{"id":14024,"date":"2015-05-20T23:36:28","date_gmt":"2015-05-20T20:36:28","guid":{"rendered":"http:\/\/hgpu.org\/?p=14024"},"modified":"2015-05-20T23:36:28","modified_gmt":"2015-05-20T20:36:28","slug":"a-performance-and-scalability-analysis-of-the-tsunami-simulation-easywave-for-different-multi-core-architectures-and-programming-models","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=14024","title":{"rendered":"A Performance and Scalability Analysis of the Tsunami Simulation EasyWave for Different Multi-Core Architectures and Programming Models"},"content":{"rendered":"<p>In this paper, the performance and scalability of different multi-core systems is experimentally evaluated for the Tsunami simulation EasyWave. The target platforms include a standard Ivy Bridge Xeon processor, an Intel Xeon Phi accelerator card, and also a GPU. OpenMP, MPI and CUDA were used to parallelize the program to these platforms. The absolute performance of the application on the different platforms is compared, and limiting factors are analyzed based on the application&#8217;s scaling behavior.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this paper, the performance and scalability of different multi-core systems is experimentally evaluated for the Tsunami simulation EasyWave. The target platforms include a standard Ivy Bridge Xeon processor, an Intel Xeon Phi accelerator card, and also a GPU. OpenMP, MPI and CUDA were used to parallelize the program to these platforms. The absolute performance [&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":[89,303,192,3],"tags":[14,1801,1798,1483,242,20,252,176,67,1543],"class_list":["post-14024","post","type-post","status-publish","format-standard","hentry","category-nvidia-cuda","category-earth-and-space-sciences","category-geoscience","category-paper","tag-cuda","tag-earth-and-space-sciences","tag-geoscience","tag-intel-xeon-phi","tag-mpi","tag-nvidia","tag-openmp","tag-package","tag-performance","tag-tesla-k40"],"views":2695,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/14024","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=14024"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/14024\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=14024"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=14024"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=14024"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}