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.
@article{arxiv.2201.11063,
title = {The BrainScaleS-2 accelerated neuromorphic system with hybrid plasticity},
author = {Christian Pehle and Sebastian Billaudelle and Benjamin Cramer and Jakob Kaiser and Korbinian Schreiber and Yannik Stradmann and Johannes Weis and Aron Leibfried and Eric Müller and Johannes Schemmel},
journal= {arXiv preprint arXiv:2201.11063},
year = {2022}
}
Comments
22 pages, 10 figures; amended funding acknowledgements, added one citation