ReckOn - Institute of Neuroinformatics

Learn about Institute of Neuroinformatics's neuromorphic hardware: ReckOn

ReckOn At A Glance

Status: Released
Chip Type: Digital
On-Chip Learning: true

A summary

Overview

ReckOn is a spiking recurrent neural network (RNN) processor enabling on-chip learning over second-long timescales based on a modified version of the e-prop algorithm (we released a PyTorch implementation of the vanilla e-prop algorithm for leaky integrate-and-fire neurons here). It was prototyped and measured in 28-nm FDSOI CMOS at the Institute of Neuroinformatics, University of Zurich and ETH Zurich, and published at the 2022 IEEE International Solid-State Circuits Conference (ISSCC).

DateTitleAuthorsVenue/Source
March 2022ReckOn: A 28nm sub-mm² task-agnostic spiking recurrent neural network processor enabling on-chip learning over second-long timescalesC. Frenkel and G. IndiveriIEEE International Solid-State Circuits Conference (ISSCC)
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