Suppr超能文献

用于应急硅集成光学计算的材料。

Materials for emergent silicon-integrated optical computing.

作者信息

Demkov Alexander A, Bajaj Chandrajit, Ekerdt John G, Palmstrøm Chris J, Ben Yoo S J

机构信息

Department of Physics, The University of Texas, Austin, Texas 78712, USA.

Department of Computer Science, The University of Texas, Austin, Texas 78712, USA.

出版信息

J Appl Phys. 2021 Aug 21;130(7):070907. doi: 10.1063/5.0056441. Epub 2021 Aug 19.

Abstract

Progress in computing architectures is approaching a paradigm shift: traditional computing based on digital complementary metal-oxide semiconductor technology is nearing physical limits in terms of miniaturization, speed, and, especially, power consumption. Consequently, alternative approaches are under investigation. One of the most promising is based on a "brain-like" or scheme. Another approach is quantum computing using photons. Both of these approaches can be realized using silicon photonics, and at the heart of both technologies is an efficient, ultra-low power broad band optical modulator. As silicon modulators suffer from relatively high power consumption, materials other than silicon itself have to be considered for the modulator. In this Perspective, we present our view on such materials. We focus on oxides showing a strong linear electro-optic effect that can also be integrated with Si, thus capitalizing on new materials to enable the devices and circuit architectures that exploit shifting computational machine learning paradigms, while leveraging current manufacturing infrastructure. This is expected to result in a new generation of computers that consume less power and possess a larger bandwidth.

摘要

计算架构的进展正接近一种范式转变

基于数字互补金属氧化物半导体技术的传统计算在小型化、速度,尤其是功耗方面正接近物理极限。因此,正在研究替代方法。最有前景的方法之一是基于“类脑”或 方案。另一种方法是使用光子的量子计算。这两种方法都可以通过硅光子学实现,并且这两种技术的核心都是高效、超低功耗的宽带光调制器。由于硅调制器存在相对较高的功耗,因此必须考虑使用硅本身以外的材料来制造调制器。在这篇观点文章中,我们阐述了对这类材料的看法。我们关注那些具有强线性电光效应且能与硅集成的氧化物,从而利用新材料来实现利用不断变化的计算机器学习范式的器件和电路架构,同时借助现有的制造基础设施。这有望带来新一代功耗更低、带宽更大的计算机。

相似文献

1
Materials for emergent silicon-integrated optical computing.用于应急硅集成光学计算的材料。
J Appl Phys. 2021 Aug 21;130(7):070907. doi: 10.1063/5.0056441. Epub 2021 Aug 19.
3
Integrated silicon photonic MEMS.集成硅光子微机电系统
Microsyst Nanoeng. 2023 Mar 20;9:27. doi: 10.1038/s41378-023-00498-z. eCollection 2023.

本文引用的文献

2
3
Quantum computational advantage using photons.利用光子实现量子计算优势。
Science. 2020 Dec 18;370(6523):1460-1463. doi: 10.1126/science.abe8770. Epub 2020 Dec 3.
5
An integrated optical modulator operating at cryogenic temperatures.一种在低温下工作的集成光学调制器。
Nat Mater. 2020 Nov;19(11):1164-1168. doi: 10.1038/s41563-020-0725-5. Epub 2020 Jul 6.
8
Recent advances in physical reservoir computing: A review.近期物理存储计算的进展:综述。
Neural Netw. 2019 Jul;115:100-123. doi: 10.1016/j.neunet.2019.03.005. Epub 2019 Mar 20.
9
In-memory computing on a photonic platform.光子平台上的内存计算。
Sci Adv. 2019 Feb 15;5(2):eaau5759. doi: 10.1126/sciadv.aau5759. eCollection 2019 Feb.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验