{"id":10026,"date":"2013-07-15T00:00:11","date_gmt":"2013-07-14T21:00:11","guid":{"rendered":"http:\/\/hgpu.org\/?p=10026"},"modified":"2013-07-15T00:00:11","modified_gmt":"2013-07-14T21:00:11","slug":"exploiting-space-and-time-coherence-in-grid-based-sorting","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=10026","title":{"rendered":"Exploiting Space and Time Coherence in Grid-based Sorting"},"content":{"rendered":"<p>In recent years, many approaches for real-time simulation of physical phenomena using particles have been proposed. Many of these use 3D grids for representing spatial distributions and employ a collision detection technique where particles must be sorted with respect to the cells they occupy. In this paper we propose several techniques that make it possible to explore spatio-temporal coherence in order to reduce the work needed to produce a correct ordering and thus accelerate the collision detection phase of the simulation. Sequential and GPU-based implementations are discussed, and experimental results are presented. Although devised with particle-based simulations in mind, the proposed techniques have a broader scope, requiring only some means of establishing subsequences of the input which did not change from one frame to the next.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In recent years, many approaches for real-time simulation of physical phenomena using particles have been proposed. Many of these use 3D grids for representing spatial distributions and employ a collision detection technique where particles must be sorted with respect to the cells they occupy. In this paper we propose several techniques that make it possible [&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":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[36,11,90,3],"tags":[1787,7,455,137,1782,20,1268,1793,286,9],"class_list":["post-10026","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-computer-science","category-opencl","category-paper","tag-algorithms","tag-ati","tag-ati-radeon-hd-5870","tag-collision-detection","tag-computer-science","tag-nvidia","tag-nvidia-geforce-gt-540-m","tag-opencl","tag-particle-simulation","tag-sorting"],"views":3241,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/10026","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=10026"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/10026\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=10026"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=10026"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=10026"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}