Abstract:Focusing on dynamic power consumption of the chip,this paper proposed a new energy-saving strategy named BP-DVFS.Currently,DVFS (dynamic voltage and frequency scaling) technology failed to predict future behavior of CPU.In order to improve the performance of CPU utilization and predict more accurate CPU dynamic frequency,it is essential to reduce its operating power consumption.A CPU model named FPU-CPU (forward predict utilization) was built in strategy.A non-linear relationship between the CPU utilization in next period and the CPU running resource was assumed in the model.Five events related to CPU resources and extracted from run-time processor environment were measured as features.Afterwards,the training phase of was performed by the BP (back propagation) neural network.Various experiments were then carried out to predict different kinds of tasks including CPU utilization,processing and power consumption through BP neural network.To evaluate the performance of proposed method,the experimental results under same situation were compared with three traditional CPU frequency modulation strategies.The experimental results showed that the CPU power consumption of BP-DVFS based strategy is lower than that of other three strategies when CPU handles different kinds of program tasks.The experimental verification indicated that the proposed technique wasnot only accurate inpredicting performance of CPU utilization,but also helpful to reduce power consumption of CPU.