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Characterization of SiN Integrated Optical Phased Arrays on a Wafer-Scale Test Station
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Published on: April 1, 2020

Fiber-optic array algebraic processing architectures.

N Q Ngo, le N Binh

    Applied Optics
    |November 2, 2010
    PubMed
    Summary

    A novel fiber-optic array processor (FOAP) achieves high accuracy for complex matrix operations using digital multiplication by analog convolution. This optical computing approach offers a promising alternative to digital methods.

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    Area of Science:

    • Optical Computing
    • Digital Signal Processing
    • Computer Architecture

    Background:

    • Traditional digital processors face limitations in speed and power consumption for large-scale matrix operations.
    • Fiber-optic technologies offer potential for high-bandwidth, low-loss data transmission and processing.

    Purpose of the Study:

    • To propose a high-accuracy fiber-optic array processor (FOAP) architecture.
    • To explore its application in various binary arithmetic matrix operations.
    • To compare its performance against existing digital and optical architectures.

    Main Methods:

    • Development of a FOAP architecture utilizing an array of all-optical elemental-processing units.
    • Implementation of digital multiplication by analog convolution algorithm.
    • Design of FOAP matrix multipliers for nonnegative and twos-complement binary arithmetic.
    • Comparative performance analysis with time-integrating, space-integrating, and digital multipliers.

    Main Results:

    • Demonstration of a high-accuracy FOAP for matrix-vector, matrix-matrix, triple-matrix, and high-order matrix operations.
    • Successful implementation of binary programmable fiber-optic transversal filters.
    • Validation of the FOAP architecture's effectiveness through performance comparisons.

    Conclusions:

    • The proposed FOAP architecture provides a viable and accurate method for optical matrix multiplication.
    • The digital multiplication by analog convolution algorithm is effectively extended for optical implementation.
    • FOAP presents a competitive alternative to conventional digital multipliers for specific computational tasks.

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