VCSEL-based Coherent Scalable Deep Learning

Number of patents in Portfolio can not be more than 2000

United States of America

APP PUB NO 20250111218A1
SERIAL NO

18863245

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Abstract

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The exponential growth in deep learning models is challenging existing computing hardware. Optical neural networks (ONNs) accelerate machine learning tasks with potentially ultrahigh bandwidth and nearly no loss in data movement. Scaling up ONNs involves improving scalability, energy efficiency, compute density, and inline nonlinearity. However, realizing all these criteria remains an unsolved challenge. Here, we demonstrate a three-dimensional spatial time-multiplexed ONN architecture based on dense arrays of microscale vertical cavity surface emitting lasers (VCSELs). The VCSELs, coherently injection-locked to a leader laser, operate at gigahertz data rates with a 7T-phase-shift voltage on the 10-millivolt level. Optical nonlinearity is incorporated into the ONN with no added energy cost using coherent detection of optical interference between VCSELs.

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MASSACHUSETTS INSTITUTE OF TECHNOLOGY77 MASSACHUSETTS AVENUE CAMBRIDGE MA 02139

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Chen, Zaijun Los Angeles, US 1 0
ENGLUND, Dirk Robert Brookline, US 58 799
HAMERLY, Ryan Cambridge, US 8 14

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