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The SpiNNaker 2 Processing Element Architecture for Hybrid Digital Neuromorphic Computing

Authors :
Höppner, Sebastian
Yan, Yexin
Dixius, Andreas
Scholze, Stefan
Partzsch, Johannes
Stolba, Marco
Kelber, Florian
Vogginger, Bernhard
Neumärker, Felix
Ellguth, Georg
Hartmann, Stephan
Schiefer, Stefan
Hocker, Thomas
Walter, Dennis
Liu, Genting
Garside, Jim
Furber, Steve
Mayr, Christian
Publication Year :
2021

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.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2103.08392
Document Type :
Working Paper