SamurAI: A Versatile IoT Node With Event-Driven Wake-Up and Embedded ML Acceleration

Abstract

Increased capabilities, such as recognition and self- adaptability, are now required from Internet-of-Things (IoT) applications. While IoT node power consumption is a major con- cern for these applications, cloud-based processing is becoming unsustainable due to continuous sensor or image data transmis- sion over the wireless network. Thus, optimized ML capabilities and data transfers should be integrated into the IoT node. More- over, IoT applications are torn between sporadic data-logging and energy-hungry data processing (e.g., image classification). Thus, the versatility of the node is key in addressing this wide diversity of energy and processing needs. This article presents SamurAI, a versatile IoT node bridging 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. AR contains a 1.7-MOPS event-driven, asynchronous Wake-up Controller (WuC) with a 207-ns wake- Manuscript received 20 April 2022; revised 6 July 2022; accepted 9 August 2022. Date of publication 2 September 2022; date of current version 26 May 2023. This article was approved by Associate Editor Vivek De. This work was supported in part funded by the WAKeMeUP project, which received funding from the Electronic Components and Systems for European Leadership Joint Undertaking in collaboration with th e European Union’s H2020 Framework Programme under Grant H2020/2014-2020 and National A