Exit Menu

High Performance Simulation for Industry and Society (Ongoing Research Theme)


Project description

Simulation is a decision support technique used in industry and society. Contemporary simulation software systems limit model size/detail and therefore the quality of results and the amount of investigation/experimentation that can be done in a project. 

This work investigates (1) how distributed simulation techniques can be used to create large scale models and (2) how advanced high performance computing architectures (e.g. cloud, exascale computing) and systems (e.g. e-Infrastructures) can be used to speed up simulation experimentation. 

Examples of successful projects: we have worked successfully with over 30 companies to create new high performance simulation software, with Saker Solutions and Sellafield PLC to create high performance distributed simulations of nuclear waste reprocessing, with the Ford Motor Company to speed up engine production simulation and with several healthcare institutions to speed up experimentation via science gateways.

Impact video by Hobsons Brewery and Company Limited

Please Allow all cookies to view this video from YouTube. Alternatively view the content here


Impact video by Podoactiva SL

Please Allow all cookies to view this video from YouTube. Alternatively view the content here



  • Taylor, S.J.E., Anagnostou, A., Kiss, T., Terstyanszky, G., Visti, H., Farkas, Z., Kacsuk, P., Sereda, A. and Fantini, N. (2018). The CloudSME simulation platform and its applications: A generic multi-cloud platform for developing and executing commercial cloud-based simulations. Future Generation Computer Systems. 88:524-539. https://doi.org/10.1016/j.future.2018.06.006
  • Taylor, S.J.E. Distributed Simulation: State-of-the-Art and Potential for Operational Research. (2019). European Journal of Operational Research. 273(1):1-19. https://doi.org/10.1016/j.ejor.2018.04.032
  • Kiss, T., DesLauriers, J., Gesmier, G., Terstyanszky, G., Pierantoni, G., Abu Oun, O., Taylor, S.J.E., Anagnostou, A., Kovacs, J. (2019). A cloud-agnostic queuing system to support the implementation of deadline-based application execution policies. Future Generation Computer Systems, 101: 99-111. https://doi.org/10.1016/j.future.2019.05.062
  • Taylor, S.J.E., Anagnostou, A., Kiss, T., Terstyanszky, G., Kacsuk, P., Fantini, N., Lakehal, D. and Costes, J. (2019). Enabling Cloud-based Computational Fluid Dynamics with a Platform-as-a-Service Solution. IEEE Transactions on Industrial Informatics. 15(1): 85-94. https://doi.org/10.1109/TII.2018.2849558