Hybrid Dram Next Gen Ferroelectric Memory For Normally-Off - Instant-On Embedded Systems H/F - 38

Le CEA est un acteur majeur de la recherche, au service des citoyens, de l'économie et de l'Etat.

Il apporte des solutions concrètes à leurs besoins dans quatre domaines principaux : transition énergétique, transition numérique, technologies pour la médecine du futur, défense et sécurité sur un socle de recherche fondamentale. Le CEA s'engage depuis plus de 75 ans au service de la souveraineté scientifique, technologique et industrielle de la France et de l'Europe pour un présent et un avenir mieux maîtrisés et plus sûrs.

Implanté au coeur des territoires équipés de très grandes infrastructures de recherche, le CEA dispose d'un large éventail de partenaires académiques et industriels en France, en Europe et à l'international.

Les 20 000 collaboratrices et collaborateurs du CEA partagent trois valeurs fondamentales :

- La conscience des responsabilités
- La coopération
- La curiositéWhat is CEA LIST?
The LIST institute is part the CEA (French Alternative Energies and Atomic Energy Commission) Technology Research Division. CEA-LIST brings together nearly 1,000 scientists, engineers and technicians, expert in smart digital systems. We are committed to developing high-added-value innovations that respond to the major challenges facing our economy and society. This internship will take place in the Grenoble site of the CEA-List institute, in a research team focused on integrated circuits design for a variety of applications (e.g., cybersecurity, Internet of Things, artificial intelligence, emerging technologies).

Internship description
Thanks to the use of Hafnium Zirconium Oxide (HZO) stacks, it is now possible to fabricate ferroelectric memories that are both highly scalable and compatible with standard CMOS processes. These memories combine high integration density, comparable to current DRAM technologies, with the unique ability to exhibit both volatile and non-volatile behavior.
The objective of this internship is to evaluate the potential of such hybrid memories for normally-off / instant-on embedded systems, and to quantify the optimal partitioning between volatile and non-volatile regions. The study will help define design guidelines at the macro-architecture, memory controller, and even OS memory management levels.
During the internship, the student will use tracing tools and realistic workloads to characterize memory activity and energy behavior. The work will combine architectural modeling, software-level profiling, and system-level energy analysis.