22Explorations in Morphic Architectures

Tetsuya Asai1 and Ferdinand Peper2

1Graduate School of Information Science and Technology, Hokkaido University, Japan

2Center for Information and Neural Networks, National Institute of Information and Communications Technology, USA

22.1 Introduction

Biological systems give us examples of amorphous, unstructured devices capable of noise- and fault-tolerant information processing. They excel in massively parallel spatial problems, as opposed to digital processors, which are rather weak in that area. The morphic architecture was thus introduced in the Emerging Research Architecture section of ITRS 2007, to refer to biologically inspired architectures that embody a new kind of computation paradigm in which adaptation plays a key role to effectively address the particulars of problems [1]. This chapter focuses on recent progress of two morphic architectures that offer opportunities for emerging nanoelectronic devices: neuromorphic architectures and cellular automaton architectures.

22.2 Neuromorphic Architectures

The term neuromorphic was introduced by Carver Mead in the late 1980s to describe VLSI systems containing electronic analog circuits that mimic neuro-biological architectures in the nervous system [2]. Traditional neurocomputers employ components that are biologically rather implausible, like static threshold elements that represent neurons, whereas neuromorphic architectures are closer to biology. An example of a neuromorphic VLSI ...

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