{"id":11539,"date":"2014-03-06T04:38:37","date_gmt":"2014-03-06T02:38:37","guid":{"rendered":"http:\/\/hgpu.org\/?p=11539"},"modified":"2014-03-06T04:38:37","modified_gmt":"2014-03-06T02:38:37","slug":"performance-tradeoff-spectrum-of-integer-and-floating-point-applications-kernels-on-various-gpus","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=11539","title":{"rendered":"Performance Tradeoff Spectrum of Integer and Floating Point Applications Kernels on Various GPUs"},"content":{"rendered":"<p>Floating point precision and performance and the ratio of floating point units to integer processing elements on a graphics processing unit accelerator all continue to present complex tradeoffs for optimising core utilisation on modern devices. We investigate various hybrid CPU and GPU combinations using a range of different GPU models occupying different points in this tradeoff space. We analyse some performance data for a range of numerical simulation kernels and discuss their use as benchmark problems for characterising such devices.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Floating point precision and performance and the ratio of floating point units to integer processing elements on a graphics processing unit accelerator all continue to present complex tradeoffs for optimising core utilisation on modern devices. We investigate various hybrid CPU and GPU combinations using a range of different GPU models occupying different points in this [&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":[11,89,3],"tags":[451,1782,14,20,253,379,974,1092,1549,1306,67,931,1017,1341,1241],"class_list":["post-11539","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-paper","tag-benchmarking","tag-computer-science","tag-cuda","tag-nvidia","tag-nvidia-geforce-gtx-260","tag-nvidia-geforce-gtx-480","tag-nvidia-geforce-gtx-580","tag-nvidia-geforce-gtx-590","tag-nvidia-geforce-gtx-660-m","tag-nvidia-geforce-gtx-680","tag-performance","tag-tesla-m2050","tag-tesla-m2070","tag-tesla-m2075","tag-tesla-m2090"],"views":2364,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/11539","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=11539"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/11539\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=11539"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=11539"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=11539"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}