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Published on 7 December 2023
Research FieldArtificial intelligence & Data intelligence

Domaine-SMesoscopic physics

ThemeTechnological challenges

Theme-SCondensed matter physics, chemistry & nanosciences

Artificial intelligence & Data intelligence Technological challenges Mesoscopic physics Condensed matter physics, chemistry & nanosciences DRT DCOS S3C LDQC Grenoble
Hybrid CMOS / spintronic circuits for Ising machines
The proposed research project is related to the search for hardware accelerators for solving NP-hard optimization problems. Such problems, for which finding exact solutions in polynomial time is out of reach for deterministic Turing machines, find many applications in diverse fields such as logistic operations, circuit design, medical diagnosis, Smart Grid management etc. One approach in particular is derived from the Ising model, and is based on the evolution (and convergence) of a set of binary states within an artificial neural network (ANN).In order to improve the convergence speed and accuracy, the network elements may benefit from an intrinsic and adjustable source of fluctuations. Recent proof-of-concept work highlights the interest of implementing such neurons with stochastic magnetic tunnel junctions (MTJ). The main goals will be the simulation, dimensioning and fabrication of hybrid CMOS/MTJ elements. The test vehicles will then be characterized in order to validate their functionality. This work will be carried out in the frame of a scientific collaboration between CEA-Leti and Spintec.
Département Composants Silicium (LETI) Service des Composants pour le Calcul et la Connectivité Laboratoire Dispositifs Quantiques et Connectivité
HUTIN Louis CEA DRT/DCOS//LDMC CEA 17 rue des martyrs 38054 Grenoble Cedex
Start date1/1/2021

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