Research

AMfoRS

Architectures and Methods for Resilient Systems
since 2015


Research topics

photo AMfoRS

The AMfoRS team targets crucial challenges regarding resilient integrated systems. Our goal is twofold: guarantee that systems will not behave unexpectedly and ensure a substantial level of robustness and security. Our work aims at increasing the synergies between verification technologies and activities on the design and validation of reliable, safe and secure integrated systems, with a focus on digital parts.
The expected outcomes of our research include methods, tools and hardware blocks necessary to justify trust in increasingly complex integrated systems and even cyber-physical systems.
The team takes part in several scientific challenges identified not only at the laboratory level, but also in the Research "poles" of University Grenoble-Alpes (especially the MSTIC pole) and more generally at the national level (French strategic directions) and international level (in particular European H2020 priorities).

Team leader

MAISTRI Paolo

Last publications

Garay Trindade M., Benevenuti F., Letiche M., Beaucour J., Kastensmidt F., Possamai Bastos R., Effects of thermal neutron radiation on a hardware-implemented machine learning algorithm, Microelectronics Reliability, Ed. Elsevier, Vol. 116, No. 114022, DOI: 10.1016/j.microrel.2020.114022, 2021
 
Morgül M.C., Frontini L., Tunali O., Anghel L., Ciriani V., Vatajelu I., Moritz C.A., Stan M., Alexandrescu D., Altun M., Circuit Design Steps for Nano-Crossbar Arrays: Area-Delay-Power Optimization with Fault Tolerance, IEEE transactions on Nanotechnology, Ed. IEEE, Vol. , DOI: 10.1109/TNANO.2020.3044017, 2020
 
Anghel L., Bernasconi A., Ciriani V., Frontini L., Trucco G., Vatajelu I., Stuck-At Fault Mitigation of Emerging Technologies Based Switching Lattices, Journal of Electronic Testing: Theory and Applications, Ed. Springer , Vol. , pp. 313–326, DOI: 10.1007/s10836-020-05885-2, 2020
 
Garay Trindade M., Garibotti R.F., Ost L., Letiche M., Beaucour J., Possamai Bastos R., Assessment of Machine Learning Algorithms for Near-Sensor Computing Under Radiation Soft Errors, 16th International School on the Effects of Radiation on Embedded Systems for Space Applications (SERESSA 2020), Porto Alegre (Virtual edition), BRAZIL, 2020
 
Garay Trindade M., Garibotti R.F., Ost L., Letiche M., Beaucour J., Possamai Bastos R., Assessment of Machine Learning Algorithms for Near-Sensor Computing Under Radiation Soft Errors, IEEE International conference on electronics, circuits & systems (ICECS 2020), Glasgow, SCOTLAND, UNITED KINGDOM, 2020
 
Annual activity report