Open AccessProgrammable matrix operation with reconfigurable time-wavelength plane manipulation and dispersed time delay
Author(s) -
Yuyao Huang,
Wenjia Zhang,
Fan Yang,
Jiangbing Du,
Zuyuan He
Publication year - 2019
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.27.020456
Subject(s) - computer science , matrix multiplication , convolution (computer science) , optical computing , time domain , multiplication (music) , optics , matrix (chemical analysis) , autocorrelation , algorithm , artificial neural network , physics , mathematics , artificial intelligence , materials science , quantum mechanics , computer vision , acoustics , composite material , quantum , statistics
We propose a novel optical computing architecture for massive parallel matrix manipulation based on reconfigurable time-wavelength plane manipulation and and dispersed time delay. Two linear weighting methods in either wavelength or time domain are proposed and validated. We perform the autocorrelation function of a 7-bit m-sequence with the speed at 1.18×10 11 multiplications and accumulations per second (MACs/s) and a multiplication of a 4 × 4 matrix and a 4 × 1 vector at 2.69×10 9 MACs/s. The edge extraction of 32 × 32 binary images is also realized in simulation by optical 2D convolution at 5×10 8 MACs/s. The proposed optical computing unit can be a key building block to process complex computing tasks with advanced deep learning algorithms and it is promising for the future photonic neural network circuits.