Prediction of CPU idle-busy activity pattern

  title={Prediction of CPU idle-busy activity pattern},
  author={Qian Diao and Justin J. Song},
  journal={2008 IEEE 14th International Symposium on High Performance Computer Architecture},
Real-world workloads rarely saturate multi-core processor. CPU C-states can be used to reduce power consumption during processor idle time. The key unsolved problem is: when and how to use which C-state. We propose a machine learning prediction method and usage model. We evaluate this model with idle traces collected on dual-core and quad-core processor, and find this method can well predict CPUpsilas activity pattern at the error level not exceeding 4%. Compared with existing OS C-state policy… CONTINUE READING


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Publications referenced by this paper.
Showing 1-8 of 8 references

Book Chapter: DBN MODELS FOR VISUAL TRACKING AND PREDICTION, Bayesian Network Technologies: Applications and Graphical Models, edited by Ankush Mittal, Ashraf

Qian Diao, Jianye Lu, Wei Hu, Yimin Zhang, Gary Bradski
Kassim and Tele Tan. IGI Global, • 2006
View 1 Excerpt

A dynamic Bayesian network approach to multi-cue based visual tracking

Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. • 2004
View 1 Excerpt

Kalman filter toolbox for Matlab

Kevin P. Murthy
View 1 Excerpt

1 Some Strategies for Kalman Filtering And

SMOOTHINGR Todling, Stephen E. Cohn
View 3 Excerpts

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