Simpler and Faster HLBVH with Work Queues
A recently developed algorithm called Hierachical Linear Bounding Volume Hierarchies (HLBVH) has demonstrated the feasibility of reconstructing the spatial index needed for ray tracing in real-time, even in the presence of millions of fully dynamic triangles. In this work we present a simpler and faster variant of HLBVH, where all the complex bookkeeping of pre x sums, compaction and partial breadth- rst tree traversal needed for spatial partitioning has been replaced with an elegant pipeline built on top of ecient work queues and binary search. The new algorithm is both faster and more memory ecient, removing the need for temporary storage of geometry data for intermediate computations. Finally, the same pipeline has been extended to parallelize the construction of the top-level SAH optimized tree on the GPU, eliminating round-trips to the CPU, accelerating the overall construction speed by a factor of 5 to 10x.
Copyright by the Association for Computing Machinery, Inc. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Publications Dept, ACM Inc., fax +1 (212) 869-0481, or email@example.com. The definitive version of this paper can be found at ACM's Digital Library http://www.acm.org/dl/.