title: Power-efficient simulation of detailed cortical microcircuits on SpiNNaker.
abstract: Computer simulation of neural matter is a promising methodology for understanding the function of the brain. Recent anatomical studies have mapped the intricate structure of cortex, and these data have been exploited in numerous simulations attempting to explain its function. However, the largest of these models run inconveniently slowly and require vast amounts of electrical power, which hinders useful experimentation. SpiNNaker is a novel computer architecture designed to address these problems using low-power microprocessors and custom communication hardware. We use four SpiNNaker chips (of a planned fifty thousand) to simulate, in real-time, a cortical circuit of ten thousand spiking neurons and four million synapses. In this simulation, the hardware consumes 100 nJ per neuron per millisecond and 43 nJ per postsynaptic potential, which is the smallest quantity reported for any digital computer. We argue that this approaches fast, power-feasible and scientifically useful simulations of large cortical areas.
authors.affiliation: School of Computer Science, The University of Manchester, Manchester, M13 9PL, UK. thomas.sharp@cs.man.ac.uk
authors.forename: Thomas
authors.initials: T
authors.lastname: Sharp
authors.forename: Francesco
authors.initials: F
authors.lastname: Galluppi
authors.forename: Alexander
authors.initials: A
authors.lastname: Rast
authors.forename: Steve
authors.initials: S
authors.lastname: Furber
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D002540:Cerebral Cortex / Q000166:cytology / Q000502:physiology*; D003198:Computer Simulation / Q000639:trends; D003201:Computers / Q000639:trends; D003202:Computers, Analog / Q000639:trends; D011211:Electric Power Supplies / Q000639:trends; D006801:Humans; D008959:Models, Neurological; D009474:Neurons / Q000166:cytology / Q000502:physiology*