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http://hdl.handle.net/10609/93171
Title: Designing a benchmark for the performance evaluation of agent-based simulation applications on HPC
Author: Moreno Vendrell, Andreu
Rodríguez Guerra, Juan José
Beltrán, Daniel
Sikora, Anna
Jorba i Esteve, Josep  
César Galobardes, Eduardo
Others: Universitat Autònoma de Barcelona
Universitat Oberta de Catalunya (UOC)
Keywords: agent-based modeling and simulation
parallel applications
performance
benchmark
Issue Date: 17-Nov-2018
Publisher: Journal of Supercomputing
Citation: Moreno, A., Rodríguez, J.J., Beltrán, D., Sikora, A., Jorba, J. & César, E. (2019). Designing a benchmark for the performance evaluation of agent-based simulation applications on HPC. Journal of Supercomputing, 75(3), 1524-1550. doi: 10.1007/s11227-018-2688-8
Project identifier: info:eu-repo/grantAgreement/TIN2017-84553-C2-1-R
info:eu-repo/grantAgreement/TIN2014-53234-C2-1-R
info:eu-repo/grantAgreement/2017-SGR-313
Also see: https://link.springer.com/article/10.1007%2Fs11227-018-2688-8
Abstract: Agent-based modeling and simulation (ABMS) is a class of computational models for simulating the actions and interactions of autonomous agents with the goal of assessing their effects on a system as a whole. Several frameworks for generating parallel ABMS applications have been developed taking advantage of their common characteristics, but there is a lack of a general benchmark for comparing the performance of the generated applications. We propose and design a benchmark that takes into consideration the most common characteristics of this type of applications and includes parameters for influencing their relevant performance aspects. We provide an initial implementation of the benchmark for FLAME, FLAME GPU, Repast HPC and EcoLab, some of the most popular parallel ABMS platforms, and use it for comparing the applications generated by these platforms. The obtained results are mostly in agreement with previous studies, but the designed and implemented specification has allowed for testing a wider set of aspects, such as the number of interacting agents, the amount of interchanged data or the evolution of the workload and obtaining more reliable results.
Language: English
URI: http://hdl.handle.net/10609/93171
ISSN: 0920-8542MIAR

1573-0484MIAR
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