Voronoi diagrams—a survey of a fundamental geometric data structure
ACM Computing Surveys (CSUR)
A comparison of sequential Delaunay triangulation algorithms
Proceedings of the eleventh annual symposium on Computational geometry
Fast computation of generalized Voronoi diagrams using graphics hardware
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Triangle: Engineering a 2D Quality Mesh Generator and Delaunay Triangulator
FCRC '96/WACG '96 Selected papers from the Workshop on Applied Computational Geormetry, Towards Geometric Engineering
Cg: a system for programming graphics hardware in a C-like language
ACM SIGGRAPH 2003 Papers
Jump flooding in GPU with applications to Voronoi diagram and distance transform
I3D '06 Proceedings of the 2006 symposium on Interactive 3D graphics and games
Variants of Jump Flooding Algorithm for Computing Discrete Voronoi Diagrams
ISVD '07 Proceedings of the 4th International Symposium on Voronoi Diagrams in Science and Engineering
Efficient large-scale terrain rendering method for real-world game simulation
Edutainment'06 Proceedings of the First international conference on Technologies for E-Learning and Digital Entertainment
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
Parallel Banding Algorithm to compute exact distance transform with the GPU
Proceedings of the 2010 ACM SIGGRAPH symposium on Interactive 3D Graphics and Games
Technical Section: Parallel GPU-based data-dependent triangulations
Computers and Graphics
Navigation queries from triangular meshes
MIG'10 Proceedings of the Third international conference on Motion in games
Computing 2D constrained Delaunay triangulation using the GPU
I3D '12 Proceedings of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games
gHull: A GPU algorithm for 3D convex hull
ACM Transactions on Mathematical Software (TOMS)
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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.