{"id":17125,"date":"2017-04-11T22:44:45","date_gmt":"2017-04-11T19:44:45","guid":{"rendered":"https:\/\/hgpu.org\/?p=17125"},"modified":"2017-04-11T22:44:45","modified_gmt":"2017-04-11T19:44:45","slug":"a-modular-gpu-raytracer-using-opencl-for-non-interactive-graphics","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=17125","title":{"rendered":"A modular GPU raytracer using OpenCL for non-interactive graphics"},"content":{"rendered":"<p>We describe the development of a modular plugin based raytracer renderer called RenderGirl suitable for running inside the OpenCL framework. We aim to take advantage of heterogeneous computing devices such as GPUs and many-core CPUs, focusing on parallelism. We implemented the traditional partitioning scheme called bounding volume hierarchies, where each scene is hierarchically subdivided into axis-aligned bounding boxes, so a ray may only need to traverse a subset of geometry by traversing the BVH and discarding objects it surely cannot hit, optimizing the rendering process. These structures were implemented on a many-core high parallel architecture suitable for OpenCL, which needed a specific binary tree structure implementation ready for stackless traversal on GPUs. RenderGirl is split between two main portions: Core and Interface, where the Core portions provide the bulk of ray-tracing operations and manage the communication with OpenCL; and the interfaces provide communication with a given host program, seeking modularity. In this paper we describe our results and performance gains with our partitioning scheme.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We describe the development of a modular plugin based raytracer renderer called RenderGirl suitable for running inside the OpenCL framework. We aim to take advantage of heterogeneous computing devices such as GPUs and many-core CPUs, focusing on parallelism. We implemented the traditional partitioning scheme called bounding volume hierarchies, where each scene is hierarchically subdivided into [&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":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[11,90,3],"tags":[1782,452,20,1779,1793,176,181,144],"class_list":["post-17125","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-opencl","category-paper","tag-computer-science","tag-heterogeneous-systems","tag-nvidia","tag-nvidia-geforce-gtx-970","tag-opencl","tag-package","tag-raytracing","tag-rendering"],"views":2530,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/17125","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=17125"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/17125\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=17125"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=17125"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=17125"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}