{"id":14299,"date":"2015-07-24T23:40:37","date_gmt":"2015-07-24T20:40:37","guid":{"rendered":"http:\/\/hgpu.org\/?p=14299"},"modified":"2015-07-24T23:40:37","modified_gmt":"2015-07-24T20:40:37","slug":"comparison-between-gpu-and-parallel-cpu-optimizations-in-viewshed-analysis","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=14299","title":{"rendered":"Comparison between GPU and parallel CPU optimizations in viewshed analysis"},"content":{"rendered":"<p>Parallel CPU implementations of a viewshed algorithm using both multithreading and SIMD vectorization and GPU implementations were implemented and compared in this study. The results show that parallelism is essential for achieving good performance on a CPU, and that data transfer can be partly overlapped by computations to hide some of the overheads in GPU implementations. The GPU implementation was the fastest with a performance approximately 3 times faster than the parallel CPU implementation for the hardware the tests were performed on.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Parallel CPU implementations of a viewshed algorithm using both multithreading and SIMD vectorization and GPU implementations were implemented and compared in this study. The results show that parallelism is essential for achieving good performance on a CPU, and that data transfer can be partly overlapped by computations to hide some of the overheads in GPU [&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":[36,11,90,3],"tags":[1787,1782,20,1549,1793,390],"class_list":["post-14299","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-computer-science","category-opencl","category-paper","tag-algorithms","tag-computer-science","tag-nvidia","tag-nvidia-geforce-gtx-660-m","tag-opencl","tag-thesis"],"views":2498,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/14299","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=14299"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/14299\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=14299"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=14299"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=14299"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}