A Scalable, Hybrid Scheme for Volume Rendering Massive Data Sets

Childs, Hank; Duchaineau, Mark; Ma, Kwan-Liu

A Scalable, Hybrid Scheme for Volume Rendering Massive Data Sets

Files

153-161.pdf (284.13 KB)

Date

2006

Authors

Childs, Hank
Duchaineau, Mark
Ma, Kwan-Liu

Publisher

The Eurographics Association

Abstract

We introduce a parallel, distributed memory algorithm for volume rendering massive data sets. The algorithm's scalability has been demonstrated up to 400 processors, rendering one hundred million unstructured elements in under one second. The heart of the algorithm is a hybrid approach that parallelizes over both the elements of the input data and over the pixels of the output image. At each stage of the algorithm, there are strong limits on how much work each processor performs, ensuring good parallel efficiency. The algorithm is sample-based. We present two techniques for calculating the sample points: a 3D rasterization technique and a kernel-based technique, which trade off between speed and generality. Finally, the algorithm is very flexible. It can be deployed in general purpose visualization tools and can also support diverse mesh types, ranging from structured grids to curvilinear and unstructured meshes to point clouds.

        @inproceedings{:10.2312/EGPGV/EGPGV06/153-161
,
booktitle = {Eurographics Symposium on Parallel Graphics and Visualization
},
editor = {Alan Heirich and Bruno Raffin and Luis Paulo dos Santos
},
title = {{A Scalable, Hybrid Scheme for Volume Rendering Massive Data Sets
}},
author = {Childs, Hank and 
Duchaineau, Mark and 
Ma, Kwan-Liu
},
year = {2006
},
publisher = {The Eurographics Association
},
ISSN = {1727-348X
},
ISBN = {3-905673-40-1
},
DOI = {/10.2312/EGPGV/EGPGV06/153-161
}
}