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bioSPINspired SIGNED

Bio-inspired Spin-Torque Computing Architectures

Total Cost €


EC-Contrib. €






Project "bioSPINspired" data sheet

The following table provides information about the project.


Organization address
address: RUE MICHEL ANGE 3
city: PARIS
postcode: 75794

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country France [FR]
 Project website
 Total cost 1˙907˙767 €
 EC max contribution 1˙907˙767 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2015-CoG
 Funding Scheme ERC-COG
 Starting year 2016
 Duration (year-month-day) from 2016-09-01   to  2021-08-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 


 Project objective

In the bioSPINspired project, I propose to use my experience and skills in spintronics, non-linear dynamics and neuromorphic nanodevices to realize bio-inspired spin torque computing architectures. I will develop a bottom-up approach to build spintronic data processing systems that perform low power ‘cognitive’ tasks on-chip and could ultimately complement our traditional microprocessors. I will start by showing that spin torque nanodevices, which are multi-functional and tunable nonlinear dynamical nano-components, are capable of emulating both neurons and synapses. Then I will assemble these spin-torque nano-synapses and nano-neurons into modules that implement brain-inspired algorithms in hardware. The brain displays many features typical of non-linear dynamical networks, such as synchronization or chaotic behaviour. These observations have inspired a whole class of models that harness the power of complex non-linear dynamical networks for computing. Following such schemes, I will interconnect the spin torque nanodevices by electrical and magnetic interactions so that they can couple to each other, synchronize and display complex dynamics. Then I will demonstrate that when perturbed by external inputs, these spin torque networks can perform recognition tasks by converging to an attractor state, or use the separation properties at the edge of chaos to classify data. In the process, I will revisit these brain-inspired abstract models to adapt them to the constraints of hardware implementations. Finally I will investigate how the spin torque modules can be efficiently connected together with CMOS buffers to perform higher level computing tasks. The table-top prototypes, hardware-adapted computing models and large-scale simulations developed in bioSPINspired will lay the foundations of spin torque bio-inspired computing and open the path to the fabrication of fully integrated, ultra-dense and efficient CMOS/spin-torque nanodevice chips.


year authors and title journal last update
List of publications.
2019 R. Matsumoto, S. Lequeux, H. Imamura, J. Grollier
Chaos and Relaxation Oscillations in Spin-Torque Windmill Spiking Oscillators
published pages: , ISSN: 2331-7019, DOI: 10.1103/PhysRevApplied.11.044093
Physical Review Applied 11/4 2019-11-28
2019 M. Riou, J. Torrejon, B. Garitaine, F. Abreu Araujo, P. Bortolotti, V. Cros, S. Tsunegi, K. Yakushiji, A. Fukushima, H. Kubota, S. Yuasa, D. Querlioz, M.D. Stiles, J. Grollier
Temporal Pattern Recognition with Delayed-Feedback Spin-Torque Nano-Oscillators
published pages: , ISSN: 2331-7019, DOI: 10.1103/PhysRevApplied.12.024049
Physical Review Applied 12/2 2019-11-28
2018 Miguel Romera, Philippe Talatchian, Sumito Tsunegi, Flavio Abreu Araujo, Vincent Cros, Paolo Bortolotti, Juan Trastoy, Kay Yakushiji, Akio Fukushima, Hitoshi Kubota, Shinji Yuasa, Maxence Ernoult, Damir Vodenicarevic, Tifenn Hirtzlin, Nicolas Locatelli, Damien Querlioz, Julie Grollier
Vowel recognition with four coupled spin-torque nano-oscillators
published pages: 230-234, ISSN: 0028-0836, DOI: 10.1038/s41586-018-0632-y
Nature 563/7730 2019-05-22
2018 D. Pinna, F. Abreu Araujo, J.-V. Kim, V. Cros, D. Querlioz, P. Bessiere, J. Droulez, J. Grollier
Skyrmion Gas Manipulation for Probabilistic Computing
published pages: , ISSN: 2331-7019, DOI: 10.1103/PhysRevApplied.9.064018
Physical Review Applied 9/6 2019-05-22
2018 Alice Mizrahi, Julie Grollier, Damien Querlioz, M. D. Stiles
Overcoming device unreliability with continuous learning in a population coding based computing system
published pages: 152111, ISSN: 0021-8979, DOI: 10.1063/1.5042250
Journal of Applied Physics 124/15 2019-05-22
2019 D. Marković, N. Leroux, M. Riou, F. Abreu Araujo, J. Torrejon, D. Querlioz, A. Fukushima, S. Yuasa, J. Trastoy, P. Bortolotti, J. Grollier
Reservoir computing with the frequency, phase, and amplitude of spin-torque nano-oscillators
published pages: 12409, ISSN: 0003-6951, DOI: 10.1063/1.5079305
Applied Physics Letters 114/1 2019-05-22

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