Hybrid Fuzzy Kalman Filter for Workload Prediction of 3D Graphic System

• Main Authors: Bao-chen Ke, 柯保辰
• Other Authors: Sian-Rong Kuang
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/59599747840945483346

碩士 === 國立中山大學 === 資訊工程學系研究所 === 99 === In modern life, 3D graphics system is widely applied to portable product like Notebook, PDA and smart phone. Unlike desktop system, the capacity of batteries of these embedded systems is finite. Furthermore, rapid improvement of IC process leads to quick growth in the transistor count of a chip. According to above-mentioned reason and the complex computation of 3D graphics system, the power consumption will be very large. To efficiently lengthen the lifetime of battery, power management is an indispensable technique. Dynamic voltage and frequency scaling (DVFS) is one of the popular power management policy. In the scheme of DVFS, an accurate workload predictor is needed to predict the workload of every frame. According to these predictions a specific voltage and frequency level is applied to each frame of the 3D graphics system. The number of the voltage/frequency levels and the voltage/frequency of each level are fixed, the voltage/frequency table is decided according to the application of power management. Whenever the workload predictor completes the workload prediction of next frame, the voltage/frequency level of next frame will be found by looking up the voltage/frequency table. In this thesis, we propose a power management scheme with a framework composed of mainly Kalman filter and an auxiliary fuzzy controller to predict the workload of next frame. This scheme amends the shortcomings of traditional Kalman filter that needs to know the system features beforehand. And we propose a brand new concept named ”delayed display” to massively reduce the miss rate of prediction without changing the framework of predictor.