A control-theoretic approach for energy efficient CPU-GPU subsystem in mobile platforms

This paper presents a control-theoretic approach to optimize the energy consumption of integrated CPU and GPU subsystems for graphic applications. It achieves this via a dynamic management of the CPU and GPU frequencies. To this end, we first model the interaction between the GPU and CPU as a queuing system. Second, we formulate a Multi-Input-Multi-Output state-space closed loop control to ensure robustness and stability. We evaluated this control on an Intel Baytrail-based Android platform. Experimental evaluations show energy savings of 17.4% in the CPU-GPU subsystem with a low performance impact of 0.9%.