We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms that are currently implemented. We next review the precision of those simulation strategies, in particular in cases where plasticity depends on the exact timing of the spikes. We overview different simulators and simulation environments presently available (restricted to those freely available, open source and documented). For each simulation tool, its advantages and pitfalls are reviewed, with an aim to allow the reader to identify which simulator is appropriate for a given task. Finally, we provide a series of benchmark simulations of different types of networks of spiking neurons, including Hodgkin-Huxley type, integrate-and-fire models, interacting with current-based or conductance-based synapses, using clock-driven or event-driven integration strategies. The same set of models are implemented on the different simulators, and the codes are made available. The ultimate goal of this review is to provide a resource to facilitate identifying the appropriate integration strategy and simulation tool to use for a given

Optimistic parallel discrete event simulation method is applied to large scale data parallel applications. Specificly, optimizations for state saving of large state vectors and bounded optimism are incorporated in the simulation environment. Dynamic load balancing is studied, and a checkpoint and migration mechanism is implemented and integrated with the PVM message passing environment.

of laser dynamics

The different kinds of behavior exhibited by the system in a laser dynamics simulation using a cellular automata model are analyzed. Three distinct types of behavior have been found: laser constant operation, laser spiking and a complex behavior showing irregular oscillations. In the last case, the power spectrum follows a power law of the type 1/f − � with exponent close to � = 2. In the laser spiking regime, the dependence of the decay rate of the oscillations is found to be in good agreement with the predictions of the theoretical laser rate equations and the experimental phenomenology. In our model the system components evolve under local rules which reproduce the physics of the laser system at the microscopic level, and the laser properties appear as cooperative emergent phenomena associated to these rules. 1.

Abstract — In order to analyze the feasibility of executing a parallel bioinspired model of laser dynamics on a heterogeneous non-dedicated cluster, we evaluate its performance including artificial load to simulate other tasks or jobs submitted by other users. As the model is based on a synchronous cellular automaton (CA), using the SPMD (Single Program, Multiple Data) paradigm, it is not clear in advance if an appropriate efficiency can be obtained on this kind of platform. A dynamic load balancing strategy with two main differences from most previous implementations of CA based models has been used. First, it is possible to migrate load to cluster nodes initially not belonging to the pool. Second, a modular approach is taken in which the model is executed on top of a dynamic load balancing tool—the Dynamite system — gaining flexibility. Very satisfactory results have been obtained, with performance increases from 60 % to 80%. I.

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