2023/11/19 by Tzu-Chien Hsueh, Yeshaiahu Fainman, Hsueh, Tzu-Chien +3
Computer Science · Engineering · #Emerging Technologies (cs.ET) #FOS: Computer and information sciences #FOS: Electrical engineering #Neural Networks and Reservoir Computing #Optical Network Technologies #Photonic and Optical Devices #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2311.11224
openalex publication_date 2023/11/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper proposes to adopt advanced monolithic silicon-photonics integrated-circuits manufacturing capabilities to achieve a system-on-chip photonic-electronic linear-algebra accelerator with the features of optical comb-based broadband incoherent photo-detections and high-dimensional operations of consecutive matrix-matrix multiplications to enable substantial leaps in computation density and energy efficiency, with practical considerations of power/area overhead due to photonic-electronic on-chip conversions, integrations, and calibrations through holistic co-design approaches to support attention-head mechanism based deep-learning neural networks used in Large Language Models and other emergent applications.