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Energy-efficient Neuromorphic 2D Devices and Circuits for Edge AI Computing

CORDIS · observation · Publication date unknown

Energy-efficient Neuromorphic 2D Devices and Circuits for Edge AI Computing ENERGIZE aims to implement novel neuromorphic hardware based on two-dimensional (2D) materials for energy efficient artificial intelligence (AI). This technological breakthrough will be sustained on memristive, ferroelectric and floating gate two- and three-terminal devices based on 2D materials. ENERGIZE seeks to enhance the hardware for the implementation of artificial neural networks through chiplet-based multi-core in-memory computing technologies, providing also guidelines for evaluating and benchmarking 2D devices and circuits. ENERGIZE will be conducted by interconnected research integrating partners of Europe and Korea, accelerating the advancement of neuromorphic technology. ENERGIZE will demonstrate: wafer-scale growth of 2D materials for neuromorphic devices, reliable fabrication and characterization processes of two- and three-terminal devices, development of arrays of 2D devices compatible with existing technologies, efficient inference and training of neural networks in crossbar arrays a

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recordType

award

status

SIGNED

region

EU

value

1499791.25

unit

EUR