Currently there is considerable interest in making use of many-core processor architectures, such as Nvidia and AMD graphics processing units (GPUs) for scientific computing. In this work we explore the use of the Open Computing Language (OpenCL) for a typical Numerical Relativity application: a time-domain Teukolsky equation solver (a linear, hyperbolic, partial differential equation solver using finite-differencing). OpenCL is the only vendor-agnostic and multi-platform parallel computing framework that has been adopted by all major processor vendors. Therefore, it allows us to write portable source-code and run it on a wide variety of compute hardware and perform meaningful comparisons. The outcome of our experimentation suggests that it is relatively straightforward to obtain order-of-magnitude gains in overall application performance by making use of many-core GPUs over multi-core CPUs and this fact is largely independent of the specific hardware architecture and vendor. We also observe that a single high-end GPU can match the performance of a small-sized, message-passing based CPU cluster.<\/p>\n","protected":false},"excerpt":{"rendered":"
Currently there is considerable interest in making use of many-core processor architectures, such as Nvidia and AMD graphics processing units (GPUs) for scientific computing. In this work we explore the use of the Open Computing Language (OpenCL) for a typical Numerical Relativity application: a time-domain Teukolsky equation solver (a linear, hyperbolic, partial differential equation solver […]<\/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":[96,90,3],"tags":[1794,7,455,98,175,20,1793,252,378],"class_list":["post-1386","post","type-post","status-publish","format-standard","hentry","category-astrophysics","category-opencl","category-paper","tag-astrophysics","tag-ati","tag-ati-radeon-hd-5870","tag-computational-physics","tag-general-relativity-and-quantum-cosmology","tag-nvidia","tag-opencl","tag-openmp","tag-tesla-c2050"],"views":2649,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/1386","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=1386"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/1386\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1386"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1386"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1386"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}