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Specifications of Nanoscale Devices and Circuits for Neuromorphic Computational Systems

DSpace at IIT Bombay

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Title Specifications of Nanoscale Devices and Circuits for Neuromorphic Computational Systems
 
Creator RAJENDRAN, B
LIU, Y
SEO, JS
GOPALAKRISHNAN, K
CHANG, L
FRIEDMAN, DJ
RITTER, MB
 
Subject CMOS
hybrid integrated circuits
neural network hardware
resistive random access memory (RRAM)
PLASTICITY
NEURONS
 
Description The goal of neuromorphic engineering is to build electronic systems that mimic the ability of the brain to perform fuzzy, fault-tolerant, and stochastic computation, without sacrificing either its space or power efficiency. In this paper, we determine the operating characteristics of novel nanoscale devices that could be used to fabricate such systems. We also compare the performance metrics of a million neuron learning system based on these nanoscale devices with an equivalent implementation that is entirely based on end-of-scaling digital CMOS technology and determine the technology targets to be satisfied by these new devices. We show that neuromorphic systems based on new nanoscale devices can potentially improve density and power consumption by at least a factor of 10, as compared with conventional CMOS implementations.
 
Publisher IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
 
Date 2014-10-15T12:21:50Z
2014-10-15T12:21:50Z
2013
 
Type Article
 
Identifier IEEE TRANSACTIONS ON ELECTRON DEVICES, 60(1)246-253
http://dx.doi.org/10.1109/TED.2012.2227969
http://dspace.library.iitb.ac.in/jspui/handle/100/14892
 
Language en