Current Status and Future Optimization of Low-Power Design in Digital Circuits

The advantages of low power consumption are evident: significantly re ducing system operational costs and facilitating startup conditions. Lowpower design provides a perpetual development goal for circuits, driving continuous efforts to minimize power consumption. This study systematically analyzes the current status and future optimization pathways of low-power design techniques for digital circuits, focusing on two core directions: circuit simplification and hardware innovation. Through literature review and tool experiments (such as Boolean logic optimization using SymPy and Karnaugh map simplification with Logic Friday), the research quantitatively evaluates the effects of multi-level optimization: at the hardware level, employing partitioned multi-supply multi-voltage (MSMV) domains and dynamic voltage and frequency scaling (DVFS) can achieve 30%-50% power reduction, while novel materials (e.g., carbon nanotube transistors) can suppress static power consumption to 0.05pA. The findings indicate that future advancements require integrating AI-driven automation toolchains (such as Q-learning for logic expression optimization) with cross-layer co-design approaches (including in-memory computing and neuromorphic architectures) to break through the energy wall limitation. Software tools need to enhance multi-output cooperative optimization capabilities, while hardware innovation should rely on the convergence of AI and materials engineering, ultimately achieving full lifecycle energy efficiency optimization.