一种2.17μW@120fps超低功耗双模CMOS图像传感器

Ziwei Li, Han Xu, Zheyu Liu, Li Luo, Qi Wei, Fei Qiao
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引用次数: 0

摘要

为了解决视觉系统的功耗瓶颈问题,提出了一种基于感知与计算(Senputing)架构的超低功耗CMOS图像传感器(CIS)芯片。该芯片以超低功耗实现了模拟域的BNN第一层卷积。它有两种工作模式:Normal-Sensor (NS)模式和Direct- Photocurrent-Computation (DPC)模式。在MNIST分类任务上,65nm CMOS工艺下的原型测量结果表明,特征图计算功率为2.17μW,帧率为120fps,准确率为98.1%。计算效率达到11.49TOPs/W,是目前同类产品的14.8倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A 2.17μW@120fps Ultra-Low-Power Dual-Mode CMOS Image Sensor with Senputing Architecture
This paper proposes an ultra-low-power CMOS Image Sensor (CIS) chip based on sensing-with-computing (Senputing) architecture to reduce the power bottleneck of vision system. This Senputing chip achieves BNN 1st-layer convolution in analog domain with ultra-low power consumption. It has two working modes, Normal-Sensor (NS) mode and Direct- Photocurrent-Computation (DPC) mode. The prototype measurement results under 65nm CMOS process on MNIST classification task shows that the power of feature map computation is 2.17μW with 120fps frame rates and 98.1% accuracy. The computation efficiency reaches to 11.49TOPs/W, which is 14.8× higher than state-of-art works.
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