Simulation of large-scale multitarget tracking scenarios using GPUs
Yusuf Dinath, Ratnasingham Tharmarasa, Eric Meger, Pierre Valin, Thia Kirubarajan · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2012
The increased availability of Graphical Processing Units (GPUs) in personal computers has made parallel pro- gramming worthwhile, but not necessarily easier. This paper will take advantage of the power of a GPU, in conjunction with the Central Processing Unit (CPU), in order to simulate target trajectories for large-scale scenarios, such as wide-area maritime or ground surveillance. The idea is to simulate the motion of tens of thousands of targets using a GPU by formulating an optimization problem that maximizes the throughput. To do this, the proposed algorithm is provided with input data that describes how the targets are expected to behave, path information (e.g., roadmaps, shipping lanes), and available computational resources. Then, it is possible to break down the algorithm into parts that are done in the CPU versus those sent to the GPU. The ultimate goal is to compare processing times of the algorithm with a GPU in conjunction with a CPU to those of the standard algorithms running on the CPU alone. In this paper, the optimization formulation for utilizing the GPU, simulation results on scenarios with a large number of targets and conclusions are provided.