The BrainScaleS-2 accelerated neuromorphic system with hybrid plasticity

2022/01/26 by Christian Pehle, Sebastian Billaudelle, Pehle, Christian +17 · 11 citations
Engineering · Computer Science · #Advanced Memory and Neural Computing #Ferroelectric and Negative Capacitance Devices #Neural Networks and Reservoir Computing

paper · pdf · doi:10.48550/arxiv.2201.11063

Abstract

Since the beginning of information processing by electronic components, the nervous system has served as a metaphor for the organization of computational primitives. Brain-inspired computing today encompasses a class of approaches ranging from using novel nano-devices for computation to research into large-scale neuromorphic architectures, such as TrueNorth, SpiNNaker, BrainScaleS, Tianjic, and Loihi. While implementation details differ, spiking neural networks - sometimes referred to as the third generation of neural networks - are the common abstraction used to model computation with such systems. Here we describe the second generation of the BrainScaleS neuromorphic architecture, emphasizing applications enabled by this architecture. It combines a custom analog accelerator core supporting the accelerated physical emulation of bio-inspired spiking neural network primitives with a tightly coupled digital processor and a digital event-routing network.

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