A 1.8mW Perception Chip with Near-Sensor Processing Scheme for Low-Power AIoT Applications

Zheyu Liu, Erxiang Ren, Li Luo, Qi Wei, Xing Wu, Xueqing Li, F. Qiao, Xinjun Liu, Huazhong Yang
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引用次数: 7

Abstract

In the past few years, the demand for intelligence of IoT front-end devices has dramatically increased. However, such devices face challenges of limited on-chip resources and strict power or energy constraints. Recent progress in binarized neural networks has provided promising solutions for front-end processing system to conduct simple detection and classification tasks by making trade-offs between the processing quality and the computation complexity. In this paper, we propose a mixed-signal perception chip, in which an ADC-free 32x32 image sensor and a BNN processing array are directly integrated with a 180nm standard CMOS process. Taking advantage of the ADC-free processing architecture, the whole processing system only consumes 1.8mW power, while providing up to 545.4 GOPS/W energy efficiency. The implementation performance and energy efficiency are comparable with the state-of-the-art designs in much more advanced CMOS technologies. This work provides a promising alternative for low-power IoT intelligent applications.
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基于近传感器处理方案的1.8mW低功耗AIoT感知芯片
在过去的几年里,对物联网前端设备的智能化需求急剧增加。然而,这种设备面临着有限的片上资源和严格的功率或能量限制的挑战。二值化神经网络的最新进展为前端处理系统通过权衡处理质量和计算复杂度来完成简单的检测和分类任务提供了有希望的解决方案。在本文中,我们提出了一种混合信号感知芯片,该芯片将无adc的32 × 32图像传感器和BNN处理阵列直接集成到180nm标准CMOS工艺中。利用无adc的处理架构,整个处理系统仅消耗1.8mW功率,同时提供高达545.4 GOPS/W的能效。实现性能和能源效率可与更先进的CMOS技术中最先进的设计相媲美。这项工作为低功耗物联网智能应用提供了一个有希望的替代方案。
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