Large-Scale Integrated Photonics for Energy-Efficient AI Hardware

被引：0

作者：

Tossoun, Bassem ^{[1
]}

Liang, Di ^{[1
]}

Xiao, Xian ^{[1
]}

Cheung, Stanley ^{[2
]}

Singaraju, Prerana ^{[1
]}

Srinivasan, Sudharsanan ^{[1
]}

Descos, Antoine ^{[1
]}

Hu, Yingtao ^{[1
]}

Baek, Jongseo ^{[1
]}

London, Yanir ^{[2
]}

Yuan, Yuan ^{[2
]}

Peng, Yiwei ^{[2
]}

Van Vaerenbergh, Thomas ^{[3
]}

Kurzveil, Geza ^{[1
]}

Fiorentino, Marco ^{[2
]}

Beausoleil, Raymond G. ^{[2
]}

机构：

[1] Hewlett Packard Labs, Hewlett Packard Enterprise, Santa Barbara, CA 93106 USA

[2] Hewlett Packard Labs, Hewlett Packard Enterprise, Milpitas, CA USA

[3] Hewlett Packard Labs, Hewlett Packard Enterprise, Brussels, Belgium

来源：

2024 IEEE PHOTONICS SOCIETY SUMMER TOPICALS MEETING SERIES, SUM 2024 | 2024年

关键词：

photonic computing; silicon photonics; neuromorphic computing;

D O I：

10.1109/SUM60964.2024.10614557

中图分类号：

学科分类号：

摘要：

The convergence of deep learning models and the availability of large datasets has spurred significant interest in developing new hardware that can run AI algorithms more energy-efficiently. At Hewlett Packard Labs, we've developed an energy-efficient silicon photonics platform, a foundational technology for next-generation AI hardware.

引用

页数：2

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