Accelerating Petri-Net simulations using NVIDIA graphics processing units

Yianni, Panayioti C., Neves, Luis C., Rama, Dovile and Andrews, John D. (2018) Accelerating Petri-Net simulations using NVIDIA graphics processing units. European Journal of Operational Research, 265 (1). pp. 361-371. ISSN 0377-2217

Full text not available from this repository.


Stochastic Petri-Nets (PNs) are combined with General-Purpose Graphics Processing Unit (GPGPUs) to develop a fast and low cost framework for PN modelling. GPGPUs are composed of many smaller, parallel compute units which has made them ideally suited to highly parallelised computing tasks. Monte Carlo (MC) simulation is used to evaluate the probabilistic performance of the system. The high computational cost of this approach is mitigated through parallelisation. The efficiency of different approaches to parallelisation of the problem is evaluated. The developed framework is then used on a PN model example which supports decision-making in the field of infrastructure asset management. The model incorporates deterioration, inspection and maintenance into a complete decision-support tool. The results obtained show that this method allows the combination of complex PN modelling with rapid computation in a desktop computer.

Item Type: Article
Keywords: CUDA; GPU; Petri-Net; Parallel Asset management
Schools/Departments: University of Nottingham, UK > Faculty of Engineering
Identification Number:
Depositing User: Eprints, Support
Date Deposited: 20 Jul 2017 10:37
Last Modified: 04 May 2020 19:32

Actions (Archive Staff Only)

Edit View Edit View