Self-tuning for maximized lifetime energy-efficiency in the presence of circuit aging

This paper presents an integrated framework, together with control policies, for optimizing dynamic control of self-tuning parameters of a digital system over its lifetime in the presence of circuit aging. A variety of self-tuning parameters such as supply voltage, operating clock frequency, and dynamic cooling are considered, and jointly optimized using efficient algorithms described in this paper. Our optimized self-tuning approach satisfies performance constraints at all times, and maximizes a lifetime computational power efficiency (LCPE) metric, which is defined as the total number of clock cycles achieved over lifetime divided by the total energy consumed over lifetime. We present three control policies: 1) progressive-worst-case-aging (PWCA), which assumes worst-case aging at all times; 2) progressive-on-state- aging (POSA), which estimates aging by tracking active/sleep modes, and then assumes worst-case aging in active mode and long recovery effects in sleep mode; and 3) progressive-real-time-aging-assisted (PRTA), which acquires real-time information and initiates optimized control actions. Various flavors of these control policies for systems with dynamic voltage and frequency scaling (DVFS) are also analyzed. Simulation results on benchmark circuits, using aging models validated by 45 nm measurements, demonstrate the effectiveness and practicality of our approach in significantly improving LCPE and/or lifetime compared to traditional one-time worst-case guardbanding. We also derive system design guidelines to maximize self-tuning benefits.