Photonic chips have great potential for neural network computing due to their fast speed, low power consumption, and parallelism. We propose a quantized neural network modeling method based on microring resonators (MRR). We analyze the optical properties of the MRRs and utilize lasers with different wavelengths as inputs of the neural network. The quantization aware method is adopted to train the neural network, and the stochastic search method is utilized to determine hyperparameters of the network. We transform the network parameters and hyperparameters into MRR parameters to simulate neural network matrix multiplication operations. Finally, we used the Mixed National Institute of Standards and Technology database for testing the proposed model. For 4-, 5-, and 6-bit quantization of weight parameters, we obtain classification accuracies of 94.23%, 94.73%, and 96.11%, respectively. Thus our study demonstrates the feasibility of building a neural network inference system using a microring structure and provides a theoretical support for applying MRRs in neural networks.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.