":"2013-07-22T19:50:50","guid":{"rendered":"http:\/\/hgpu.org\/?p=10108"},"modified":"2013-07-22T22:50:50","modified_gmt":"2013-07-22T19:50:50","slug":"performance-evaluation-of-the-ocean-land-atmosphere-model-using-graphics-processing-units","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=10108","title":{"rendered":"Performance Evaluation of the Ocean-Land-Atmosphere Model Using Graphics Processing Units"},"content":{"rendered":"<p>The Ocean-Land-Atmosphere Model (OLAM) is an atmospheric model to simulate and cover all Earth surface. OLAM demands a great amount of processing in a simulation because of the large number of data structures used to represent the atmosphere. Because of this, we investigate in this paper how to increase performance using GPUs to compute the model. A prototype of OLAM was developed including the call of CUDA threads in order to explore GPU parallelism. Performance evaluations of some atmospheric simulations show that the use of CUDA threads increases significantly the performance of this atmospheric model.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The Ocean-Land-Atmosphere Model (OLAM) is an atmospheric model to simulate and cover all Earth surface. OLAM demands a great amount of processing in a simulation because of the large number of data structures used to represent the atmosphere. Because of this, we investigate in this paper how to increase performance using GPUs to compute the [&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":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[89,303,3],"tags":[14,1801,20,244],"class_list":["post-10108","post","type-post","status-publish","format-standard","hentry","category-nvidia-cuda","category-earth-and-space-sciences","category-paper","tag-cuda","tag-earth-and-space-sciences","tag-nvidia","tag-tesla-s1070"],"views":2072,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/10108","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=10108"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/10108\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=10108"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=10108"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=10108"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}