high performance computing on graphics processing units: hgpu.org

A novel algorithm is presented to compute the convex hull of a point set in R3using the graphics processing unit (GPU). By exploiting the relationship between the Voronoi diagram and the convex hull, the algorithm derives the approximation of the convex hull from the former. The missed points are found back by using a two-round checking in digital and continuous space successively. The algorithm does not need explicit locking or any other concurrency control mechanism, thus it can maximize the parallelism available on the modern GPU. The implementation using the CUDA programming model on Nvidia GPUs is robust, exact, and efficient. The experiments show that it is up to an order of magnitude faster than other sequential convex hull implementations running on the CPU for inputs of millions of points. The works demonstrate that the GPU can be used to solve non-trivial computational geometry problems with significant performance benefit, without sacrificing accuracy or robustness.