Title page for etd-0728111-174057


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URN etd-0728111-174057
Author Bao-chen Ke
Author's Email Address No Public.
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Department Computer Science and Engineering
Year 2010
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title Hybrid Fuzzy Kalman Filter for Workload Prediction of 3D Graphic System
Date of Defense 2011-07-26
Page Count 86
Keyword
  • Workload Prediction
  • 3D Graphic System
  • Fuzzy Controller
  • Power Management
  • Dynamic Voltage Frequency Scaling(DVFS)
  • Kalman Filter
  • Abstract 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.
    Advisory Committee
  • Sheng-Fu Siao - chair
  • Yun-Nab chang - co-chair
  • Ke-Chi Kuo - co-chair
  • Ming-Chih Chen - co-chair
  • Sian-Rong Kuang - advisor
  • Files
  • etd-0728111-174057.pdf
  • Indicate in-campus at 5 year and off-campus access at 5 year.
    Date of Submission 2011-07-28

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