Scaling FMI-CS Based Multi-Simulation Beyond Thousand FMUs on Infiniband Cluster

In recent years, co-simulation has become an increasingly industrial tool to simulate Cyber Physical Systems including multi-physics and control, like smart electric grids, since it allows to involve different modeling tools within the same temporal simulation. The challenge now is to integrate in a single calculation scheme very numerous and intensely interconnected models, and to do it without any loss in model accuracy. This will avoid neglecting fine phenomena or moving away from the basic principle of equation-based modeling. Offering both a large number of computing cores and a large amount of distributed memory, multi-core PC clusters can address this key issue in order to achieve huge multi-simulations in acceptable time. This paper introduces all our efforts to parallelize and distribute our co-simulation environment based on the FMI for Co-Simulation standard (FMI-CS). At the end of 2016 we succeeded to scale beyond 1000 FMUs and 1000 computing cores on different PC-clusters, including the most recent HPC Infiniband-cluster available at EDF.

[1]  Stéphane Vialle,et al.  Scaling of Distributed Multi-simulations on Multi-core Clusters , 2016, 2016 IEEE 25th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE).

[2]  Massimo Torquati,et al.  Message Passing on InfiniBand RDMA for Parallel Run-Time Supports , 2014, 2014 22nd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing.

[3]  J. Ramanujam,et al.  Cluster partitioning approaches to mapping parallel programs onto a hypercube , 1987, Parallel Comput..

[4]  K. Mani Chandy,et al.  Distributed Simulation: A Case Study in Design and Verification of Distributed Programs , 1979, IEEE Transactions on Software Engineering.

[5]  Laurent Ciarletta,et al.  Hybrid Co-simulation of FMUs using DEV&DESS in MECSYCO , 2016, 2016 Symposium on Theory of Modeling and Simulation (TMS-DEVS).

[6]  Yves Sorel,et al.  Acceleration of FMU Co-Simulation On Multi-core Architectures , 2016 .

[7]  Andrea Omicini,et al.  Give agents their artifacts: the A&A approach for engineering working environments in MAS , 2007, AAMAS '07.

[8]  Stéphane Vialle,et al.  Toward an accurate and fast hybrid multi-simulation with the FMI-CS standard , 2016, 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA).

[9]  Andreas Junghanns,et al.  The Functional Mockup Interface for Tool independent Exchange of Simulation Models , 2011 .

[10]  Bernard P. Zeigler,et al.  Theory of Modeling and Simulation: Integrating Discrete Event and Continuous Complex Dynamic Systems , 2000 .

[11]  Dirk Saelens,et al.  OpenIDEAS – An Open Framework for integrated District Energy Simulations , 2015, Building Simulation Conference Proceedings.

[12]  Amir Nakib,et al.  Hybrid Heuristics for Mapping Task Problem on Large Scale Heterogeneous Platforms , 2016, 2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW).

[13]  Stéphane Vialle,et al.  FMI-based distributed multi-simulation with DACCOSIM , 2015, SpringSim.