Scalable, ferroelectric based accelerators for energy efficient edge AI

Informations projet

Ferro4EdgeAI

N° de convention de subvention: 101135656

DOI

10.3030/101135656

Date de signature de la CE 25 Octobre 2023

Date de début 1 Janvier 2024

Date de fin 31 Decembre 2027

Financé au titre de

• Digital, Industry and Space

Coût total

€ 3 959 917,25

Contribution de l’UE

€ 3 750 364,25

Coordonné par

COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES
France

Periodic Reporting for period 1 - Ferro4EdgeAI (Scalable, ferroelectric based accelerators for energy efficient edge AI)

Période du rapport: 2024-01-01 au 2025-06-30

Résumé du contexte et des objectifs généraux du projet

The project aims to develop an ultra-low power, scalable edge accelerator for edge intelligence. Our innovative solution incorporates a memory-augmented neural network, based on Back End of Line (BEoL) integrated ferroelectric (FE) technology. The consortium partners bring a range of expertise across the entire value chain, from device technology to prototypes and systems simulations. The goal is to maximise the advantages of FE technology, including reliability, durability, high energy efficiency, low latency, and scalability.

Travail effectué depuis le début du projet jusqu’à la fin de la période considérée dans le rapport et principaux résultats atteints jusqu’à présent

The key performance indicators of each stage of the value chain, from materials, through devices, bitcells, arrays and circuits have been defined and related to one another. This provides us with firm guidelines for the project work. Design and simulations of the accelerator blocks has started. The first wafers with novel FeFET-2 circuits have been produced, novel bitcells for future wafers have been designed and the optimal material properties defined.

Progrès au-delà de l’état des connaissances et impact potentiel prévu (y compris l’impact socio-économique et les conséquences sociétales plus larges du projet jusqu’à présent)

The device at the heart of FerroEdgeAI is a non-volatile memory cell consisting of a ferroelectric capacitor made using hafnium zirconate, wired to a standard CMOS field effect transistor. This device has the enormous advantage of being ultra-low power and, at the same time, allows a non-destructive, fast read of its memory state, whether that be analogue or digital. It can therefore reply to the needs of data intensive, edge intelligence. The consortium has already defined the optimal material parameters and is currently integrating the device into novel circuits

The projected energy gain of ferroelectric accelerator (NV-XBAR) with respect to baseline micro-cont

The ferrolectric memory cell, called FeFET-2, of Ferro4EdgeAI