Abstract:
This paper presents a heterogeneous TinyML SoC with E2p- aware system-level energy management achieving a minimum 3.5µW and 30000× peak-to-idle power ratio. The energy-ev...Show MoreMetadata
Abstract:
This paper presents a heterogeneous TinyML SoC with E2p- aware system-level energy management achieving a minimum 3.5µW and 30000× peak-to-idle power ratio. The energy-event-performance (E2P)-aware management utilizes various fully synthesizable monitors to be aware of the runtime status of heterogeneous blocks and hierarchical voltage regulation for MEP search at system level, which gains >28% energy saving compared to single block MEP. A 2-stage CIM-based event-driven wakeup scheme is also developed to reduce the always-on energy by over 87%. The presented TinyML SoC is suitable for edge AI applications with state-of-the-art low-power features. Keywords: TinyML, Power management, MEP, Event-driven.
Date of Conference: 16-20 June 2024
Date Added to IEEE Xplore: 26 August 2024
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