H-PLOC: Hierarchical Parallel Locally-Ordered Clustering for Bounding Volume Hierarchy Construction
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.
Authors
- Daniel Meister (ORCID: https://orcid.org/0000-0002-3149-1442)
- Andrew Kensler
- Joshua Barczak (ORCID: https://orcid.org/0009-0002-0630-7612)
- Carsten Benthin (ORCID: https://orcid.org/0000-0003-3337-1636)
- John Tsakok
- Rohan Mehalwal
Institutions
- Advanced Micro Devices (United States) (US)
Publication Details
- Journal
- Proceedings of the ACM on Computer Graphics and Interactive Techniques
- Published
- 2024-08-09
- DOI
- https://doi.org/10.1145/3675377
- Citations
- 7
- Primary Topic
- Advanced Image and Video Retrieval Techniques
- Type
- article
- Field-Weighted Citation Impact
- 1.74