Spiking neural network simulation: memory-optimal synaptic event scheduling.
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.
Department of Psychology, University of Sheffield, Sheffield, S10 2TP, UK. Robert.Stewart@pharm.ox.ac.uk
Robert D
RD
Stewart
Kevin N
KN
Gurney
D000200:Action Potentials / Q000502:physiology*; D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D006801:Humans; D008568:Memory / Q000502:physiology*; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology; D009474:Neurons / Q000502:physiology*; D013569:Synapses / Q000502:physiology; D009435:Synaptic Transmission / Q000502:physiology*; D013997:Time Factors