We are currently experiencing intermittent issues impacting performance. We apologize for the inconvenience.
By Topic

A high-speed digital neural network chip with low-power chain-reaction architecture

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Uchimura, K. ; NTT LSI Lab., Kanagawa, Japan ; Saito, O. ; Amemiya, Y.

A high-speed digital neural network chip adopts a polyhedric discrimination neuron (PDN) model and low-power chain-reaction (LCR) architecture that can reduce the power dissipation to one-fiftieth or less. The chip contains 832 fully implemented digital synapse units that form 13 neurons on a 10.3-mm×14.1-mm die using 0.8-μm CMOS technology. The synapse weights are updated using an external computer. A computational speed of 8 billion connections per second (GCPS) is achieved with low 54-mW power dissipation. The forward propagation time is 104 ns. These features make it possible to implement large-scale neural network chips and systems

Published in:

Solid-State Circuits, IEEE Journal of  (Volume:27 ,  Issue: 12 )