The team is dedicated to the evaluation of the benefits of using magnetic devices in Integrated Circuits (ICs). It is expected that integrating non-volatility in ICs could contribute to push forward the incoming limits in the microelectronics scaling. This work includes integrating the magnetic devices in standard design tools, design hybrid circuits and evaluate their performance for various applications. The unique combination of advantages of spintronics devices (non-volatility associated with high speed and endurance, analogue capabilities, well controlled stochastic behavior…) allows intrinsically mixing the memory and logic functionalities (in Memory Computing). This opens the way towards new computing paradigms, beyond the standard Von-Newman architecture of computing systems. The most interesting applications addressed in the team are described below.
Hybrid CMOS/Magnetic design flow
Designing hybrid circuits requires integrating the magnetic devices in the standard design flow of microelectronics. This includes compacts models for electrical simulations, technology files including the magnetic back-end and libraries of Standard Cells for digital design.
Low-power logic circuits
One issue related to microelectronics scaling is the increasing standby power, due to leakage currents. Introducing non-volatility in circuits allows easing the power gating technique, which consists in cutting-off the power supply of inactive blocks to save leakage.
IC Reliability: Hardware security & Radiation hardening
While STT MRAM can be beneficial for hardware security (taking advantage of its stochastic behavior for cryptography for instance), it also presents some specific failures mechanisms that has to be studied to take the appropriate countermeasures.
The intrinsic hardness to radiations of the magnetic devices make them a good candidate to be embedded in circuits for space applications. It can be advantageously combined with other hardening technologies or design techniques targeting space applications.
Spiking Neural Networks are seen as a Key building block for strongly improving the energy efficiency of current AI applications and opening up new possibilities (in terms of unsupervised learning, recurrent networks, probabilistic inference, etc.). The scientific challenges to be tackled are the following: the first one is to define power-constrained learning and inference algorithms (online, supervised, unsupervised, probabilistic, etc.). The second one is to design a scalable and flexible SNN architecture, adaptable to the different above-mentioned algorithms, and fabricate that circuit in hybrid nanoscale CMOS and NVM technology, enabling very dense synaptic density. The last objective is to derive a principled toolchain for the algorithm, design, development, and integration of spiking neural networks for future adoption in industrial health and automotive embedded applications.
- NV-APROC, ANR (2019-2023) – MRAM-based Non-volatile Asynchronous Processor
- MISTRAL, ANR (2019-2023) – MRAM/CMOS Hybridization to secure cryptographic algorithms
- SPINBRAIN (2020-2022) – Spintronic-based Neural Network
- HANS, UGA (2019-2022) –
- ELECSPIN, ANR (2016-2020) – Electric-filed control of spin-based phenomena
- Christophe LAYER : Research scientist
- François DUHEM: Research scientist
- Mounia KHARBOUCHE (supervised by G. Di Pendina, R. Wacquez and J.M. Portal) (2016-2019)
- Rana ALHALABI (supervised by G. Di Pendina, E. Nowak and L. Prejbeanu) (2016-2019)
- Jeremy LOPES (supervised by G. Di Pendina, E. Beigne, D. Dangla and L. Torres) (2014-2017)
- Erya DENG (supervised by G. Prenat and L. Anghel) (2014-2017)
- Olivier GONCALVES (supervised by G. Prenat and B. Dieny) (2009-2012)
- Wei GUO (supervised by G. Prenat and B. Dieny) (2006 – 2010)
- Mourad El BARAJI (supervised by G. Prenat and B. Dieny) (2007-2009)
- Pierre VANHAUWAERT (2014-2017)
- Eldar ZIANBETOV (2014-2017)
- Kotb JABEUR (2013-2017)
- Virgile JAVERLIAC (2013-2014)
- Fabrice BERNARD-GRANGER (2013-2014)
- Yun YANG (2012-2013)
- Abdelilah MEJDOUBI (2010-2012)
- Stephane GROS (2013-2014)
- Pierre PAOLI (2013-2014)
- GREAT, H2020 (2016-2019)
- MASTA, ANR (2016-2019)
- NOVELASIC, CEA-nanosciences (2015)
- MAD, CEA internal (2014-2018)
- SPOT, H2020 (2012-2015)
- MARS, ANR (2012-2015)
- DIPMEM, ANR (2012-2015)
- HYMAGINE, ERC Advanced grant (2010-2015)
- Toplink Innovation
- University of Brasov
- CEA Tech (Gardanne)
- EMSE (Gardanne)
- Tiempo Secure
- Dolphin Integration
- Thales TRT
- University of Newcastle
- EM Marin
- Detection of Heating and Photocurrent attacks using Hybrid CMOS/STT-MRAM (March 26th, 2020)
Integrated Circuits (ICs) have to be protected against threatening environmental radiations and malicious perturbations. A large panel of countermeasures have been developed to answer the needs of this challenging field. This work proposes an innovative ...
- PhD defense – Hybridation CMOS/STT-MRAM des circuits intégrés pour la sécurité matérielle de l’Internet des Objets (November 28th, 2019)
On Monday 9th of Decembre at 13h30 Mounia KHARBOUCHE-HARRARI, will defend her thesis, jointly carried out by IM2NP, CEA-Tech and SPINTEC, entitled : « Hybridation CMOS/STT-MRAM des circuits intégrés pour la sécurité matérielle de l’Internet des ...
- Seminar – CMOS-compatible materials and processes for spintronic applications in 300mm R&D (October 21st, 2019)
On Wednesday October 23 at 14:00 we have the pleasure to welcome Maik Wagner-Reetz from Fraunhofer IPMS, Dresden. He will give us a seminar at CEA/SPINTEC, Bat 1005, room 445 entitled : CMOS-compatible materials and processes ...
- Seminar – Dynamics and oscillations in spintronic neural nets (October 03rd, 2019)
On Thursday October 17 at 11:00 we have the pleasure to welcome Julie Grollier from Unité Mixte de Physique CNRS/Thales. She will give us a seminar at CEA/SPINTEC, Bat 1005, room 434A entitled : Dynamics and ...
- Masters thesis projects for Spring 2020 (September 30th, 2019)
You find here the list of proposals for Master-2 internships to take place at Spintec during Spring 2020. In most cases, these internships are intended to be suitable for a longer-term PhD work. Interested Master-1 ...