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.

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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
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article

H-PLOC: Hierarchical Parallel Locally-Ordered Clustering for Bounding Volume Hierarchy Construction

Daniel Meister, Andrew Kensler, Joshua Barczak, Carsten Benthin et al.
7 citations
Proceedings of the ACM on Computer Graphics and Interactive Techniques
Advanced Image and Video Retrieval Techniques
1.74
article

H-PLOC: Hierarchical Parallel Locally-Ordered Clustering for Bounding Volume Hierarchy Construction

Daniel Meister, Andrew Kensler, Joshua Barczak, Carsten Benthin, John Tsakok, Rohan Mehalwal
article en
7 citations

Abstract

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.

Proceedings of the ACM on Computer Graphics and Interactive TechniquesVol. 7(3)
Advanced Micro Devices (United States) (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 14%
Advanced Image and Video Retrieval Techniques
1.74
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H-PLOC: Hierarchical Parallel Locally-Ordered Clustering for Bounding Volume Hierarchy Construction — Daniel Meister, Andrew Kensler, et al. · Proceedings of the ACM on Computer Graphics and Interactive Techniques (2024) | TGRS Research Map | TGRS