GPU-Accelerated Multiple Observer Siting

We present two fast parallel implementations of the Franklin-Vogt multiple observer siting algorithm, using either OpenMP or CUDA. In this problem, the objective is to site observers on a raster terrain such that the joint area visible by them is maximized. On a portion of terrain with 16,385×16,385 cells, assuming that observers can see out to a radius-of-interest of 100 cells, finding the approximate 15,000 observers that have the greatest coverage takes only 17s in CUDA. That is a factor of 70 speedup from the sequential version. The OpenMP version exhibits a factor of 17 speedup on a 16 core system. Applications for the multiple observer siting problem include radio transmission towers, environmental monitoring sites, and path planning for surveillance drones. The algorithm has four steps: finding the visibility indices of all points, selecting a candidate subset of potential top observers, finding each one's viewshed, and greedily constructing the final solution.