Konferensartikel

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

Stephane Vialle
UMI 2958 - GT-CNRS, CentraleSupelec, Université Paris-Saclay, 57070 Metz, France / LRI - UMR 8623, 91190 Gif-sur-Yvette, France

Jean-Philippe Tavella
EDF Lab Saclay, 91120 Palaiseau, France

Cherifa Dad
UMI 2958 - GT-CNRS, CentraleSupelec, Université Paris-Saclay, 57070 Metz, France

Remi Corniglion
EDF Lab Saclay, 91120 Palaiseau, France

Mathieu Caujolle
EDF Lab Saclay, 91120 Palaiseau, France

Vincent Reinbold
University of Leuven, Department of Civil Engineering, 3001 Leuven, Belgium

Ladda ner artikelhttp://dx.doi.org/10.3384/ecp17132673

Ingår i: Proceedings of the 12th International Modelica Conference, Prague, Czech Republic, May 15-17, 2017

Linköping Electronic Conference Proceedings 132:74, s. 673-682

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Publicerad: 2017-07-04

ISBN: 978-91-7685-575-1

ISSN: 1650-3686 (tryckt), 1650-3740 (online)

Abstract

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 inter-connected 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.

Nyckelord

Multi-Simulation, FMI, Scaling, Multi-core, PC Cluster

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