Finding Efficient Spatial Distributions for Massively Instanced 3-d Models
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Date
2020
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Instancing is commonly used to reduce the memory footprint of massive 3-d models. Nevertheless, large production assets often do not fit into the memory allocated to a single rendering node or into the video memory of a single GPU. For memory intensive scenes like these, distributed rendering can be helpful. However, finding efficient data distributions for these instanced 3-d models is challenging, since a memory-efficient data distribution often results in an inefficient spatial distribution, and vice versa. Therefore, we propose a k-d tree construction algorithm that balances these two opposing goals and evaluate our scene distribution approach using publicly available instanced 3-d models like Disney's Moana Island Scene.
Description
@inproceedings{10.2312:pgv.20201070,
booktitle = {Eurographics Symposium on Parallel Graphics and Visualization},
editor = {Frey, Steffen and Huang, Jian and Sadlo, Filip},
title = {{Finding Efficient Spatial Distributions for Massively Instanced 3-d Models}},
author = {Zellmann, Stefan and Morrical, Nate and Wald, Ingo and Pascucci, Valerio},
year = {2020},
publisher = {The Eurographics Association},
ISSN = {1727-348X},
ISBN = {978-3-03868-107-6},
DOI = {10.2312/pgv.20201070}
}