This paper presents the optimization and parallelization of the multiple observer siting program, originally developed by Franklin and Vogt. Siting is a compute-intensive application with a large amount of inherent parallelism. The advantage of parallelization is not only a faster program but also the ability to solve bigger problems. We have parallelized the program using two different techniques: OpenMP, using multi-core CPUs, and CUDA, using a general purpose graphics processing unit (GPGPU). Experiment results show that both techniques are very effective. Using the OpenMP program, we are able to site tens of thousands of observers on a 16385 × 16385 terrain in less than 2 minutes, on our workstation with two CPUs and one GPU. The CUDA program achieves the same in about 30 seconds.