Abstract
This paper presents a spiking neural network simulator suitable for biologically plausible large neural networks, named DAMNED for “Distributed And Multi-threaded Neural Event-Driven”. The simulator is designed to run efficiently on a variety of hardware. DAMNED makes use of multi-threaded programming and non-blocking communications in order to optimize communications and computations overlap. This paper details the even-driven architecture of the simulator. Some original contributions are presented, such as the handling of a distributed virtual clock and an efficient circular event queue taking into account spike propagation delays. DAMNED is evaluated on a cluster of computers for networks from 103 to 105 neurons. Simulation and network creation speedups are presented. Finally, scalability is discussed regarding number of processors, network size and activity of the simulated NN.
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References
Bohte, S.M.: The evidence for neural information processing with precise spike-times: A survey. Natural Computing 3(4), 195–206 (2004)
Chandy, K.M., Misra, J.: Distributed simulation: A case study in design and verification of distributed programs. IEEE Transactions on Software Engineering, SE-5(5), 440–452 (1979)
Ferscha, A.: Parallel and distributed simulation of discrete event systems. In: Parallel and Distributed Computing Handbook, pp. 1003–1041. McGraw-Hill, New York (1996)
Flynn, M.J., Rudd, K.W.: Parallel architectures. ACM Computation Surveys 28(1), 67–70 (1996)
Message Passing Interface Forum. MPI: A message-passing iterface standard. Technical Report UT-CS-94-230, University of Tennessee (1994)
Gerstner, W., Kistler, W.M.: Spiking Neuron Models: An Introduction. Cambridge University Press, New York (2002)
Izhikevich, E.M.: Simple model of spiking neurons. IEEE Transactions on Neural Networks 14(6), 1569–1572 (2003)
Knight, B.W.: Dynamics of encoding in a population of neurons. Journal of General Physiology 59, 734–766 (1972)
Lobb, C.J., Chao, Z.C., Fujimoto, R.M., Potter, S.M.: Parallel event-driven neural network simulations using the hodgkin-huxley model. In: Proceedings of the Workshop on Principles of Advanced and Distributed Simulations. PADS 2005, June 2005, pp. 16–25 (2005)
Makino, T.: A discrete-event neural network simulator for general neuron models. Neural Computing and Applications 11(3-4), 210–223 (2003)
Marin, M.: Comparative analysis of a parallel discrete-event simulator. In: SCCC, pp. 172–177 (2000)
Mattia, M., Giudice, P.D.: Efficient event-driven simulation of large networks of spiking neurons and dynamical synapses. Neural Computation 12, 2305–2329 (2000)
Morrison, A., Mehring, C., Geisel, T., Aertsen, A., Diesmann, M.: Advancing the boundaries of high-connectivity network simulation with distributed computing. Neural Computation 17, 1776–1801 (2005)
Rudolph, M., Destexhe, A.: Analytical integrate-and-fire neuron models with conductance-based dynamics for event-driven simulation strategies. Neural Computation 18(9), 2146–2210 (2006)
Shelley, M.J., Tao, L.: Efficient and accurate time-stepping schemes for integrate-and-fire neuronal network. Journal of Computational Neuroscience 11(2), 111–119 (2001)
Swadlow, H.A.: Efferent neurons and suspected interneurons in binocular visual cortex of the awake rabbit: Receptive fileds and binocular properties. Journal of Neurophysiology 59(4), 1162–1187 (1988)
Watts, L.: Event-driven simulation of networks of spiking neurons. In: Cowan, J.D., Tesauro, G., Alspector, J. (eds.) Advances in Neural Information Processing System, vol. 6, pp. 927–934. MIT Press, Cambridge (1994)
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Mouraud, A., Puzenat, D. (2009). Simulation of Large Spiking Neural Networks on Distributed Architectures, The “DAMNED” Simulator. In: Palmer-Brown, D., Draganova, C., Pimenidis, E., Mouratidis, H. (eds) Engineering Applications of Neural Networks. EANN 2009. Communications in Computer and Information Science, vol 43. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03969-0_33
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DOI: https://doi.org/10.1007/978-3-642-03969-0_33
Publisher Name: Springer, Berlin, Heidelberg
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