Press briefing

On the way to brain-like computing

19.2.2020

Within the EU project NeurONN, a research team from Fraunhofer EMFT is working with six European partners on extremely energy-efficient elements and architectures for neuromorphic computing. This also involves the use of innovative 2D materials.

The NeurONN research team at the kick-off meeting
© CNRS
The NeurONN research team at the kick-off meeting
Thermal assisted chemical vapor deposition on 8inch wafer.
© Fraunhofer EMFT / Bernd Müller
Thermal assisted chemical vapor deposition on 8inch wafer.
© Fraunhofer EMFT
Interconnected neurons

It is an exciting new research area that is becoming increasingly important in the context of the AI (artificial intelligence) megatrend: so-called neuromorphic computing uses technologies that imitate the human brain and nervous system. It is thus predestined to solve complex and comprehensive associative learning problems. At the same time, it offers the opportunity to significantly reduce the energy consumption of current silicon-based circuits.

In the EU project NeurONN, launched in early 2020, a research team from Fraunhofer EMFT is working with six European partners on a new neuromorphic approach based on energy-efficient elements and architectures. In the proposed neurologically inspired computer architecture, information is encrypted in the phase of coupled oscillating elements that are interconnected to form a neural network.  Just like the brain, the two key components in neuromorphic computing are called neuron and synapse - they replicate the distributed computing and memory units. The neurons used in the project are novel elements based on vanadium dioxide, which can be 250 times more efficient than state-of-the-art digital oscillators based on CMOS.

The work package of the Fraunhofer EMFT focuses particularly on the synapses: Within the framework of NeurONN, the scientists are developing 2D memristors on a nanoscale based on innovative 2D nanomaterials. The tiny devices are expected to be 330 times more efficient in terms of operating speed, lifetime and energy consumption than currently used technologies.

The project with a duration of 36 months (1 January 2020 - 31 December 2022) brings together leading European research and academic institutions: IBM Research Zurich, the Fraunhofer EMFT, CSIC/University of Seville, Silvaco, UK and AI Mergence, FR. It is coordinated by the French CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS. Additionally, NeurONN has initiated an industrial advisory board including members from Intel Corporation and Prophesee.

The NeurONN kick-off meeting took place in Montpellier (France) on February 4 and 5, 2020 at the premises of LIRMM, CNRS. The project is funded under the EU research program Horizon 2020 under grant number 871501.

Contact person at CNRS: Dr. Aida Todri-Sanial, project coordinator: aida.todri@lirmm.fr.