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
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Creator |
RAJENDRAN, B
LIU, Y SEO, JS GOPALAKRISHNAN, K CHANG, L FRIEDMAN, DJ RITTER, MB |
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Subject |
CMOS
hybrid integrated circuits neural network hardware resistive random access memory (RRAM) PLASTICITY NEURONS |
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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.
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Publisher |
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
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Date |
2014-10-15T12:21:50Z
2014-10-15T12:21:50Z 2013 |
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Type |
Article
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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 |
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Language |
en
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