Abstract
In this paper we summarize several techniques that allow a dramatic speed-up of the simulation of networks of integrate and fire (I & F) neurons. The speed-up these methods allow is investigated in simulations where the computation time is measured as a function of network activity. Several topics are discussed such as the current limits of real time (largest network that can be simulated in real time) and the computational convenience of mean-field approximations. We conclude that the simulation of large models of I & F neurons in real time is feasible within the current technology.
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Sánchez-Montañás, M.A. (2001). Strategies for the Optimization of Large Scale Networks of Integrate and Fire Neurons. In: Mira, J., Prieto, A. (eds) Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence. IWANN 2001. Lecture Notes in Computer Science, vol 2084. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45720-8_14
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DOI: https://doi.org/10.1007/3-540-45720-8_14
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