Simpler and Faster HLBVH with Work Queues

Abstract

A recently developed algorithm called Hierachical Linear Bounding Volume Hierarchies (HLBVH) has demonstrated the feasibility of reconstructing the spatial index needed forray 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 bookkeepingof 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 e cient work queues and binary search. The new algorithm is both faster and more memory e cient, 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.