Jin Park, Eun-ji Choi, Kyu-Bae Lee, Jae-Jin Lee, Kyuseung Han, Woojoo Lee
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Developing an Ultra-low Power RISC-V Processor for Anomaly Detection
This paper aims to develop an ultra-low power processor for wearable devices for anomaly detection. To this end, this paper proposes a processor architecture that divides the architecture into a part for general applications running on wearable devices (day part) and a part that performs anomaly detection by analyzing sensor data (night parts), and each part operates completely independently. This day-night architecture allows the day part, which contains the power-hungry main-CPU and system interconnect, to be turned off most of the time except for intermittent work, and the night part, which consists only of the sub-CPU and minimal IPs, can run all the time with low power. By developing a processor based on the proposed processor architecture, the design verification of the proposed technology and the superiority of power saving are demonstrated.