Splatting is a popular technique for volume rendering, where voxels are represented by Gaussian kernels, whose pre-integrated footprints are accumulated to form the image. Splatting has been mainly used to render pre-shaded volumes, which can result in significant blurring in zoomed views. This can be avoided in the image-aligned splatting scheme, where one accumulates kernel slices into equi-distant, parallel sheet buffers, followed by classification, shading, and compositing. In this work, we attempt to evolve this algorithm to the next level: GPU (graphics processing unit) based acceleration. First we describe the challenges that the highly parallel "Gather" architecture of modern GPUs poses to the "Scatter" based nature of a splatting algorithm. We then describe a number of strategies that exploit newly introduced features of the latest-generation hardware to address these limitations. Two crucial operations to boost the performance in image-aligned splatting are the early elimination of hidden splats and the skipping of empty buffer-space. We describe mechanisms which take advantage of the early z-culling hardware facilities to accomplish both of these operations efficiently in hardware.<\/p>\n","protected":false},"excerpt":{"rendered":"
Splatting is a popular technique for volume rendering, where voxels are represented by Gaussian kernels, whose pre-integrated footprints are accumulated to form the image. Splatting has been mainly used to render pre-shaded volumes, which can result in significant blurring in zoomed views. This can be avoided in the image-aligned splatting scheme, where one accumulates kernel […]<\/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":[11,3],"tags":[1782,168,20,420,144],"class_list":["post-962","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-paper","tag-computer-science","tag-image-aligned-splatting","tag-nvidia","tag-nvidia-quadro-fx-3400","tag-rendering"],"views":2814,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/962","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=962"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/962\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=962"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=962"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=962"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}