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.
Keywords
Cite
@article{arxiv.2311.11224,
title = {ChatGPT at the Speed of Light: Optical Comb-Based Monolithic Photonic-Electronic Linear-Algebra Accelerators},
author = {Tzu-Chien Hsueh and Yeshaiahu Fainman and Bill Lin},
journal= {arXiv preprint arXiv:2311.11224},
year = {2023}
}
Comments
17 pages, 9 figures, 2 tables, 19 equations