现场可编程门阵列
强化学习
计算机科学
软件部署
推论
量化(信号处理)
门阵列
钢筋
过程(计算)
嵌入式系统
人工智能
算法
工程类
结构工程
操作系统
作者
Jiajin Wang,Guoqing Pu,Zhiwei Fang,Chao Luo,Yong Wu,Lilin Yi
标识
DOI:10.1109/acp/poem59049.2023.10368889
摘要
A real-time embedded approach to realize intelligent mode-locked fiber lasers based on reinforcement learning is proposed. The reinforcement learning is deployed in a Field programmable gate array (FPGA) to complete the inference process and real-time control. Benefited from the dedicated quantization and deployment strategy, the FPGA finishes a single forward inference in 6.4 us, which is about 32-times faster than an Nvidia RTX-3050 GPU, and the proposed solution manifests ultrahigh power efficiency.
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