Alzahrani, E., Simons, A.J.H. orcid.org/0000-0002-5925-7148 and Richmond, P. orcid.org/0000-0002-4657-5518 (2020) Data aware simulation of complex systems on GPUs. In: 2019 International Conference on High Performance Computing & Simulation (HPCS). 2019 International Conference on High Performance Computing & Simulation (HPCS), 15-19 Jul 2019, Dublin, Ireland. Institute of Electrical and Electronics Engineers (IEEE) , pp. 567-574. ISBN 9781728144856
Abstract
GPUs have been demonstrated to be highly effective at improving the performance of Multi-Agent Systems (MAS). One of the major limitations of further performance improvements is in the memory bandwidth required to move agent data through the GPU's memory hierarchy. This paper presents a formal model for data aware simulation and an empirical study into the impact of minimising data movement on performance. This study proposes a method that can be applied to the simulation of complex systems on GPUs to extract required data from agent behaviour during simulation time and how this information can be used to reduce data movement. The FLAME GPU software has been extended to demonstrate this technique. Three benchmark experiments have been applied to evaluate the overall reduction in simulation execution time under specific criteria. The results of the comparison between the current and new system show that reducing data movement within a simulation improves overall performance with up to 4.8x speedup reported.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | Memory access reduction; FLAME GPU; Agent Based Modelling; Simulation |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Funding Information: | Funder Grant number ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL EP/N018869/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 22 Jun 2023 15:49 |
Last Modified: | 23 Jun 2023 12:22 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Identification Number: | 10.1109/hpcs48598.2019.9188054 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:200725 |