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Efficient parallel algorithms for optical computing with the discrete Fourier transform (DFT) primitive.

J H Reif, A Tyagi

    Applied Optics
    |February 12, 2008
    PubMed
    Summary
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    New optical computing models enable faster algorithms for complex tasks like discrete Fourier transforms (DFT). This research presents efficient parallel algorithms for sorting and string matching, nearing theoretical optical computing limits.

    Area of Science:

    • Computer Science
    • Optical Computing
    • Algorithm Design

    Background:

    • Optical computing offers significant speed advantages for computations like the discrete Fourier transform (DFT).
    • Traditional parallel computing models present challenges for designing algorithms that leverage optical computing's speed.
    • The DFT is a computationally intensive task in standard parallel computing models.

    Purpose of the Study:

    • To develop new computational models that accurately represent optical computing capabilities.
    • To establish paradigms for designing efficient parallel algorithms within these new models.
    • To present novel parallel algorithms for various computational problems.

    Main Methods:

    • Development of two new computational models: DFT-VLSIO (very-large-scale integrated optics) and DFT-circuit.

    Related Experiment Videos

  • Introduction of two paradigms for parallel algorithm development tailored to these optical computing models.
  • Design and analysis of parallel algorithms for polynomial and matrix computations, sorting, and string matching.

    • Main Results:

    • Efficient parallel algorithms were developed for polynomial and matrix computations, sorting, and string matching.
    • The developed sorting and string-matching algorithms demonstrate near-optimal performance.
    • Algorithms achieve performance within a polylog factor of established optical computing (VLSIO) lower bounds.

    Conclusions:

    • The new DFT-VLSIO and DFT-circuit models effectively capture the potential of optical computing.
    • The presented parallel algorithms offer significant efficiency improvements for key computational problems.
    • This work advances the design of algorithms for future optical computing systems.