Low-power scalable multilayer optoelectronic neural networks enabled with incoherent light.

ABSTRACT: Optical approaches have made great strides towards the goal of high-speed, energy-efficient computing necessary for modern deep learning and AI applications. Read-in and read-out of data, however, limit the overall performance of existing approaches. This study introduces a multilayer optoelectronic computing framework that alternates between optical and optoelectronic layers to implement matrix-vector multiplications and rectified linear functions, respectively. Our framework is designed for real-time, parallelized operations, leveraging 2D arrays of LEDs and photodetectors connected via independent analog electronics. We experimentally demonstrate this approach using a system with a three-layer network with two hidden layers and operate it to recognize images from the MNIST database with

SUBMITTER: Song A 

PROVIDER: S-EPMC11655539 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature