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Evaluating a DVS Scheme for Real-Time Embedded Systems

Evaluating a DVS Scheme for Real-Time Embedded Systems. Ruibin Xu, Daniel Mossé and Rami Melhem. Introduction. Energy conservation is important for real-time embedded systems Dynamic Voltage Scaling (DVS) is effective in power management

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Evaluating a DVS Scheme for Real-Time Embedded Systems

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  1. Evaluating a DVS Scheme for Real-Time Embedded Systems Ruibin Xu, Daniel Mossé and Rami Melhem

  2. Introduction • Energy conservation is important for real-time embedded systems • Dynamic Voltage Scaling (DVS) is effective in power management • A popular problem: minimizing energy consumption while meeting the deadlines

  3. Frame length time Focus • Frame-based systems that execute variable workloads • The problem becomes minimizing the expected energy consumption while meeting the deadlines ……

  4. A New DVS Scheme (MEEC) emsoft’05 original problem relax simplified problem efficient algorithm Evaluations fix practical solution optimal solution parc’05

  5. Task and System Model • N periodic tasksT1, T2, …, TN to be executed consecutively in each frame • The power function is p(f) = c0+c1f α

  6. slack slack slack Review of Existing Schemes Proportional Scheme Greedy Scheme Statistical Scheme

  7. The MEEC Scheme • Incorporates the variability of the tasks into the speed schedule • The variability of the tasks are captured by the probability density function of the workload of the tasks • Aims to minimize the expected energy consumption in the system probability workload

  8. β2 β3 β4 β1d (1-β1)d d The MEEC Scheme slack β1

  9. … d d are Both are proportional to 1/d2 An Important Property The optimal expected energy consumption for

  10. β4=100% β3=xx% vs. β2=xx% vs. β1=xx% vs. Computing βi T1 T2 T3 T4

  11. Applying PACE • PACE is a technique in which the execution speed is gradually increased as the task progresses

  12. The MEEC Scheme • The β values (optimal) are computed based on the assumption of unrestricted continuous frequency • We need to deal with: • Minimum and maximum speed restriction • Discrete speed • We have solutions and will use simulation to test them

  13. Evaluations – Power models • Synthetic processor • Strictly conforms to p(f)=f3 • 10 frequencies: 100MHz, 200MHz,…, 1000MHz • Intel Xscale • Power numbers from Intel datasheets • p(f) = 80+1520(f/1000)3

  14. Evaluation – Synthetic Workload • We simulated systems that have 5,10,15,20 tasks • The WCEC of each task is randomly generated from 10M to 1G cycles • The probability distribution of each task is randomly chosen from 6 representative distributions • Frame length

  15. Evaluation – Synthetic Workload • We evaluated 8 schemes • Proportional with and without PACE • Greedy with and without PACE • Statistical with and without PACE • MEEC with and without PACE • We simulated 100,000 frames and computed the average energy consumption per frame for each scheme

  16. Results – Synthetic Workload • For synthetic CPU, the best scheme is always MEEC (with or without PACE), but MEEC with PACE is only better than MEEE without PACE 13.6% of the time with an average saving of 1.2% • For Intel Xscale, the best scheme is always MEEC without PACE • Conclusion: PACE is not recommended in the MEEC scheme

  17. β values Can differ a lot compute PACE (discrete frequency) fix Why PACE Is Not Good in MEEC scheme? PACE (under the assumption of unrestricted continuous frequency)

  18. Results – Synthetic Workload

  19. Evaluation – Automatic Target Recognition (ATR) • The ATR application does pattern matching of targets in images • The regions of interest (ROI) in the image are detected and each ROI is compared with all the templates • Image processing time is proportional to the number of ROIs

  20. Evaluation – Automatic Target Recognition (ATR) • A front-end is responsible for collecting images and send them to the back-end periodically for target recognition • This application can be modeled as a frame-based real-time system in which all the tasks have the same workload distribution front-end …… back-end

  21. Evaluation – Automatic Target Recognition (ATR) • Simulation setup • Use Intel Xscale • The period is 100ms • The front-end sends 1 to 6 images to the back-end • The number of ROIs in an image varies from 1 to 8 • The back-end precomputes 6 speed schedules

  22. Results - Automatic Target Recognition (ATR)

  23. Summary • In this paper, we demonstrate and evaluate a new DVS scheme that aims to minimize the expected energy consumption in the system

  24. Conclusions • The MEEC scheme achieves significant energy savings over the existing schemes • Using only static information or aggregating dynamic information, even with probabilistic techniques, will not produce as good results as when dynamic information for each task in considered separately

  25. Thank you

  26. A Simple Example • 3 tasks, the frame length is 14 time units • For the CPU, c0=0, c1=1, fmin=0, and fmax=1

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