GVDB: Raytracing Sparse Voxel Database Structures on the GPU

Hoetzlein, Rama Karl

GVDB: Raytracing Sparse Voxel Database Structures on the GPU

Files

109-117.pdf (6.54 MB)

gvdb_15mbps.mp4 (302.65 MB)

Date

2016

Authors

Hoetzlein, Rama Karl

Publisher

The Eurographics Association

Abstract

Simulation and rendering of sparse volumetric data have different constraints and solutions depending on the application area. Generating precise simulations and understanding very large data are problems in scientific visualization, whereas convincing simulations and realistic visuals are challenges in motion pictures. Both require volumes with dynamic topology, very large domains, and efficient high quality rendering.We present the GPU voxel database structure, GVDB, based on the voxel database topology of Museth [Mus13], as a method for efficient GPU-based compute and raytracing on a sparse hierarchy of grids. GVDB introduces an indexed memory pooling design for dynamic topology, and a novel hierarchical traversal for efficient raytracing on the GPU. Examples are provided for ray sampling of volumetric data, rendering of isosurfaces with multiple scattering, and raytracing of level sets. We demonstrate that GVDB can give large performance improvements over CPU methods with identical quality.

        @inproceedings{10.2312:hpg.20161197
,
booktitle = {Eurographics/ ACM SIGGRAPH Symposium on High Performance Graphics
},
editor = {Ulf Assarsson and Warren Hunt
},
title = {{GVDB: Raytracing Sparse Voxel Database Structures on the GPU
}},
author = {Hoetzlein, Rama Karl
},
year = {2016
},
publisher = {The Eurographics Association
},
ISSN = {2079-8679
},
ISBN = {978-3-03868-008-6
},
DOI = {10.2312/hpg.20161197
}
}