计算机科学
可扩展性
人工神经网络
光子学
能源消耗
布线(电子设计自动化)
光学计算
炸薯条
计算机体系结构
信号处理
人工智能
细胞神经网络
计算机工程
图像处理
计算科学
大数据
编码(内存)
计算机硬件
图形处理单元
深度学习
并行处理
电子工程
能量(信号处理)
嵌入式系统
芯片上的网络
高效能源利用
数据处理
作者
Zhang Feng,Kejian Zhu,Tuo Li,Changhong Wang,Xiaofeng Zou,Yanan Du,Yu Bi,Ruiting Wang,Xin Xi,Pengfei Sun
摘要
In the era of big data, the amount of data is increasing day by day. The existing processors based on electronic chips are confronted with the problems of limited speed and excessive energy consumption when dealing with massive data processing. Low scalability of the current high-speed photonic neural network computing chips limits its further development. This paper proposes an ultra-high-speed scalable photonic neural network computing chip and integration technology for artificial intelligence. Dividing the photonic computing chip into light source module, electro-optical conversion module, routing module, computational unit module, etc., can significantly improve the computing performance in different scenarios. The chip's digit recognition accuracy can reach 96.74% and 97.67% for tested and calculated values, respectively. The computing density is as high as 1.523 TOPS/mm2 at 40 computational units. It provides a new solution for ultra-high-speed optoelectronic information processing
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