Research Article
GPU optimized parallel implementation of NaSch traffic model
@INPROCEEDINGS{10.4108/eai.24-4-2019.2284233, author={Yassine El Hafid and Abdessamad El Rharras and Mohamed Wahbi and Rachid Saadane}, title={GPU optimized parallel implementation of NaSch traffic model}, proceedings={Proceedings of the Third International Conference on Computing and Wireless Communication Systems, ICCWCS 2019, April 24-25, 2019, Faculty of Sciences, Ibn Tofa\~{n}l University -K\^{e}nitra- Morocco}, publisher={EAI}, proceedings_a={ICCWCS}, year={2019}, month={5}, keywords={: gpgpu cpu cuda nasch model road traffic parallel computing optimization}, doi={10.4108/eai.24-4-2019.2284233} }- Yassine El Hafid
Abdessamad El Rharras
Mohamed Wahbi
Rachid Saadane
Year: 2019
GPU optimized parallel implementation of NaSch traffic model
ICCWCS
EAI
DOI: 10.4108/eai.24-4-2019.2284233
Abstract
Traffic simulation has a practical interest for modern society, mainly in minimizing the problems of congestion, which is the main cause of road accidents. In this way, several traffic models were developed based on Cellular Automata (CA). Moreover, the simulation of traffic system requires a high computing ability. Therefore, this paper explores the ways to use the graphics-processing unit (GPU) for reducing time simulation of such applications. We propose several software implementations to maximize GPU performance for NaSch model parallelization. Compared to CPU, the simulation results show that we need optimization effort to get better performance results for GPU.
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