Francois Andireu

Institution d’accueil : French Alternative Energies and Atomic Energy Commission

Laboratoire : LETI

Appel à projets : Consolidator (PE7)

Nom du projet : MY-CUBE – 3D integration of a logic/memory CUBE for In-Memory-Computing

Montant : 2.73 M€

Description :

For integrated circuits to be able to leverage the future “data deluge” coming from the cloud and cyber-physical systems, the historical scaling of Complementary-Metal-Oxide-Semiconductor (CMOS) devices is no longer the corner stone. At system-level, computing performance is now strongly power-limited and the main part of this power budget is consumed by data transfers between logic and memory circuit blocks in widespread Von-Neumann design architectures. An emerging computing paradigm solution overcoming this “memory wall” consists in processing the information in-situ, owing to In-Memory-Computing (IMC). However, today’s existing memory technologies are ineffective to In-Memory compute billions of data items, as it is the case in the brain. Things may change with the emergence of three key enabling technologies: non-volatile resistive memory, new energy-efficient nanowire transistors and 3D-monolithic. My-CUBE will leverage them towards a functionality-enhanced system with a tight entangling of logic and memory. Only such a technology can support the scalability of the IMC concept. Following a holistic approach from the system to the material, My-CUBE unique solution relies on a new class of nano-technology, mixing at the fine-grain level a high capacity of non-volatile resistive memory coupled with new junctionless nanowire transistors 3D-interconnected at low-temperature, to perform data-centric computations. A 3D IMC accelerator circuit will be designed, manufactured and measured, targeting a 20x reduction in (Energy x Delay) Product vs. Von-Neumann systems. This technology that adds smartness to memory/storage will not only be a game changer for artificial intelligence, machine learning, data analytics or any data-abundant computing systems but it will also be, more broadly, a key computational kernel for next low-power, energy-efficient European integrated circuits.