H-PLOC: Hierarchical Parallel Locally-Ordered Clustering for Bounding Volume Hierarchy Construction
Carsten Benthin, Daniel Meister, Joshua Barczak, Rohan Mehalwal, John Tsakok, Andrew Kensler · Proceedings of the ACM on Computer Graphics and Interactive Techniques · 2024
We propose a novel GPU-oriented approach for constructing binary bounding volume hierarchies (BVHs) based on the parallel locally-ordered clustering (PLOC/PLOC++) algorithm. Compared to competing high-performance GPU BVH build algorithms (PLOC++ or ATRBVH), our method provides similar BVH quality in just a single kernel launch while achieving 1.1-3.6× lower construction times for the entire BVH build and 1.6-13× lower for just the binary BVH construction phase. Additionally, we propose an efficient algorithm to convert a binary BVH to an n-wide BVH with just a single kernel launch. Besides being extremely efficient, our proposed algorithms are simple to implement, allowing easy integration into existing frameworks.