2D Triangulation of Polygons on CUDA

General Purpose computing on Graphics Processor Units (GPGPU) brings massively parallel computing (hundreds of compute cores) to the desktop at a reasonable cost, but requires that algorithms be carefully designed to take advantage of this power. The present work explores the possibilities of CUDA (NVIDIA Compute Unified Device Architecture) using GPGPU approach for 2D Triangulation of Polygons. We have conducted an experiment to measure the performance of the GPU with respect to the CPU. The experiment consists of implementing a serial and a parallel algorithm to triangulate 2D polygons and executing both algorithms on several different sets of polygons to compare the performance. We also present an application that uses the polygon triangulation.