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The SpiNNaker (Spiking Neural Network Architecture) project will soon deliver a machine incorporating a million ARM processor cores for real-time modelling of large-scale spiking neural networks. Although the scale of the machine is in the realms of high-performance computing, the technology used to build the machine comes very much from the mobile embedded world, using small integer cores and Network-on-Chip communications both on and between chips. The full machine will use a total of 10 square meters of active silicon area with 57,600 routers using predominantly multicast algorithms to convey real- time spike information through a lightweight asynchronous packet-switched fabric. In this talk I will focus on the NoC aspects, including novel approaches to fault-tolerance and deadlock avoidance.
Steve Furber (Mon,) studied this question.