||In the past few years, due to the rapid advance in technology and the aid of 3D graphics applications the world of 3D graphics is rapidly expanding from desktop computers and dedicated gaming consoled to handheld devices, such as cellular phones, PDAs, laptops etc.,. However, unlike traditional desktop computers and gaming consoles, mobile computing devices typically have slower processors that have less capability for handling large computation-intensive workloads like 3D graphics application. In addition, the power consumption is one of the major design specifications to realize the 3D graphics accelerating engine for mobile devices because handheld batteries have limited lifetimes. Moreover, the size of chip is depend on the Moore’s Law: The number of transistors in a chip are double in every eighteen months. Even though the produce cost is decrease, but the capacity of battery cannot increase like the transistors. Therefore, how to reduce power consumption by using efficient power management techniques has become a very important research topic in 3D graphics SoC design.|
For 3D graphics applications, dynamic voltage and frequency scaling (DVFS) is a good candidate to reduce the power consumption of 3D graphics accelerating engine. So many relative papers have researched in how to accurately predict the workload and scale the voltage and frequency. The prediction policy can divide into History-based predictor  and Frame-structure predictor [2-4]. The History-based predictor predicts the latter frame workload by previous frame workload to scale the voltage, and the frame-structure predictor performs offline and then determine the different kind of frame for an application. A table is used to save the mapping of different kind of frame to the voltage, and then the voltage is scaled according to the mapping table. A lot of researchers put the power management policy in software i.e. processors, but our proposed workload prediction scheme has been realized into the hardware circuit. Therefore, it can not only reduce the overhead of processor but also quickly adjust the voltage and frequency of 3D graphics accelerating engine. Our prediction policy is one of the History-based predictor ,and it is an adaptive PID predictor [5-6] in which the parameters of Proportional controller and Integral controller can be adaptively adjusted so that it can obtain more accurate prediction results than non-adaptive predictor.
In general, the workload that the selected voltage can handle is usually over than the predicted workload. That is, actual workload is usually less than predicted workload. So that the slack time will be generated. We can utilize the slack time through Inter-frame compensation [7-10] to save more energy while maintaining the similar output quality. We use a simple policy to adaptively select the parameters for compensation between the frames to simplify the hardware architecture of the power management policy. Experimental results show that, we can get more energy saving and more accurate workload prediction when the adaptive PI predictor and adaptive Inter-frame compensation are utilized.