Efficient Point Merging Using Data Parallel Techniques
| dc.contributor.author | Yenpure, Abhishek | en_US |
| dc.contributor.author | Childs, Hank | en_US |
| dc.contributor.author | Moreland, Kenneth | en_US |
| dc.contributor.editor | Childs, Hank and Frey, Steffen | en_US |
| dc.date.accessioned | 2019-06-02T18:26:06Z | |
| dc.date.available | 2019-06-02T18:26:06Z | |
| dc.date.issued | 2019 | |
| dc.description.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. | en_US |
| dc.description.sectionheaders | Session 3 | |
| dc.description.seriesinformation | Eurographics Symposium on Parallel Graphics and Visualization | |
| dc.identifier.doi | 10.2312/pgv.20191112 | |
| dc.identifier.isbn | 978-3-03868-079-6 | |
| dc.identifier.issn | 1727-348X | |
| dc.identifier.pages | 79-88 | |
| dc.identifier.uri | https://doi.org/10.2312/pgv.20191112 | |
| dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/pgv20191112 | |
| dc.publisher | The Eurographics Association | en_US |
| dc.subject | Computing methodologies | |
| dc.subject | Shared memory algorithms | |
| dc.subject | Scientific visualization | |
| dc.subject | Computer graphics | |
| dc.title | Efficient Point Merging Using Data Parallel Techniques | en_US |