Photonic network-on-chip architectures using multilayer deposited silicon materials for high-performance chip multiprocessors

Author:

Biberman Aleksandr1,Preston Kyle2,Hendry Gilbert1,Sherwood-Droz Nicolás2,Chan Johnnie1,Levy Jacob S.2,Lipson Michal2,Bergman Keren1

Affiliation:

1. Columbia University, New York, NY

2. Cornell University, Ithaca, NY

Abstract

Integrated photonics has been slated as a revolutionary technology with the potential to mitigate the many challenges associated with on- and off-chip electrical interconnection networks. To date, all proposed chip-scale photonic interconnects have been based on the crystalline silicon platform for CMOS-compatible fabrication. However, maintaining CMOS compatibility does not preclude the use of other CMOS-compatible silicon materials such as silicon nitride and polycrystalline silicon. In this work, we investigate utilizing devices based on these deposited materials to design photonic networks with multiple layers of photonic devices. We apply rigorous device optimization and insertion loss analysis on various network architectures, demonstrating that multilayer photonic networks can exhibit dramatically lower total insertion loss, enabling unprecedented bandwidth scalability. We show that significant improvements in waveguide propagation and waveguide crossing insertion losses resulting from using these materials enables the realization of topologies that were previously not feasible using only the single-layer crystalline silicon approaches.

Funder

Air Force Office of Scientific Research

Semiconductor Research Corporation

Division of Electrical, Communications and Cyber Systems

National Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Electrical and Electronic Engineering,Hardware and Architecture,Software

Cited by 76 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Silicon Photonic Multi-DNN Accelerator;2023 32nd International Conference on Parallel Architectures and Compilation Techniques (PACT);2023-10-21

2. Photonic NoCs for Energy-Efficient Data-Centric Computing;Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing;2023-10-01

3. Universal wavelength reuse mechanism for optical networks-on-chip based on a cooperative game;Journal of Optical Communications and Networking;2023-05-19

4. Polycrystalline silicon PhC cavities for CMOS on-chip integration;Scientific Reports;2022-10-12

5. Ascend: A Scalable and Energy-Efficient Deep Neural Network Accelerator With Photonic Interconnects;IEEE Transactions on Circuits and Systems I: Regular Papers;2022-07

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3