Publication

Modelling of vertical and ferroelectric junctionless technology for efficient 3D neural network compute cube dedicated to embedded artificial intelligence

David Atienza Alonso, Giovanni Ansaloni, Alexandre Sébastien Julien Willommet
2021
Conference Papers

Abstract

This paper presents the set of simulation means used to develop the concept of N2C2 (neural network compute cube) based on a vertical transistor technology platform. On the basis of state-of-the-art junctionless nanowire transistors (JLNT), TCAD simulation, compact modeling and EM simulation are leveraged through a Design- Technology Co-Optimization (DTCO) to achieve innovative 3D circuit architectures. Further, System-Technology Co-Optimization (STCO) implications on 3D NN system architecture are explored.

Official source

https://infoscience.epfl.ch/entities/publication/d4fbdb21-b7f0-4d71-990a-c0e5a5d12313

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Modelling of vertical and ferroelectric junctionless technology for efficient 3D neural network compute cube dedicated to embedded artificial intelligence

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