Monolithically integrated asynchronous optical recurrent accelerator

Bo Wu; Haojun Zhou; Junwei Cheng; Wenkai Zhang; Shiji Zhang; Chaoran Huang; Dongmei Huang; Hailong Zhou; Jianji Dong; Xinliang Zhang

doi:10.1186/s43593-025-00084-y

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Monolithically integrated asynchronous optical recurrent accelerator

eLight Vol. 5, (2025)

Research Article | Updated：2025-07-29

- Monolithically integrated asynchronous optical recurrent accelerator
- Affiliations：
- Author bio：
  
  hhailongzhou@hust.edu.cn
  jjjdong@hust.edu.cn
  kxlzhang@mail.hust.edu.cn
- Funds：
- DOI：10.1186/s43593-025-00084-y
  CLC：
- Received：27 October 2024，
  
  Revised：17 January 2025，
  
  Accepted：04 March 2025，
  
  Published Online：06 May 2025，
  
  Published：2025-12
- Accepted：
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Bo Wu, Haojun Zhou, Junwei Cheng, et al. Monolithically integrated asynchronous optical recurrent accelerator[J]. Elight, 2025, 5.
DOI：

Bo Wu, Haojun Zhou, Junwei Cheng, et al. Monolithically integrated asynchronous optical recurrent accelerator[J]. Elight, 2025, 5. DOI： 10.1186/s43593-025-00084-y.

摘要

Abstract

Computing with light is widely recognized as a promising paradigm for overcoming the energy and latency limitations of electronic computing. However

the energy consumption and latency in current optical computing hardware predominantly arise in the electrical domain rather than the optical domain

primarily due to frequent signal conversions between optical (analog) and electrical (digital) formats. Furthermore

as the operating frequency of optical computing surpasses the GHz range

the synchronization of parallel electrical signals and the management of optical delays become increasingly critical. These challenges exacerbate energy consumption and latency

particularly in recurrent optical operations. To address these limitations

we propose a novel asynchronous computing paradigm for on-chip optical recurrent accelerators based on wavelength encoding

effectively mitigating synchronization challenges. By leveraging the intrinsic causality of wavelength relay

our approach eliminates the need for rigorous temporal alignment. To demonstrate the flexibility and efficacy of this asynchronous paradigm

we present two advanced recurrent models—an optical hidden Markov model and an optical recurrent neural network—monolithically integrated for the first time. These models incorporate hundreds of linear and nonlinear computing units densely packed into a compact footprint of just 10 mm

. Experimental evaluations on various benchmark tasks underscore the superior energy efficiency and low latency of the propose

d asynchronous optical accelerators. This innovation enables the efficient processing of large-scale parallel signals and positions optical processors as a pivotal technology for applications such as autonomous driving and intelligent robotics.

关键词

Keywords

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