{"id":7729,"date":"2012-06-10T23:21:36","date_gmt":"2012-06-10T20:21:36","guid":{"rendered":"http:\/\/hgpu.org\/?p=7729"},"modified":"2012-06-10T23:21:36","modified_gmt":"2012-06-10T20:21:36","slug":"s-buffer-sparsity-aware-multi-fragment-rendering","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=7729","title":{"rendered":"S-buffer: Sparsity-aware Multi-fragment Rendering"},"content":{"rendered":"<p>This work introduces S-buffer, an efficient and memory-friendly gpu-accelerated A-buffer architecture for multi-fragment rendering. Memory is organized into variable contiguous regions for each pixel, thus avoiding limitations set in linked-lists and fixed-array techniques. S-buffer exploits fragment distribution for precise allocation of the needed storage and pixel sparsity (empty pixel ratio) for computing the memory offsets for each pixel in a parallel fashion. An experimental comparative evaluation of our technique over previous multi-fragment rendering approaches in terms of memory and performance is provided.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This work introduces S-buffer, an efficient and memory-friendly gpu-accelerated A-buffer architecture for multi-fragment rendering. Memory is organized into variable contiguous regions for each pixel, thus avoiding limitations set in linked-lists and fixed-array techniques. S-buffer exploits fragment distribution for precise allocation of the needed storage and pixel sparsity (empty pixel ratio) for computing the memory offsets [&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":[1782,20,379,1793,182,176,144],"class_list":["post-7729","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-opencl","category-paper","tag-computer-science","tag-nvidia","tag-nvidia-geforce-gtx-480","tag-opencl","tag-opengl","tag-package","tag-rendering"],"views":2064,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/7729","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=7729"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/7729\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=7729"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=7729"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=7729"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}