Iterative photonic processor for fast complexvalued matrix inversion
Iterative photonic processor for fast complexvalued matrix inversion作者机构:Department of EngineeringCentre for Photonic SystemsElectrical Engineering DivisionUniversity of CambridgeCambridge CB30FAUK Huawei Technologies(Sweden)AB16440 KistaSweden
出 版 物:《Photonics Research》 (光子学研究(英文版))
年 卷 期:2022年第10卷第11期
页 面:2488-2501页
核心收录:
学科分类:070207[理学-光学] 07[理学] 08[工学] 0803[工学-光学工程] 081201[工学-计算机系统结构] 0702[理学-物理学] 0812[工学-计算机科学与技术(可授工学、理学学位)]
基 金:Huawei Technologies(Sweden)AB(G107576)
摘 要:An N×N iterative photonic processor is proposed for the first time, we believe, for fast computation of complexvalued matrix inversion, a fundamental but computationally expensive linear algebra operation. Compared to traditional digital electronic processing, optical signal processing has a few unparalleled features that could enable higher representational efficiency and faster computing speed. The proposed processor is based on photonic integration platforms–the inclusion of Ⅲ-V gain blocks offers net neutral loss in the phase-sensitive loops. This is essential for the Richardson iteration method that is adopted in this paper for complex linear systems. Wavelength multiplexing can be used to significantly improve the processing efficiency, allowing the computation of multiple columns of the inverse matrix using a single processor core. Performances of the key building blocks are modeled and simulated, followed by a system-level analysis, which serves as a guideline for designing an N×N Richardson iteration processor. An inversion accuracy of98%can be predicted for a 64×64 photonic processor with a80times faster inversion rate than electronic processors. Including the power consumed by both active components and electronic circuits, the power efficiency of the proposed processor is estimated to be over an order of magnitude more energy-efficient than electronic processors. The proposed iterative photonic integrated processor provides a promising solution for future optical signal processing systems.