⚡ 本页包含 AI 生成的分析内容，仅供参考
本文介绍了STM32N6微控制器，采用16nm FinFET工艺，集成Neural-ART神经网络处理单元，实现高效边缘AI推理。该芯片面向物联网、可穿戴、工业自动化和智能家居等场景，解决了边缘设备对实时、低功耗AI处理的需求，同时减少延迟和云依赖。
Abstract The STM32N6 microcontroller meets the growing need for intelligent edge devices in IoT, wearables, industrial automation, and smart home systems supporting real-time, energyefficient AI processing at the edge, reducing latency and enhancing data privacy by limiting cloud reliance. At its core, the Neural-ART neural processing unit delivers complex and power efficient AI inference. This paper examines the chip’s 16nm FinFET design, performance, computational power and energy efficiency The STM32N6 microcontroller addresses the increasing demand for intelligent edge devices in IoT, wearable technology, industrial automation, and smart-home systems. It enables real-time, energy-efficient AI processing at the edge, reducing latency and enhancing data privacy by minimizing cloud dependency. At its core is the Neural-ART neural processing unit (NPU), a dedicated accelerator that supports complex AI inference with minimal power
G. Desoli1, J-F. Agaësse2, N. Chawla3, E. Hilkens2, T. Boesch4, V. Taufour2, M. Ayodhyawasi3, P. Ravenhill2, S. Pal-Singh3, M. Soulie2
STMicroelectronics, Cornaredo, Italy, 2STMicroelectronics, Grenoble, France, 3STMicroelectronics, Greater Noida, India, 4STMicroelectronics, Geneva, Switzerland