Parallel Voronoi Computation for Physics-Based Simulations

Abstract

Voronoi diagrams are fundamental data structures in computational geometry, with applications in areas such as physics-based simulations. For non-Euclidean distances, the Voronoi diagram must be performed over a grid-graph, where the edges encode the required distance information. The major bottleneck in this case is a shortest path algorithm that must be computed multiple times during the simulation. The authors present a GPU algorithm for solving the shortest path problem from multiple sources using a generalized distance function. Their algorithm was designed to leverage the grid-based nature of the underlying graph that represents the deformable objects. Experimental results report speed-ups up to 65x over a current reference sequential method.