Adaptive Tetrahedral Grids for Volumetric Path-Tracing

Fuente: arXiv
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Main Authors: Benyoub, Anis, Dupuy, Jonathan
Format: Preprint
Published: 2025
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author Benyoub, Anis
Dupuy, Jonathan
author_facet Benyoub, Anis
Dupuy, Jonathan
contents We advertise the use of tetrahedral grids constructed via the longest edge bisection algorithm for rendering volumetric data with path tracing. The key benefits of such grids is two-fold. First, they provide a highly adaptive space-partitioning representation that limits the memory footprint of volumetric assets. Second, each (tetrahedral) cell has exactly 4 neighbors within the volume (one per face of each tetrahedron) or less at boundaries. We leverage these properties to devise optimized algorithms and data-structures to compute and path-trace adaptive tetrahedral grids on the GPU. In practice, our GPU implementation outperforms regular grids by up to x30 and renders production assets in real time at 32 samples per pixel.
format Preprint
id arxiv_https___arxiv_org_abs_2506_11510
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Adaptive Tetrahedral Grids for Volumetric Path-Tracing
Benyoub, Anis
Dupuy, Jonathan
Graphics
We advertise the use of tetrahedral grids constructed via the longest edge bisection algorithm for rendering volumetric data with path tracing. The key benefits of such grids is two-fold. First, they provide a highly adaptive space-partitioning representation that limits the memory footprint of volumetric assets. Second, each (tetrahedral) cell has exactly 4 neighbors within the volume (one per face of each tetrahedron) or less at boundaries. We leverage these properties to devise optimized algorithms and data-structures to compute and path-trace adaptive tetrahedral grids on the GPU. In practice, our GPU implementation outperforms regular grids by up to x30 and renders production assets in real time at 32 samples per pixel.
title Adaptive Tetrahedral Grids for Volumetric Path-Tracing
topic Graphics
url https://arxiv.org/abs/2506.11510