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Dakai Zhu, Rami Melhem, and Bruce Childers Presented by Xuan Qi

Scheduling with Dynamic Voltage/Speed Adjustment Using Slack Reclamation in Multi-Processor Real-Time Systems. Dakai Zhu, Rami Melhem, and Bruce Childers Presented by Xuan Qi. Power is a Big Issue!!!. Microsoft data center at San Antonio: the biggest customer of CPS energy Sensor networks

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Dakai Zhu, Rami Melhem, and Bruce Childers Presented by Xuan Qi

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  1. Scheduling with Dynamic Voltage/Speed Adjustment Using Slack Reclamation in Multi-Processor Real-Time Systems Dakai Zhu, Rami Melhem, and Bruce Childers Presented by Xuan Qi Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  2. Power is a Big Issue!!! • Microsoft data center at San Antonio: the biggest customer of CPS energy • Sensor networks • Mobile Computing • Robots • Medical • Aerospace and military uses Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  3. Outline: • Introduction • Power module • Task module • Scheduling algorithm • Simulation results • Conclusion • References Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  4. Introduction: • Real-time system and tasks with hard deadline • Dynamic Voltage/Frequency Scaling (DVFS) e.g. CPU 1.5V 3.0GHz, 1.3V 2.5GHz, 1.2V 2.0GHz • Multi-processor: N homogenous processors Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  5. Power Module: • P = Ps + h * (Pind + Pd) h = , when processor is active. , when processor is inactive (sleep). • Focus onPd in this paper. • Ed is proportional to ( ). • so if f’ = 1/2f, Ed’ = 1/4Ed. Energy saving is 3/4Ed. Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  6. Task Module: • A task is defined as a tuple (ci, ai) • ci: worst case execution time (WCET) • ai: actual execution time (AET) • Common deadline D • No precedence • Frame-based real-time system Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  7. Save Energy by DVFS: • General idea: • Tasks T1 (4, 3) and T2 (2, 2) • Eold = P * t = • Enew = P * t = • Energy Saving: 10/9 Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  8. Outline: • Introduction • Power module • Task module • Scheduling algorithm • Simulation results • Conclusion • References Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  9. Scheduling for Independent Tasks: • Global – common queue • Optimal-NP [2] • Heuristic - LTF (based on WCET) • Partition – separate queue Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  10. Slack Reclamation Schemes: • Static Power Management • Task’s Dynamic Behavior • AET is a small portion of WCET. [3] • Slack • Unused time considered as slack and can be reused by the following tasks at run-time • Reclaim Slack • Greedy Scheme • Shared Scheme Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  11. LTF Order T1 T3 T4 T2 T1 T4 T2 T3 T1 and T4 T2 and T3 Static Power Management: T1=(6,2); T2=(4,4); T3=(4,4); T4=(2,2); Queue D P1 f = 1 f = 0.8 P2 Time 8 10 Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  12. LTF Order T1 T1 T3 T4 T2 T3 T2 T4 Canonical Execution Scheduling with Greedy Slack Reclamation (GSR): T1=(6,2); T2=(4,4); T3=(4,4); T4=(2,2); Queue D P1 P2 Time 8 GSR: any slack on one processor will be given to the next task running on this processor Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  13. T1 T4 T3 T2 Scheduling with Greedy Slack Reclamation (GSR): T1=(6,2); T2=(4,4); T3=(4,4); T4=(2,2); Queue LTF Order D P1 P2 Time 8 Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  14. T1 T4 T3 T2 Scheduling with Greedy Slack Reclamation (GSR): T1=(6,2); T2=(4,4); T3=(4,4); T4=(2,2); Queue LTF Order D P1 P2 Time 2 6 8 Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  15. T1 T4 T2 Scheduling with Greedy Slack Reclamation (GSR): T1=(6,2); T2=(4,4); T3=(4,4); T4=(2,2); Queue LTF Order D P1 T3 P2 Time 2 6 8 10 GSR MISS the deadline! Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  16. T1 T2 T3 T4 Scheduling with Shared Slack Reclamation (SSR): T1=(6,2); T2=(4,4); T3=(4,4); T4=(2,2); Queue LTF Order D P1 P2 Time 2 4 6 8 SSR: slack on one processor will be shared with other processors when possible Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  17. T1 T2 T3 T4 Scheduling with Shared Slack Reclamation (SSR): T1=(6,2); T2=(4,4); T3=(4,4); T4=(2,2); Queue LTF Order D P1 P2 Time 2 4 6 8 SSR: sharing slack Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  18. T1 T2 T4 Scheduling with Shared Slack Reclamation (SSR): T1=(6,2); T2=(4,4); T3=(4,4); T4=(2,2); Queue LTF Order D P1 T3 P2 Time 2 4 6 8 Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  19. T1 T2 Scheduling with Shared Slack Reclamation (SSR): T1=(6,2); T2=(4,4); T3=(4,4); T4=(2,2); Queue LTF Order D P1 T3 P2 T4 Time 2 4 6 8 SSR: meet the deadline Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  20. Scheduling with Shared Slack Reclamation (SSR): • The SSR algorithm can be extended to N processors. Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  21. Outline: • Introduction • Power module • Task module • Scheduling algorithm • Simulation results • Conclusion • References Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  22. Simulation Results-Independent Tasks: [1] Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  23. Simulation Results-Independent Tasks: [1] Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  24. Conclusion: • Multi-processor Real-time System • Dynamic adjust speed at run time • Both dependent task set & independent task set • Achieve up to 60% energy saving Slides incorporate materials kindly provided by Dr. Dakai Zhu.

  25. References: • [1] Dakai Zhu, Rami Melhem, and Bruce Childers. Scheduling with Dynamic Voltage/Speed Adjustment Using Slack Reclamation in Multi-Processor Real-Time Systems. IEEE Trans. On Parallel and Distributed Systems, pp. 686-700, July 2003. • [2] M. L. Dertouzos and A. K. Mok. Multiprocessor on-line scheduling of hard-real-time tasks. IEEE Trans. On Software Engineering, 15(12):1497–1505, 1989. • [3] R. Ernst and W. Ye. Embedded program timing analysis based on path clustering and architecture classification. In Proc. of The International Conference on Computer-Aided Design, pages 598–604, San Jose, CA, Nov. 1997. Slides incorporate materials kindly provided by Dr. Dakai Zhu.

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