Efficient Point Merging Using Data Parallel Techniques

Date and time: 
Tuesday, June 11, 2019 - 13:00
Location: 
220 Deschutes
Author(s):
Abhishek Yenpure
University of Oregon
Host/Committee: 
  • Hank Childs (Chair)
  • Boyana Norris
  • Jee Choi
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.