Computer Science Department University of Pittsburgh 1 Evaluating a DVS Scheme for Real-Time Embedded Systems Ruibin Xu, Daniel Mossé and Rami Melhem

Computer Science Department University of Pittsburgh 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

Computer Science Department University of Pittsburgh 3 Focus Frame-based systems that execute variable workloads The problem becomes minimizing the expected energy consumption while meeting the deadlines …… time Frame length

Computer Science Department University of Pittsburgh 4 A New DVS Scheme (MEEC) simplified problem original problem optimal solution practical solution relax fix Evaluations efficient algorithm emsoft’05 parc’05

Computer Science Department University of Pittsburgh 5 Task and System Model N periodic tasksT 1, T 2, …, T N to be executed consecutively in each frame The power function is p(f) = c 0 +c 1 f α

Computer Science Department University of Pittsburgh 6 Review of Existing Schemes slack Proportional Scheme Greedy Scheme Statistical Scheme

Computer Science Department University of Pittsburgh 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 workload probability

Computer Science Department University of Pittsburgh 8 The MEEC Scheme slack β1dβ1d (1-β 1 )d d β1β1 β2β2 β3β3 β4β4

Computer Science Department University of Pittsburgh 9 An Important Property The optimal expected energy consumption for dd … are Both are proportional to 1/d 2

Computer Science Department University of Pittsburgh 10 Computing β i β 4 =100% β 3 =xx% vs. T1T1 T2T2 T3T3 T4T4 β 2 =xx% vs. β 1 =xx%

Computer Science Department University of Pittsburgh 11 Applying PACE PACE is a technique in which the execution speed is gradually increased as the task progresses

Computer Science Department University of Pittsburgh 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

Computer Science Department University of Pittsburgh 13 Evaluations – Power models Synthetic processor  Strictly conforms to p(f)=f 3  10 frequencies: 100MHz, 200MHz,…, 1000MHz Intel Xscale  Power numbers from Intel datasheets  p(f) = (f/1000) 3

Computer Science Department University of Pittsburgh 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

Computer Science Department University of Pittsburgh 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

Computer Science Department University of Pittsburgh 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

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

Computer Science Department University of Pittsburgh 18 Results – Synthetic Workload

Computer Science Department University of Pittsburgh 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

Computer Science Department University of Pittsburgh 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 ……

Computer Science Department University of Pittsburgh 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

Computer Science Department University of Pittsburgh 22 Results - Automatic Target Recognition (ATR)

Computer Science Department University of Pittsburgh 23 Summary In this paper, we demonstrate and evaluate a new DVS scheme that aims to minimize the expected energy consumption in the system

Computer Science Department University of Pittsburgh 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

Computer Science Department University of Pittsburgh 25 Thank you

Computer Science Department University of Pittsburgh 26 A Simple Example 3 tasks, the frame length is 14 time units For the CPU, c 0 =0, c 1 =1, f min =0, and f max =1