Retention State-enabled and Progress-driven Energy Management for Self-powered Nonvolatile Processors

Energy harvesting instead of battery is a better power source for wearable de vices due to many advantages such as long operation time without maintenance and comfort to users. However, harvested energy is naturally unstable and program execution will be interrupted frequently. To solve this problem, nonvolatile processor (NVP) has been proposed because it can back up volatile state before the system energy is depleted. However, this backup process also introduces non-negligible energy and area overhead. To improve the performance of NVP, retention state has been proposed recently which can enable a system to retain the volatile data to wait for power resumption instead of saving data immediately. The goal of this paper is to forward program execution as much as possible by exploiting retention state. Specifically, two objectives are achieved. The first objective is to minimize power failures of the system if there is a great probability to get power resumption during retention state. The second objective of this paper is to achieve maximum computation efficiency if it is unlikely to avoid power failure. Compared to the instant backup scheme, evaluation results report that power failure can be reduced by 81.6% and computation efficiency can be increased by 2.5x by the proposed retention state-aware energy management strategy.