Year
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(Peer-Reviewed) Integrated photonic convolution acceleration core for wearable devices
Baiheng Zhao 赵柏衡 ¹, Junwei Cheng 成骏伟 ¹, Bo Wu 吴波 ¹, Dingshan Gao 郜定山 ¹, Hailong Zhou 周海龙 ¹, Jianji Dong 董建绩 ¹ ²
¹ Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
中国 武汉 华中科技大学 武汉光电国家实验室
² Optics Valley Laboratory, Wuhan 430074, China
中国 武汉 湖北光谷实验室
Opto-Electronic Science, 2023-11-28
Abstract

With the advancement of deep learning and neural networks, the computational demands for applications in wearable devices have grown exponentially. However, wearable devices also have strict requirements for long battery life, low power consumption, and compact size.

In this work, we propose a scalable optoelectronic computing system based on an integrated optical convolution acceleration core. This system enables high-precision computation at the speed of light, achieving 7-bit accuracy while maintaining extremely low power consumption. It also demonstrates peak throughput of 3.2 TOPS (tera operations per second) in parallel processing.

We have successfully demonstrated image convolution and the typical application of an interactive first-person perspective gesture recognition application based on depth information. The system achieves a comparable recognition accuracy to traditional electronic computation in all blind tests.
Integrated photonic convolution acceleration core for wearable devices_1
Integrated photonic convolution acceleration core for wearable devices_2
Integrated photonic convolution acceleration core for wearable devices_3
Integrated photonic convolution acceleration core for wearable devices_4
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