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15 - Visual microprocessors – analog and digital VLSI implementation of the CNN Universal Machine

Published online by Cambridge University Press:  28 May 2010

Leon O. Chua
Affiliation:
University of California, Berkeley
Tamas Roska
Affiliation:
Hungarian Academy of Sciences, Budapest
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Summary

Digital technology has the key advantage that if a few building blocks are implemented then any complex system can be built from these by

  • wiring and

  • programming.

Moreover, most of the digital building blocks are placed in a regular arrangement: a simple block is repeated many times in a matrix arrangement (e.g. memories, PLAs, etc.).

The CNN core and the CNN Universal Machine architecture, containing also analog building blocks, possess the very same properties. Due to their special nature, however, they have orders of magnitude advantages in speed, power, and area (SPA) in some standard physical implementations. In many applications, like image flow computing, this advantage might be mission critical.

As a revolutionary feature, stored programmability can be introduced in the analog domain as well. This makes it possible to fabricate visual microprocessors.

In what follows, first, we show the building blocks and their simple CMOS implementation examples, without going into the details of their design issues. The emulated digital implementation will be only briefly reviewed. As to this and the optical implementation, we refer to the literature.

As a summary: using only six simple circuit building blocks, namely:

  • resistor,

  • capacitor,

  • switch,

  • VCCS (Voltage Controlled Current Source),

  • logic register, and

  • logic gate,

the most complex CNN array computer chip can be built in a VLSI friendly, regular structure.

Next, the visual microprocessor and its computational infrastructure is described.

Type
Chapter
Information
Cellular Neural Networks and Visual Computing
Foundations and Applications
, pp. 303 - 319
Publisher: Cambridge University Press
Print publication year: 2002

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