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Issue No.05 - May (2013 vol.19)

pp: 736-748

Meng Qi , GR/ST/21-256C, Nat. Univ. of Singapore, Singapore, Singapore

Thanh-Tung Cao , Nat. Univ. of Singapore, Singapore, Singapore

Tiow-Seng Tan , Sch. of Comput., Nat. Univ. of Singapore, Singapore, Singapore

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2012.307

ABSTRACT

We propose the first graphics processing unit (GPU) solution to compute the 2D constrained Delaunay triangulation (CDT) of a planar straight line graph (PSLG) consisting of points and edges. There are many existing CPU algorithms to solve the CDT problem in computational geometry, yet there has been no prior approach to solve this problem efficiently using the parallel computing power of the GPU. For the special case of the CDT problem where the PSLG consists of just points, which is simply the normal Delaunay triangulation (DT) problem, a hybrid approach using the GPU together with the CPU to partially speed up the computation has already been presented in the literature. Our work, on the other hand, accelerates the entire computation on the GPU. Our implementation using the CUDA programming model on NVIDIA GPUs is numerically robust, and runs up to an order of magnitude faster than the best sequential implementations on the CPU. This result is reflected in our experiment with both randomly generated PSLGs and real-world GIS data having millions of points and edges.

INDEX TERMS

Graphics processing units, Instruction sets, Arrays, Strips, Standards, Color,image vectorization, GPGPU, parallel computation, computational geometry, Voronoi diagram

CITATION

Meng Qi, Thanh-Tung Cao, Tiow-Seng Tan, "Computing 2D Constrained Delaunay Triangulation Using the GPU",

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