ECSEL JU Project Tempo


Massive adoption of computing in all aspects of human activity has led to unprecedented growth in the amount of data generated. Machine learning has been employed to classify and infer patterns from this abundance of raw data, at various levels of abstraction. Among the algorithms used, brain-inspired, or “neuromorphic”, computation provides a wide range of classification and/or prediction tools. Additionally, certain implementations come about with a significant promise of energy efficiency: highly optimized Deep Learning engines, ranging up to the efficiency promise of exploratory Spiking Neural Networks (SNN). Given the slowdown of silicon-only scaling, it is important to extend the roadmap of neuromorphic implementations by leveraging fitting technology innovations. Along these lines, the current project aims to sweep technology options, covering emerging memories and 3D integration, and attempt to pair them with contemporary Deep Learning (DL) and exploratory (SNN) neuromorphic computing paradigms. The process- and design-compatibility of each technology option will be assessed with respect to established integration practices. Core computational kernels of such DL/SNN algorithms (e.g. dot-product or integrate-and-fire engines) will be reduced to practice in representative demonstrators. Willing to address the needs of end-users applicative sectors (aviation, automotive, etc.), the TEMPO project has integrated the main European actors of each sector to participate to the specification of needs data set definition. This allows the TEMPO partners to complement each other in a near-optimal way so as to provide Europe with a substantiated competitive advantage and a faster time-to-market opportunity in roll-out of the technology roadmap of neuromorphic implementations throughout the different sectors involved.

ECS Strategic Research Agenda focus areas:

ECSEL Call 2018

Start date: 04/2019

Duration: 36 months

Project coordinator:

Christine Van Houtven

Number of partners: 19

Number of countries: 4

Total investment: M€ 10

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