Continuous Frequency Adjustment Technique Based on Dynamic Workload Prediction

Real-time embedded systems increasingly rely on dynamic power management to balance between power and performance goals. In this paper, we present a technique for continuous frequency adjustment (CFA) which enables one to adjust the frequency values of various functional blocks in the system at very low granularity so as to minimize energy while meeting a performance constraint. A key feature of the proposed technique is that the workload characteristics for functional blocks are effectively captured at runtime to generate a frequency value that is continuously adjusted, thereby eliminating the delay and energy penalties incurred by transitions between power-saving modes. The workload prediction is accomplished by solving an initial value problem (IVP). Applying CFA to a real-time system in 65 nm CMOS technology, we demonstrate the effectiveness of the proposed technique by reporting 13.6% energy saving under a performance constraint.