Transactions on Transport Sciences 2012, 5(2):55-62 | DOI: 10.2478/v10158-012-0007-2

Stochastic Analysis of a Queue Length Model Using a Graphics Processing Unit

J. Přikryl*,1,2, J. Kocijan3,4
1 Faculty of Transportation Sciences, Czech University of Technology, Prague, Czech Republic
2 Institute of Information Theory and Automation, Czech Academy of Sciences, Prague, Czech Republic
3 JoĹžef Stefan Institute, Ljubljana, Slovenia
4 Centre for Systems and Information Technologies, University of Nova Gorica, Slovenia

Mathematical modeling is an inevitable part of system analysis and design in science and engineering. When a parametric mathematical description is used, the issue of the parameter estimation accuracy arises. Models with uncertain parameter values can be evaluated using various methods and computer simulation is among the most popular in the engineering community. Nevertheless, an exhaustive numerical analysis of models with numerous uncertain parameters requires a substantial computational effort. The purpose of this paper is to show how the computation can be accelerated using a parallel configuration of graphics processing units (GPU). The assessment of the computational speedup is illustrated with a case study. The case study is a simulation of Highway Capacity Manual 2000 Queue Model with selected uncertain parameters. The computational results show that the parallel computation solution is efficient for a larger amount of samples when the initial and communication overhead of parallel computation becomes a sufficiently small part of the whole process.

Keywords: Graphics processing unit, GPU, Monte Carlo simulation, computer simulation, modeling.

Published: June 1, 2012  Show citation

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Přikryl, J., & Kocijan, J. (2012). Stochastic Analysis of a Queue Length Model Using a Graphics Processing Unit. Transactions on Transport Sciences, 5(2), 55-62. doi: 10.2478/v10158-012-0007-2
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