A flexible digital compute-in-memory chip for edge intelligence.

Abstract

Flexible electronics, coupled with artificial intelligence, hold the potential to revolutionize robotics, wearable and healthcare devices¹, human-machine interfaces², and other emerging applications^3,4. However, the development of flexible computing hardware that can efficiently execute neural-network-inference tasks using parallel computing remains a substantial challenge⁵. Here we present FLEXI, a thin, lightweight and robust flexible digital artificial intelligence integrated circuit to address this challenge. Our approach uses process-circuit-algorithm co-optimization and a digital dynamically reconfigurable compute-in-memory architecture. Key features include clock frequency operation of up to 12.5 MHz and power consumption as low as 2.52 mW, all while achieving subdollar-per-unit cost and an operational circuit yield of between approximately 70% and 92%. Our circuits can perform 10¹⁰ fixed and random multiplications without error, withstand over 40,000 bending cycles and maintain stable performance for a period exceeding 6 months. A one-shot on-chip neural network deployment eliminates the power consumption and latency associated with sequential weight writing, achieving up to 99.2% accuracy in temporal arrhythmia detection tasks on a single 1-kb chip. In addition, FLEXI demonstrates over 97.4% accuracy in human daily activity monitoring using multimodal physiological signals.