Graphics-intensive game applications gained significant popularity in recent years. Although most of them are available on high-end desktops, the advent of these applications on battery-powered mobile devices (e.g., laptops, PDAs, cell phones and portable game consoles) is steadily increasing. This recent development is resulting in a constantly widening gap between the demand for computational resources on portable devices and the corresponding energy resources available through batteries. In this context, power management techniques play a significant role in reducing this gap and in increasing the energy efficiency of these devices.

Most of these devices are equipped with dynamic voltage/frequency-scalable processors in which the power dissipated per clock cycle is directly proportional to its frequency and the square of the supply voltage. Therefore, one can reduce energy consumption through dynamic voltage frequency scaling (DVFS) techniques, where the processor's clock frequency is dynamically adjusted based on the predicted workload of the next frame.

The quality of the prediction highly influences the resulting performance of the system: a frequency chosen too high will waste energy whereas a frequency chosen too low will result in a frame rate drop reducing the game’s quality significantly.

We are currently investigating methods to improve the prediction accuracy and thereby reduce the energy consumption and satisfy the user's perception.