A Fast Implementation of Parallel Discrete-Event Simulation on GPGPU

Janche Sang, Che-Rung Lee, Vernon Rego, Chung-Ta King
Dept. of Computer and Info. Science, Cleveland State University, OH 44115, USA
The 2013 International Conference on Parallel and Distributed, Processing Techniques and Applications (PDPTA’13), 2013


   title={A Fast Implementation of Parallel Discrete-Event Simulation on GPGPU},

   author={Sang, Janche and Lee, Che-Rung and Rego, Vernon and King, Chung-Ta},



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Modern General Purpose Graphics Processing Units(GPGPUs) offer much more computational power than recent CPUs by providing a vast number of simple, data parallel, multithreaded cores. In this study, we focus on the use of a GPGPU to perform parallel discrete-event simulation. Our approach is to use a modified service time distribution function to allow more independent events to be processed in parallel. The implementation issues and alternative strategies will be discussed in detail. We use Thrust, an open-source parallel algorithms library which resembles the C++ Standard Template Library (STL), to build our tool. The experimental results show that our implementation can be more than 60 times faster than the sequential simulation. Furthermore, the speedup curve scales well which indicates that our implementation is suitable for large-scale discrete-event simulation models.
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