Acceleration of Microscopic Urban Traffic Simulation Using OpenCL

As the number of vehicles on our roads increases, the problems related to this phenomenon emerge more dramatically. These problems include car accidents, congestions and CO2 emissions production, increasing CO2 concentrations in the atmosphere. In order to minimize these impacts and to use the road infrastructure eff ectively, the use of traffic simulators can come in handy. Thanks to these tools, it is possible to evaluate the evolution of a traffic flow with various initial states of the simulation and thus know what to do and how to react in different states of the real-world traffic situations. This thesis deals with acceleration of microscopic urban traffic simulation using OpenCL. Supposing it is necessary to simulate a large network traffic, the need to accelerate the simulation is necessary. For this purpose, it is possible, for example, to use the graphics processing units (GPUs) and the technique of GPGPU for general purpose computations, which is used in this work. The results show that the performance gains of GPUs are significant compared to a parallel implementation on CPU