SamurAI: A 1.7MOPS-36GOPS Adaptive Versatile IoT Node with 15,000× Peak-to-Idle Power Reduction, 207ns Wake-Up Time and 1.3TOPS/W ML Efficiency
SamurAI: A 1.7MOPS-36GOPS Adaptive Versatile IoT Node with 15,000× Peak-to-Idle Power Reduction, 207ns Wake-Up Time and 1.3TOPS/W ML Efficiency
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SamurAI：1.7MOPS-36GOPS 自适应多功能物联网节点，具有 15,000× 峰值至空闲功耗降低、207ns 唤醒时间和 1.3TOPS/W ML 效率
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
F. Clermidy
中科院分区：
文献类型：
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作者：
I. Panades;Benoît Tain;J. Christmann;David Coriat;R. Lemaire;C. Jany;B. Martineau;F. Chaix;A. Quelen;Emmanuel Pluchart;J. Noel;R. Boumchedda;A. Makosiej;Maxime Montoya;Simone Bacles;David Briand;Jean;A. Valentian;Frédéric Heitzmann;E. Beigné;F. Clermidy
物联网节点应用要求在零星的数据遗传和渴望能量的数据处理之间被撕裂（例如，图像分类）。 ，无钟，事件驱动的始终响应（AR）零件和能源有效的按需（OD）部分。 （WUC）使用207NS的唤醒时间优化用于短散发器的计算。在峰值到峰值功耗的兴趣中，在应用程序分类方案中，每天的平均功率可以证明15,000×降低。
IoT node application requirements are torn between sporadic data-logging and energy-hungry data processing (e.g. image classification). This paper presents a versatile IoT node covering this gap in processing and energy by leveraging two on-chip sub-systems: a low power, clock-less, event-driven Always-Responsive (AR) part and an energy-efficient On-Demand (OD) part. The AR contains a 1.7MOPS event-driven, asynchronous Wake-up Controller (WuC) with 207ns wake-up time optimized for short sporadic computing. OD combines a deep-sleep RISC-V CPU and 1.3TOPS/W Machine Learning (ML) and crypto accelerators for more complex tasks. The node can perform up to 36GOPS while achieving 15,000× reduction from peak-to-idle power consumption. The interest of this versatile architecture is demonstrated with 105μW daily average power on an applicative classification scenario.