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arXiv · 2103.08392

The SpiNNaker 2 Processing Element Architecture for Hybrid Digital Neuromorphic Computing

Sebastian Höppner·Yexin Yan·Andreas Dixius·Stefan Scholze·Johannes Partzsch·Marco Stolba·Florian Kelber·Bernhard Vogginger·Felix Neumärker·Georg Ellguth·Stephan Hartmann·Stefan Schiefer·Thomas Hocker·Dennis Walter·Genting Liu·Jim Garside·Steve Furber·Christian Mayr
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Abstract

This paper introduces the processing element architecture of the second generation SpiNNaker chip, implemented in 22nm FDSOI. On circuit level, the chip features adaptive body biasing for near-threshold operation, and dynamic voltage-and-frequency scaling driven by spiking activity. On system level, processing is centered around an ARM M4 core, similar to the processor-centric architecture of the first generation SpiNNaker. To speed operation of subtasks, we have added accelerators for numerical operations of both spiking (SNN) and rate based (deep) neural networks (DNN). PEs communicate via a dedicated, custom-designed network-on-chip. We present three benchmarks showing operation of the whole processor element on SNN, DNN and hybrid SNN/DNN networks.

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Sebastian Höppner, Yexin Yan, Andreas Dixius, Stefan Scholze, Johannes Partzsch, Marco Stolba, Florian Kelber, Bernhard Vogginger, Felix Neumärker, Georg Ellguth, Stephan Hartmann, Stefan Schiefer, Thomas Hocker, Dennis Walter, Genting Liu, Jim Garside, Steve Furber, Christian Mayr. 2021-03-15. The SpiNNaker 2 Processing Element Architecture for Hybrid Digital Neuromorphic Computing. https://arxiv.org/abs/2103.08392

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