Name
Abstract | ||
|---|---|---|
This paper presents a novel approach to compute, for a given point set S in R2, its Delaunay triangulation T (S). Though prior work mentions the possibility of using the graphics processing unit (GPU) to compute Delaunay triangulations, no known implementation and performance have been reported. Our work uncovers various challenges in the use of GPU for such a purpose. In practice, our approach exploits the GPU to assist in the computation of a triangulation T of S that is a good approximation to T (S). From that, the approach employs the CPU to transform T ' to T (S). As a major part of the total work is done by the GPU with parallel computing capability, it is a fast and practical approach, particularly for a large number of points (millions with the current state-of-the-art GPU). For such cases, our current implementation can run up to 53% faster on a Core2 Duo machine when compared to Triangle, the well-known fastest Delaunay triangulation implementation. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1145/1342250.1342264 | SI3D |
Keywords | DocType | Citations |
novel approach,delaunay triangulation,practical approach,delaunay triangulations,computing two-dimensional delaunay triangulation,known implementation,graphics hardware,well-known fastest delaunay triangulation,prior work,total work,current state-of-the-art gpu,current implementation,computational geometry,gpgpu,voronoi diagram,computer graphic,object model | Conference | 24 |
PageRank | References | Authors |
1.20 | 12 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guodong Rong | 1 | 213 | 10.09 |
| Tiow-Seng Tan | 2 | 398 | 27.99 |
| Thanh-Tung Cao | 3 | 145 | 7.31 |
| Stephanus | 4 | 24 | 1.20 |