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Neurogrid: A Mixed-Analog-Digital Multichip System for Large-Scale Neural Simulations.

Authors :
Benjamin, Ben Varkey
Gao, Peiran
McQuinn, Emmett
Choudhary, Swadesh
Chandrasekaran, Anand R.
Bussat, Jean-Marie
Alvarez-Icaza, Rodrigo
Arthur, John V.
Merolla, Paul A.
Boahen, Kwabena
Source :
Proceedings of the IEEE; May2014, Vol. 102 Issue 5, p699-716, 18p
Publication Year :
2014

Abstract

In this paper, we describe the design of Neurogrid, a neuromorphic system for simulating large-scale neural models in real time. Neuromorphic systems realize the function of biological neural systems by emulating their structure. Designers of such systems face three major design choices: 1) whether to emulate the four neural elements—axonal arbor, synapse, dendritic tree, and soma—with dedicated or shared electronic circuits; 2) whether to implement these electronic circuits in an analog or digital manner; and 3) whether to interconnect arrays of these silicon neurons with a mesh or a tree network. The choices we made were: 1) we emulated all neural elements except the soma with shared electronic circuits; this choice maximized the number of synaptic connections; 2) we realized all electronic circuits except those for axonal arbors in an analog manner; this choice maximized energy efficiency; and 3) we interconnected neural arrays in a tree network; this choice maximized throughput. These three choices made it possible to simulate a million neurons with billions of synaptic connections in real time—for the first time—using 16 Neurocores integrated on a board that consumes three watts. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISSN :
00189219
Volume :
102
Issue :
5
Database :
Complementary Index
Journal :
Proceedings of the IEEE
Publication Type :
Academic Journal
Accession number :
95879368
Full Text :
https://doi.org/10.1109/JPROC.2014.2313565