Symbolic substitution is a spatial logic which is adapted well to optical processing. Unlike Boolean logic it also includes spatial information in the coding. It requires only regular interconnections and nonlinear devices with limited fan-out. Nevertheless the potential of this kind of logic ranges from parallel binary arithmetic to a programmable MIMD processor. Fundamentals of symbolic substitution and its applications are presented.

Digital Optical Computing With Symbolic Substitution

Holographic optical interconnects in dichromated gelatin

We examine the key issues in designing an optical expert system architecture. Our conclusions, however, are extendable to architectures for supporting traditional symbolic processing. To determine the basic operations necessary for constructing an expert system, we examine the underlying symbolic processing languages and their associated computational models. We show that traditional symbolic processing in optics would require efficient means of representing and manipulating complex structured data. This requirement necessitates a location-based addressable memory in optics. Based on the analyses of the computational models, we conclude that the architecture most feasible for optical implementation is that for a combinator graph reduction computational model. We briefly outline a proposed fine-grained optical architecture for this computational model.

Design considerations for an optical symbolic processing architecture

Homo-nipi and hetero-nipi superlattices incorporated into asymmetric Fabry-Perot cavity structures are compared and evaluated for possible use as bit plane optical memory elements in terms of the magnitude of their optical nonlinearities, on-off contrast ratio, insertion loss, carrier lifetimes, and power required to change the state of the structure. Changes in superlattice absorption coefficient as high as 1500 cm/sup -1/ and 1300 cm/sup -1/ have been achieved in type I and type II AlGaAs/GaAs hetero-nipi structures, respectively. When normalized to the GaAs quantum well layer thicknesses, the change in absorption coefficient in the type I superlattice was as high as 12000 cm/sup -1/. In asymmetric cavity modulator structures, on-off reflection contrast ratios as high as 60:1, carrier lifetimes as long as 4 ms, and on-state reflectivities as high as 0.62 have been observed. A 54:1 contrast ratio and an insertion loss of 8.5 dB were achieved simultaneously in a planar Fabry-Perot cavity structure excited with a pump beam power of 3.8 mW. The effective carrier lifetime in this case was 25 /spl mu/s. >

Optical properties of AlGaAs/GaAs nipi superlattices and their application in asymmetric cavity spatial light modulators

This paper presents a case study in the design and analysis of a massively parallel optical computer, SPARO, a novel scalable computer intended for symbolic and numeric computing. SPARO was designed for fine-grained parallel processing of combinator graph reduction, a special case of the graph reduction computational model, found most appropriate for parallel optical processing in earlier studies. The architecture consists of a planar array of optical processors that communicate through simple messages (data packets) over an optical interconnection network. A technique called instruction passing is used to realize distributed control of the architecture. Instruction passing can also be used to implement complex structures such as recursion and iteration. Each individual processor in SPARO is a finite state machine that is implemented using symbolic substitution techniques, while gateable interconnects are used to realize data movements between the processors and network. Performance analysis of SPARO reveals that while discrete computing structures can be implemented using optical techniques, massively parallel optical architectures for traditional computational models are currently unable to compete with electronic ones due to the lack of large scale addressable optical memory devices and large scale integratable optical computing elements. However, optical interconnections appear very promising for providing the network throughput necessary for these parallel architectures.

Designing massively parallel optical computers: a case study.

This paper analyzes potential optical architectures for AI applications (such as knowledge-based systems). Our goal was to investigate architectures most suitable for implementation completely in optics. While optical computing appears to hold much promise because of its inherent parallelism and speed, constructing a symbolic processor or even a general purpose computer in optics requires examining many issues never before addressed. This paper presents these issues and discusses those architectures which appear most feasible in optics. We take into account fundamental physical limitations as well as the state-of-the-art optical device research. We conclude that, unlike in electronics, large-grained parallelism is not suitable for implementation in optics. We also find that functional languages, rather than logic languages, are better candidates for optics. Finally, we show that implementing an optical symbolic processor warrants the need for a real, or at least an emulated, addressable memory in optics.

M. W. Derstine

Papers

Design considerations for an optical symbolic processing architecture

Designing massively parallel optical computers: a case study.

Architectural issues in designing symbolic processors in optics