A Custom 7nm CMOS Standard Cell Library for Implementing TNN-based Neuromorphic Processors

2020/12/10 by Nair, Harideep, Vellaisamy, Prabhu, Bhasuthkar, Santha +1
#Emerging Technologies (cs.ET) #FOS: Computer and information sciences #Hardware Architecture (cs.AR) #Machine Learning (cs.LG) #Neural and Evolutionary Computing (cs.NE)

paper · doi:10.48550/arxiv.2012.05419

Abstract

A set of highly-optimized custom macro extensions is developed for a 7nm CMOS cell library for implementing Temporal Neural Networks (TNNs) that can mimic brain-like sensory processing with extreme energy efficiency. A TNN prototype (13,750 neurons and 315,000 synapses) for MNIST requires only 1.56mm2 die area and consumes only 1.69mW.

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