Efficient Point Merging Using Data Parallel Techniques

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Date
2019
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
We study the problem of merging three-dimensional points that are nearby or coincident. We introduce a fast, efficient approach that uses data parallel techniques for execution in various shared-memory environments. Our technique incorporates a heuristic for efficiently clustering spatially close points together, which is one reason our method performs well against other methods. We then compare our approach against methods of a widely-used scientific visualization library accompanied by a performance study that shows our approach works well with different kinds of parallel hardware (many-core CPUs and NVIDIA GPUs) and data sets of various sizes.
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@inproceedings{
10.2312:pgv.20191112
, booktitle = {
Eurographics Symposium on Parallel Graphics and Visualization
}, editor = {
Childs, Hank and Frey, Steffen
}, title = {{
Efficient Point Merging Using Data Parallel Techniques
}}, author = {
Yenpure, Abhishek
and
Childs, Hank
and
Moreland, Kenneth
}, year = {
2019
}, publisher = {
The Eurographics Association
}, ISSN = {
1727-348X
}, ISBN = {
978-3-03868-079-6
}, DOI = {
10.2312/pgv.20191112
} }
Citation