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PsD-DRT-21-0025
Artificial intelligence & Data intelligence
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)
Laboratoire d’Intégration des Composants pour la Logique
Grenoble
HUTIN Louis
CEA
DRT/DCOS//LICL
CEA / LETIDépartement Composants SiliciumLaboratoire d'Intégration des Composants pour la Logique17, rue des Martyrs38054 Grenoble Cedex 9
Phone number: 04.38.78.04.78
Email: louis.hutin@cea.fr
As soon as possible
Title | Post Doc - Hybrid CMOS / spintronic circuits for Ising machines |
Employer | CEA Tech |
Job location | CEA, 17 rue des Martyrs, 38054 Grenoble |
Published | November 18, 2020 |
Application deadline | Unspecified |
Job types | Postdoc   |
Fields | Artificial Intelligence,   Artificial Neural Network,   Data Mining,   Condensed Matter Physics,   Big Data,   Machine Learning   |