Project description DEENESFRITPL Smart memory in computers to address data deluge Conventional silicon computing utilises separate chips for computing and data storage. This creates a bottleneck for data analytics, machine learning and artificial intelligence applications that require ever-larger data transfers between processing and memory units. In-memory computing is an emerging data-processing technology that could solve the big-data energy crunch facing traditional architectures. The EU-funded project MY-CUBE proposes an innovative design that minimises data movement by integrating computing and data storage. The new design features a 3D computer architecture that uses junctionless nanowire transistors and resistive random-access memory cells that are built vertically over one another. It will be able to store massive amounts of data and perform on-chip processing to extract relevant information from a data deluge. Show the project objective Hide the project objective Objective 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. Fields of science engineering and technologynanotechnologynatural sciencescomputer and information sciencesartificial intelligencemachine learning Programme(s) H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) Main Programme Topic(s) ERC-2018-COG - ERC Consolidator Grant Call for proposal ERC-2018-COG See other projects for this call Funding Scheme ERC-COG - Consolidator Grant Coordinator COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES Net EU contribution € 2 734 139,00 Address Rue leblanc 25 75015 Paris France See on map Region Ile-de-France Ile-de-France Paris Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00 Beneficiaries (1) Sort alphabetically Sort by Net EU contribution Expand all Collapse all COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES France Net EU contribution € 2 734 139,00 Address Rue leblanc 25 75015 Paris See on map Region Ile-de-France Ile-de-France Paris Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00