SpiNNaker: A 1-W 18-Core System-on-Chip for Massively-Parallel Neural Network Simulation Eustace Painkras, Luis A. Plana , Senior Member , IEEE , Jim Garside, Steve Temple, Francesco Galluppi, Student Member , IEEE

Abstract

The modelling of large systems of spiking neurons is computationally very demanding in terms of processing power and communication. SpiNNaker—Spiking Neural Network ar- chitecture—is a massively parallel computer system designed to provide a cost-effective and flexible simulator for neuroscience experiments. It can model up to a billion neurons and a trillion synapses in biological real time. The basic building block is the SpiNNaker Chip Multiprocessor (CMP), which is a custom-de- signed globally asynchronous locally synchronous (GALS) system with 18 ARM968 processor nodes re siding in synchronous islands, surrounded by a lightweight, packet-switched asynchronous communications infrastructure. In this paper, we review the design requirements for its very demanding target application, the SpiNNaker micro-architecture and its implementation issues. We also evaluate the SpiNNaker CMP, which contains 100 million transistors in a 102-mm die, provides a peak performance of 3.96 GIPS, and has a peak power consumption of 1 W when all processor cores operate at the nominal frequency of 180 MHz. SpiNNaker chips are fully operational and meet their power and performance requirements.