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Promise and pitfalls of random projection algorithms for optical processors.

Grigorii V Fomin, Dmitrii S Batanov, Egor O Kimlichenko

    Optics Express
    |July 2, 2026
    PubMed
    Summary

    Optical random projection, used in AI computing, offers distance preservation but doesn't significantly boost performance. Its limited impact questions the value of optical processing units for this task.

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    Area of Science:

    • * Emerging field of optical computing.
    • * Application of random projection in artificial intelligence (AI).
    • * High-dimensional data analysis and machine learning.

    Background:

    • * Random projection utilizes Gaussian i.i.d. matrices for efficient distance preservation in high-dimensional spaces.
    • * Key machine learning algorithms leverage random projection for improved computational efficiency.
    • * Optical implementations promise time and energy savings in computation.

    Purpose of the Study:

    • * Analyze algorithms employing random projection.
    • * Evaluate the performance enhancement offered by optical random projection.
    • * Investigate the computational time contribution of random projection within algorithms.

    Main Methods:

    • * Comprehensive analysis of algorithms including randomized singular value decomposition (RSVD), NEWMA, reservoir computing, and direct feedback alignment (DFA).

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  • * Examination of optical implementations of random projection.
  • * Performance and computational time assessment of these methods.

    • Main Results:

    • * Random projection constitutes a minor fraction of total computational time in analyzed algorithms.
    • * Optical random projection does not yield significant performance enhancements.
    • * Existing optical random projection initiatives show limited practical benefits.

    Conclusions:

    • * The computational advantage of random projection in optical computing is questionable.
    • * Further research is needed to determine the true relevance of optical random projection units.
    • * Current limitations suggest a need for re-evaluation of optical processing unit applications.