{"id":13863,"date":"2015-04-15T17:33:49","date_gmt":"2015-04-15T14:33:49","guid":{"rendered":"http:\/\/hgpu.org\/?p=13863"},"modified":"2015-04-15T17:33:49","modified_gmt":"2015-04-15T14:33:49","slug":"collaborative-diffusion-on-the-gpu-for-path-finding-in-games","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=13863","title":{"rendered":"Collaborative Diffusion on the GPU for Path-Finding in Games"},"content":{"rendered":"<p>Exploiting the powerful processing power available on the GPU in many machines, we investigate the performance of parallelised versions of pathfinding algorithms in typical game environments. We describe a parallel implementation of a collaborative diffusion algorithm that is shown to find short paths in real-time across a range of graph sizes and provide a comparison to the well known Dijkstra and A* algorithms. Although some trade-off of cost vs path-length is observed under specific environmental conditions, results show that it is a viable contender for pathfinding in typical real-time game scenarios, freeing up CPU computation for other aspects of game AI.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Exploiting the powerful processing power available on the GPU in many machines, we investigate the performance of parallelised versions of pathfinding algorithms in typical game environments. We describe a parallel implementation of a collaborative diffusion algorithm that is shown to find short paths in real-time across a range of graph sizes and provide a comparison [&hellip;]<\/p>\n","protected":false},"author":659,"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":[36,89,3],"tags":[1733,1787,14,539,1734,441],"class_list":["post-13863","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-nvidia-cuda","category-paper","tag-ai","tag-algorithms","tag-cuda","tag-games","tag-graph","tag-search"],"views":3149,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/13863","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\/659"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=13863"}],"version-history":[{"count":2,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/13863\/revisions"}],"predecessor-version":[{"id":13865,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/13863\/revisions\/13865"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=13863"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=13863"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=13863"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}