Parallel Computing Using Gpu for Efficient Traffic Simulation

Parallel Computing can be made possible using the multiple cores of the Graphics Processing Unit (GPU) thanks to the modern programmable GPU models. This allows the use of parallel computing techniques to improve upon the computation time of large scale traffic simulations. This paper proposes the use of a multi-processor algorithm for creating efficient traffic simulation software. The method in consideration achieves this by separating the r oad network into regions which are individually computed as a threaded block inside the GPU and merged together using the Central Processing Unit to provide the final data of the simulation. A significant improvement in the computation time is observed when the proposed parallelization techniques are applied to the simulator.