Nano Archive

Self-organized computation with unreliable, memristive nanodevices

Snider, G. S. (2007) Self-organized computation with unreliable, memristive nanodevices. NANOTECHNOLOGY, 18 (36).

Full text is not hosted in this archive but may be available via the Official URL, or by requesting a copy from the corresponding author.

Official URL: http://www.iop.org/EJ/abstract/0957-4484/18/36/365...

Abstract

Nanodevices have terrible properties for building Boolean logic systems: high defect rates, high variability, high death rates, drift, and ( for the most part) only two terminals. Economical assembly requires that they be dynamical. We argue that strategies aimed at mitigating these limitations, such as defect avoidance/reconfiguration, or applying coding theory to circuit design, present severe scalability and reliability challenges. We instead propose to mitigate device shortcomings and exploit their dynamical character by building self-organizing, self-healing networks that implement massively parallel computations. The key idea is to exploit memristive nanodevice behavior to cheaply implement adaptive, recurrent networks, useful for complex pattern recognition problems. Pulse-based communication allows the designer to make trade-offs between power consumption and processing speed. Self-organization sidesteps the scalability issues of characterization, compilation and configuration. Network dynamics supplies a graceful response to device death. We present simulation results of such a network-a self-organized spatial filter array-that demonstrate its performance as a function of defects and device variation.

Item Type:Article
Uncontrolled Keywords:CELL RECEPTIVE-FIELDS; NEURAL NETWORKS; FEATURE-DETECTORS; VISUAL-CORTEX; ARCHITECTURE; CIRCUITS; ORIENTATION; DEVICES; SYSTEMS; MODEL
Subjects:Material Science > Nanochemistry
ID Code:6451
Deposited By:IoN
Deposited On:23 Sep 2009 12:15
Last Modified:23 Sep 2009 12:15

Repository Staff Only: item control page