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Active HORIZON European Commission

A multiprocessor system on chip with in-memory neural processing unit

€7.95M EUR

Funder European Commission
Recipient Organization Stmicroelectronics Srl
Country Italy
Start Date Sep 01, 2022
End Date Feb 28, 2026
Duration 1,276 days
Number of Grantees 14
Roles Participant; Associated Partner; Third Party; Coordinator
Data Source European Commission
Grant ID 101070634
Grant Description

Deployment of intelligence at the edge presents many challenges because devices need to be low-cost and, as such, they are often constrained in computing capacity, memory, and energy resources.These constraints are not compatible with the need for much more advanced AI algorithms calling for Mbytes of storage and tens of GOPS per inference and call for leaner edge AI algorithms.

The current state of the art for (the few) edge-AI chips relies on low-cost process technologies at 90 or 40nm and in some cases up to 16nm, with power efficiency between 1-5 TOPS/w and power densities up to 1 TOPS/mm2.Recently several industrial projects and a few products have started to surface pursing neuromorphic and in memory computing, but none of these efforts have reached a level of maturity compatible with a mass volume production and cost, and, moreover the technology base they rely on is either not scalable to more advanced nodes (flash) or, targeting AI computing algorithms whose practical applications are yet to be fully proven (e.g., spiking).

The NeuroSoC approach instead is to rely on a solid, mature, and qualified reliable Phase Change Memory technology to create an industrially proven path to go past the state of the art, as such, the NeuroSoC chip pre-product demonstration of the technology will be the first of his kind worldwide.NeuroSoC’s aim is to develop an advanced Multi-Processor System on Chip prototype in FD-SOI 28nm CMOS technology that tightly integrates an AIMC IMNPU unit, a local digital processing subsystem, and functional safe multiprocessor host subsystems based on an enhanced version of existing RISC-V microprocessor implementation, while covering IMNPU security aspects holistically to tackle the requirements of a wide set of edge-AI applications.The project will leverage STMicroelectronics’s unique high-density embedded PCM cell process technology being the denser and only such technology qualified and mature for embedded use in the industry world

All Grantees

Ubotica Technologies Limited; Universiteit Leiden; Robert Bosch Gmbh; Ibm Research Gmbh; Stmicroelectronics Rousset Sas; Software Competence Center Hagenberg Gmbh; Universita Degli Studi Di Pavia; Eidgenoessische Technische Hochschule Zuerich; Benkei; Alma Mater Studiorum - Universita Di Bologna; Thales; Stmicroelectronics Srl; Panepistimio Patron; King's College London

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