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Spiking neural network simulation: memory-optimal synaptic event scheduling

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Abstract

Spiking neural network simulations incorporating variable transmission delays require synaptic events to be scheduled prior to delivery. Conventional methods have memory requirements that scale with the total number of synapses in a network. We introduce novel scheduling algorithms for both discrete and continuous event delivery, where the memory requirement scales instead with the number of neurons. Superior algorithmic performance is demonstrated using large-scale, benchmarking network simulations.

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Fig. 1

Notes

  1. Results using MOSES D were first presented at SfN 2005.

  2. http://senselab.med.yale.edu/senselab/modeldb

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Author notes

  1. Robert D. Stewart

    Present address: MRC Anatomical Neuropharmacology Unit, Mansfield Road, Oxford, OX1 3TH, UK

Authors and Affiliations

  1. Department of Psychology, University of Sheffield, Sheffield, S10 2TP, UK

    Robert D. Stewart & Kevin N. Gurney

Authors
  1. Robert D. Stewart
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  2. Kevin N. Gurney
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Correspondence to Robert D. Stewart.

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Action Editor: Upinder Singh Bhalla

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Stewart, R.D., Gurney, K.N. Spiking neural network simulation: memory-optimal synaptic event scheduling. J Comput Neurosci 30, 721–728 (2011). https://doi.org/10.1007/s10827-010-0288-6

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  • DOI: https://doi.org/10.1007/s10827-010-0288-6

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