Two-dimensional photonic neural network convolutional acceleration chip based on series connection structure

Abstract

The present invention discloses a two-dimensional photonic neural network convolutional acceleration chip based on series connection structure, which is integrated with a modulator, M microring delay weighting units, M−1 secondary delay waveguide, a wavelength-division multiplexer and a photodetector. Based on microring resonator arrays in M microring delay weighting units, the weighting of any convolution kernel matrix coefficient of the signal to be convolved is realized by the present invention, the refresh speed is fast, and real-time feedback training can be realized to extract the optimal convolution kernel matrix; in the present invention, realizing the primary wavelength-time interleaving of the sub weighted modulated signals with different wavelengths through the cascaded integrated waveguide between the microring resonators, realizing the secondary wavelength-time interleaving of sub-weighted modulated signals of different wavelengths by connecting the microring delay weighting units in series through the secondary delay waveguide, which can realize the delay multiplexing of the delay waveguide, comparing to parallel connection structure, it reduces the signal transmission loss caused by the delay waveguide while reducing the chip size, thereby improving the energy utilization efficiency of the chip.