E2CDA: Type I: Collaborative Research: Energy Efficient Computing with Chip-Based Photonics

E2CDA：类型 I：协作研究：基于芯片的光子学的节能计算

• 批准号: 1640227
• 负责人: Yeshaiahu Fainman
• 金额: $ 41.17万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1640227&HistoricalAwards=false
• 关键词: E2CDA; Type; Collaborative; Research; Energy

Amidst today's data explosion, demand for computing power is accelerating, and the energy requirements for solving critical problems in science, engineering, business, and intelligent processing are increasing dramatically. In order to address this critical issue, the scientific and engineering community is beginning to explore new approaches to computing, such as mimicking the brain's structure or the dynamical behavior of coupled particles. However, implementing these approaches with conventional computer architectures is highly inefficient from both energy and computing standpoints. As a result, there is a pressing need to develop revolutionary computer architectures that overcome these severe roadblocks. An ambitious program is to be pursued within the framework of this project in which light, rather than electrons, is used to realize new computing paradigms with superior energy scalability. Specifically, computing architectures will be explored that exploit the wave nature of light (i.e., its amplitude and phase) harnessing the remarkable advancements over the past decade in nanofabrication of complex photonic chips with thousands of high-performance devices. These photonic platforms would have the potential to be computationally powerful, operate with unparalleled energy efficiency, and are scalable and highly reconfigurable.To fulfill this vision of energy efficient photonic computing, the proposed research efforts will focus on the following two types of photonic processors: (1) Ising Machine and (2) Neuromorphic Computing Machine. The unifying aspect of these photonic processors is that they consist of dynamic networks of coupled photonic units and rely on the wave nature of light to solve problems which has no analogy in electron-based computing systems. Beyond developing new types of optical processors, photonics technology will be developed as the cornerstone of future computer systems. A novel architecture will be explored that integrates photonic processors and interconnects with electronic memory and processors to maximize the benefits of each technology. Research will also be undertaken to map complete, challenging problems to combinations of photonic accelerators and electronic processors, and to determine how to best scale them to maximize full-system performance. By innovating at all levels of the system - from devices to architectures including systems, compilers, and algorithms - the project would aim to achieve advances that cannot be realized within any single field.

在当今的数据爆炸中，对计算能力的需求正在加速，解决科学、工程、商业和智能处理中的关键问题的能源需求正在急剧增加。 为了解决这个关键问题，科学和工程界开始探索新的计算方法，例如模仿大脑的结构或耦合粒子的动态行为。 然而，从能源和计算的角度来看，使用传统计算机架构实现这些方法的效率非常低。因此，迫切需要开发革命性的计算机架构来克服这些严重的障碍。该项目的框架内将实施一项雄心勃勃的计划，其中使用光而不是电子来实现具有卓越能量可扩展性的新计算范例。具体来说，将探索利用光的波动性质（即其振幅和相位）的计算架构，利用过去十年在复杂光子芯片纳米制造和数千个高性能设备方面取得的显着进步。这些光子平台将具有计算能力强大、以无与伦比的能源效率运行、可扩展和高度可重构的潜力。为了实现节能光子计算的愿景，拟议的研究工作将集中在以下两种类型的光子处理器上：（1）伊辛机和（2）神经形态计算机。 这些光子处理器的统一之处在于，它们由耦合光子单元的动态网络组成，并依靠光的波动性质来解决基于电子的计算系统中无法类比的问题。除了开发新型光学处理器之外，光子技术还将被开发为未来计算机系统的基石。 将探索一种新颖的架构，该架构集成光子处理器并与电子存储器和处理器互连，以最大限度地发挥每种技术的优势。还将进行研究，将完整的、具有挑战性的问题映射到光子加速器和电子处理器的组合，并确定如何最好地扩展它们以最大化整个系统的性能。 通过在系统的各个层面进行创新——从设备到架构，包括系统、编译器和算法——该项目的目标是实现任何单一领域无法实现的进步。

项目成果

Impact of Fundamental Temperature Fluctuations on the Frequency Stability of Metallo- Dielectric Nanolasers

• DOI: 10.1109/jqe.2019.2936592
• 发表时间: 2019-10
• 期刊: IEEE Journal of Quantum Electronics
• 影响因子: 2.5
• 作者: Sizhu Jiang;S. H. Pan;Suruj S. Deka;Cheng-Yi Fang;Zijun Chen;Y. Fainman;A. El Amili

Silicon photonic chip for 16-channel wavelength division (de-)multiplexing in the O-band

• DOI: 10.1364/oe.397141
• 发表时间: 2020-08-03
• 期刊: OPTICS EXPRESS
• 影响因子: 3.8
• 作者: Davis, Jordan A.;Li, Ang;Fainman, Yeshaiahu
• 通讯作者: Fainman, Yeshaiahu

Intensity noise and bandwidth analysis of nanolasers via optical injection

通过光注入进行纳米激光器的强度噪声和带宽分析

• DOI: 10.1364/oe.27.008186
• 发表时间: 2019
• 期刊: Optics Express
• 影响因子: 3.8
• 作者: Chen, Zijun;Deka, Suruj S.;Pan, Si Hui;Jiang, Sizhu;Fang, Cheng-Yi;Fainman, Yeshaiahu;Amili, Abdelkrim El
• 通讯作者: Amili, Abdelkrim El

Nanolasers: Second-order intensity correlation, direct modulation and electromagnetic isolation in array architectures

• DOI: 10.1016/j.pquantelec.2018.05.001
• 发表时间: 2018-05
• 期刊: Progress in Quantum Electronics
• 影响因子: 11.7
• 作者: S. H. Pan;Suruj S. Deka;A. E. Amili;Q. Gu;Y. Fainman

Programmable plasmonic phase modulation of free-space wavefronts at gigahertz rates

• DOI: 10.1038/s41566-019-0360-3
• 发表时间: 2019-06
• 期刊: Nature Photonics
• 影响因子: 35
• 作者: A. Smolyaninov;A. El Amili;F. Vallini;S. Pappert;Y. Fainman