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.
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@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
} }
Citation