An Open-Source <i>NanoController v2</i> Featuring Microcoded Instruction Set Redefinition in 22-nm FDSOI-CMOS for Autonomous Ultralow-Power SoCs

The realization of autonomous, wearable, and implantable system-on-chip (SoC) for health monitoring applications poses several challenges, such as achieving ultralow size, cost, and power consumption, yet offering sufficient flexibility to reprogram and adapt the autonomously operating SoC during the course of treatment. Commonly, programmability is not considered for ultralow-power (ULP) biomedical SoCs, since a dedicated finite state machine (FSM) fixes the operation sequence, and instruction memory presents significant contributions to silicon area and power consumption. Based on a previously published tiny, programmable microarchitecture, this work proposes the strongly enhanced <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">NanoController v2</i>, for potential use in ultralow-power biomedical SoCs, and integrates it as a prototype chip in a 22-nm FDSOI-CMOS technology. By implementing a novel microcoded control unit and an automated design space exploration framework, which are made available open-source, the instruction set can be freely redefined to exploit application-specific properties. The benefits are increased code compaction, performance gain, and, consequently, decreased power consumption. In an extensive measurement campaign, a glucose sensor control application achieves 13.1% higher performance and 15.6% less code size in the best case, resulting in an extremely low power consumption of 660 nW (9% less than the reference), <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">only by a different instruction set</i> without hardware changes. Compared with other state-of-the-art small programmable microcontrollers, between 38% and 82% smaller code size and between 33% and 77% smaller silicon area and averaged power consumption could be shown. Based on the prototype results, a fully integrated glucose sensor chip will be evaluated in currently ongoing work.