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Power-efficient simulation of detailed cortical microcircuits on SpiNNaker

Thomas Sharp, Francesco Galluppi, Alexander Rast and Steve Furber

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

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