{"id":8153,"date":"2012-09-04T12:47:16","date_gmt":"2012-09-04T09:47:16","guid":{"rendered":"http:\/\/hgpu.org\/?p=8153"},"modified":"2012-09-04T12:47:16","modified_gmt":"2012-09-04T09:47:16","slug":"accelerating-distance-matrix-calculations-utilizing-gpu","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=8153","title":{"rendered":"Accelerating distance matrix calculations utilizing GPU"},"content":{"rendered":"<p>When modeling pedestrian movement, it is necessary to find a path to the target point. It is possible to use a distance matrix or derived gradient map for this purpose. Calculations of distance matrix for large areas and multiple targets are very time-consuming. Therefore this article focuses on acceleration of these calculations utilizing Graphics Processing Units (GPUs). Despite of the fact, that these calculations are not well suited for the GPU, it was possible to accelerate it significantly. The OpenCL technology was used.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>When modeling pedestrian movement, it is necessary to find a path to the target point. It is possible to use a distance matrix or derived gradient map for this purpose. Calculations of distance matrix for large areas and multiple targets are very time-consuming. Therefore this article focuses on acceleration of these calculations utilizing Graphics Processing [&hellip;]<\/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":[11,90,3],"tags":[1782,20,1349,1793],"class_list":["post-8153","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-opencl","category-paper","tag-computer-science","tag-nvidia","tag-nvidia-geforce-gt-420-m","tag-opencl"],"views":2805,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8153","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=8153"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8153\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=8153"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=8153"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=8153"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}