ARTIFICIAL INTELLIGENCE

Overview

The transversal team aims at bringing together all competencies from SPINTEC involving spintronic devices nanofabrication, characterization, circuit integration, architecture and algorithm techniques to implement hardware solutions for AI and unconventional computing applications that are hard to be with current CMOS technologies.

Spintronic based multifunctional devices are also a great opportunity to improve the energy efficiency. Moreover, the high speed and endurance magnetic devices allow more sophisticated learning algorithms implementations such as unsupervised learning, reinforcement learning, etc, crossing the gap between current edge AI implementations and the real brain computing ability.

Research topics

Bio-inspired computing

As the brain performs very sophisticated operations and consumes only few Watts, brain-inspired/neuromorphic computing is very promising path for which spintronic devices can efficiently emulate both neurons and synapses in hardware. Their nanometric size, sensitivity to input stimuli, and interactions makes those devices ideal to implement large arrays of neuro-synaptic elements. In addition, these types of architectures are very well suited to new learning rules and adaptation.  Performant and highly energy efficient, analog, voltage or current-tunable spintronic-based memristors can emulate neurons and massive dynamic connections required to solve complex, non-linear operations: Spintronic nanoscillators, spintronic and ferroelectric memristors, magnetic memories, super paramagnetic and magnetic tunnel junctions, skyrmions, etc.

Probabilistic computing

Biologically inspired operations can take huge benefit from noise, which, in current nanotechnology is considered as an issue.  Indeed, noise can be a crucial ingredient to emulate the stochastic nature of neural activity and used for computing.  In this context, probabilistic computing is particularly suitable approach that relaxes usual precision constraints.  Stochastic circuits and architectures largely benefit from spintronic based device implementations aiming at performing new energy-based or temporal-based machine learning models. The truly random nature of spintronic devices (such as magnetic and super paramagnetic tunnel junctions) makes them attractive for hardware implementations of AI and unconventional computing.

In memory computing

The most promising solutions for non-Von Neumann, in-memory computing architectures are based on the use of emerging technologies, that are able to act as both storage and information processing units thanks to their specific physical properties. High accuracy, Deep neural networks (DNN) can be built with crossbars analog in memory computing concept, involving MRAM families, such as STT, SOT, VCMA, but also with more exotic families of magneto-resistive, and ferroelectric or skyrmion based devices.

The team

Projects

  • IRS SPINBRAIN (2020-2022)
  • ANR Spinspike (2020-2024)
  • HANS, UGA (2019-2022)

Partners

  • CEA LIST
  • UMPHY
  • CEA LETI

Recent news

  • Seminar – Magnetic Josephson Junctions for artificial synapses (December 09th, 2021)Seminar - Magnetic Josephson Junctions for artificial synapses
    On Wednesday, February 09th at 10:30 Due to the pandemic situation, this seminar is cancelled (possibly reported to May 2022) Emilie Jué from Univ. of Colorado Boulder and NIST will give us a seminar entitled: Magnetic ...
  • STOCHNET – An ANR project (December 09th, 2021)STOCHNET – An ANR project
    STOCHNET stands for Hybrid Stochastic Tunnel Junction Circuits for Optimization and Inference. The motivation behind StochNet is to explore — through experimental demonstrations with hybrid CMOS stochastic tunnel junction circuits and simulations of theoretical ...
  • 24 months postdoc position – spintronic unconventional computing using stochastic magnetic tunnel junctions (December 02nd, 2021)24 months postdoc position - spintronic unconventional computing using stochastic magnetic tunnel junctions
    In the frame of the joint US-French NSF-ANR project StochNet, Spintec laboratory is opening a postdoctoral researcher position. The candidate will work on stochastic magnetic tunnel junctions grown and fabricated at Spintec, and will use ...
  • Masters thesis projects for Spring 2022 (September 17th, 2021)Masters thesis projects for Spring 2022
    You find here the list of proposals for Master-2 internships to take place at Spintec during Spring 2022. In most cases, these internships are intended to be suitable for a longer-term PhD work. Interested Master-1 ...
  • Post-doctoral positions – Coupled nano-oscillator arrays for brain inspired computing (August 04th, 2021)Post-doctoral positions - Coupled nano-oscillator arrays for brain inspired computing
    SPINTEC laboratory (Grenoble, France), in collaboration with CEA-LETI, has currently two postdoc position openings to work on theory (12 month) and on experiment (18 month) of coupled oscillator arrays for implementing neuromorphic and unconventional computing ...

Publications

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