Laptop power tuning based on system state prediction

Performance, power consumption, and heat dissipation are the three major elements of a notebook computer, and it is necessary to comprehensively coordinate the relationship between the three in order to provide users with a laptop with good performance and experience. The traditional method is to manually determine various power parameters, which is time-consuming and labor-intensive, and may not be able to achieve optimal machine performance. In this paper, we propose using a deep learning model to automatically learn the setting of the power system parameters to improve the performance of the machine and the user experience. Specifically, the method in this paper is to predict the future states of the system based on historical actions and states. By evaluating the value of the predicted states, the optimal action is selected. Experiments show that the method proposed in this paper can learn a model to adjust the power of the system, and the performance of the laptop improves a lot without exceeding the temperature standard.