A unifying framework for specifying DEVS parallel and distributed simulation architectures, Simulation, vol.89, issue.11, pp.1293-1309, 2013. ,
Theory of Modeling and Simulation, 2000. ,
A formal framework for stochastic discrete event system specification modeling and simulation, Simulation, vol.86, issue.10, pp.587-611, 2010. ,
Parallel devs: A parallel, hierarchical, modular, modeling formalism, Proceedings of the 26th Conference on Winter Simulation WSC '94, Society for Computer Simulation International, pp.716-722, 1994. ,
Distribution of random streams for simulation practitioners, Concurrency and Computation: Practice and Experience, vol.25, pp.10-1427, 2013. ,
URL : https://hal.archives-ouvertes.fr/hal-01099203
Discrete event simulation in the NEURON environment, Neurocomputing, vol.5860, issue.0, pp.1117-1122, 2004. ,
Time warp operating system, Proceedings of the Eleventh ACM Symposium on Operating Systems Principles SOSP '87, ACM, pp.77-93, 1987. ,
Devs simulation of spiking neural networks, Cybernetics and Systems: Proceedings EMCSR 2002, pp.573-578, 2002. ,
A digital neurosynaptic core using embedded crossbar memory with 45pj per spike in 45nm, Custom Integrated Circuits Conference (CICC), pp.2011-2012, 2011. ,
DAMNED: A Distributed and Multithreaded Neural Event-Driven simulation framework Computing Research Repository abs, p.51, 2005. ,
Parallel architecture and optimization for discrete-event simulation of spike neural networks, Science China Technological Sciences, vol.56, issue.2, pp.509-517, 2013. ,
Event-driven simulations of nonlinear integrate-and-fire neurons, Neural Computation, vol.19, issue.12, pp.3226-3238, 2007. ,
URL : https://hal.archives-ouvertes.fr/inria-00103500
Discrete Event Modeling and Simulation Technologies: A Tapestry of Systems and AI-Based Theories and Methodologies, Dynamic Neuronal Ensembles: Neurobiologically Inspired Discrete Event Neural Networks, 2001. ,
Extending the devs formalism for massively parallel simulation, Discrete Event Dynamic Systems, vol.3, pp.2-3, 1993. ,
What's the best possible speedup achievable in distributed simulation: Amdahl's law reconstructed, Proceedings of the Symposium on Theory of Modeling & Simulation: DEVS Integrative M&S Symposium, part of the 2015 Spring Simulation Multiconference, SpringSim '15, pp.189-196, 2015. ,
Limits to high-speed simulations of spiking neural networks using general-purpose computers, Frontiers in Neuroinformatics, vol.8, p.76, 2014. ,