ChatGPT at the Speed of Light: Optical Comb-Based Monolithic Photonic-Electronic Linear-Algebra Accelerators

Abstract

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.