1. VADA Lab.SungKyunKwan Univ. 1 Lower Power Voltage Scaling 1999. 8. 성균관대학교 조 준 동 http://vada.skku.ac.kr

2. VADA Lab.SungKyunKwan Univ. 2 Voltage Scaling Merely changing a processor clock frequency is not an effective technique for reducing energy consumption. Reducing the clock frequency will reduce the power consumed by a processor, however, it does not reduce the energy required to perform a given task. Lowering the voltage along with the clock actually alters the energy-per-operation of the microprocessor, reducing the energy required to perform a fixed amount of work.

3. VADA Lab.SungKyunKwan Univ. 3 Dynamic Voltage Scaling(DVS)

4. VADA Lab.SungKyunKwan Univ. 4 Processor Usage Model

5. VADA Lab.SungKyunKwan Univ. 5 OS: Voltage Scaling

6. VADA Lab.SungKyunKwan Univ. 6 Scale Supply Voltage with f CLK

7. VADA Lab.SungKyunKwan Univ. 7 Adaptive Power Supply Voltages

8. VADA Lab.SungKyunKwan Univ. 8 Variable Supply Voltage Block Diagram

9. VADA Lab.SungKyunKwan Univ. 9 Typical MPEG IDCT Histogram

10. VADA Lab.SungKyunKwan Univ. 10 Voltage scheduling under timing constraints –Energy consumption of a processor: 10nJ/cycle at 2.5V 25nJ/cycle at 4 V 40nJ/cycle at 5V –maximum clock frequencies: 50MHz at 5V, 40MHz at 4V, 25MHz at 2.5V –Given that an application needs 1000M cycles to finish and the timing constaint is 25sec.

11. VADA Lab.SungKyunKwan Univ. 11 Different Voltage Schedules 0510152025 Time(sec) 5.0 2 1000Mcycles 50MHz 40J (A) 0510152025 Time(sec) 5.0 2 750Mcycles 50MHz 32.5J (B) 0510152025 Time(sec) 5.0 2 1000Mcycles 40MHz 25J (C) Timing constraint 2.5 2 250Mcycles 25MHz 4.0 2 Energy consumption (  V dd 2 )

12. VADA Lab.SungKyunKwan Univ. 12 Example of Variable Supply

13. VADA Lab.SungKyunKwan Univ. 13 DVS Implementation

14. VADA Lab.SungKyunKwan Univ. 14 Variable Supply Voltage Block Diagram Computational work varies with time. An approach to reduce the energy consumption of such systems beyond shut down involves the dynamic adjustment of supply voltage based on computational workload. The basic idea is to lower power supply when the a fixed supply for some fraction of time. The supply voltage and clock rate are increased during high workload period.

15. VADA Lab.SungKyunKwan Univ. 15 Data Driven Signal Processing The basic idea of averaging two samples are buffered and their work loads are averaged. The averaged workload is then used as the effective workload to drive the power supply. Using a pingpong buffering scheme, data samples I n +2, I n +3 are being buffered while I n, I n +1 are being processed.

16. VADA Lab.SungKyunKwan Univ. 16 Example of Buffering

17. VADA Lab.SungKyunKwan Univ. 17 Graphical Interpretation

18. VADA Lab.SungKyunKwan Univ. 18 Buffering Example: MPEG Decoder

19. VADA Lab.SungKyunKwan Univ. 19 DVS

20. VADA Lab.SungKyunKwan Univ. 20 DVS Scheduling Framework µProc. Speed Time StartDeadlineStartDeadline Idle time represents wasted energy Lower speed, Lower voltage, Lower energy Energy ~ Work Speed Work Use real-time framework to constrain task voltage scheduling

21. VADA Lab.SungKyunKwan Univ. 21 DVS Simulation Speed Time S1S1 S2S2 S3S3 D1D1 D3D3 D2D2 Task Variance Weather Interrupts User Input Cache Behavior Scheduling Overhead Intercom RealityTheory Implementation Simulate run-time scheduler to fully understand voltage-scaling behavior

22. VADA Lab.SungKyunKwan Univ. 22 Simulation Infrastructure GUI Run-time Scheduler Voltage Scheduler Application support libraries MPEG  Priority 80 GUI  Priority 23 MPEG  Priority 80 GUI  Priority 23 Speed  Priority { Frame_Start(deadline); Decode_MPEG_Frame(); Frame_Finish(); } { Frame_Start(deadline); Decode_MPEG_Frame(); Frame_Finish(); } Windowing Cryptography I/O Support lpARM MPEG Develop support environment to model complete software system

23. VADA Lab.SungKyunKwan Univ. 23 Run-Time Voltage Scaling Normalized to 3.3V fixed-voltage processor Combination of independent benchmarks Dynamic Voltage Scaling significantly reduces energy dissipation!

24. VADA Lab.SungKyunKwan Univ. 24 Run-Time Performance Analysis AudioMPEGGUI Software can automatically recognize and adjust for bi-modal GUI distribution 0 2x deadline Normalized to deadline at max processor speed Application characteristics strongly affect voltage scaling performance

25. VADA Lab.SungKyunKwan Univ. 25 Compute ASAP+ System Shutdown

26. VADA Lab.SungKyunKwan Univ. 26 Another Approach: Reduce Clock Frequency

27. VADA Lab.SungKyunKwan Univ. 27 Voltage Scheduling II

28. VADA Lab.SungKyunKwan Univ. 28 Evaluation: Algorithms

29. VADA Lab.SungKyunKwan Univ. 29 AVG Computes an exponentially moving average of the previous intervals. At each interval the run-percent from the previous interval is combined with the previous running average, forming a long-term prediction of system behavior. is the relative weighting of past intervals relative of the current interval (larger value means a great weight on the past) using the equation (weight X old + new)/(weight+1). 3 can be used.

30. VADA Lab.SungKyunKwan Univ. 30 OS: Voltage Scheduling

31. VADA Lab.SungKyunKwan Univ. 31 Run-Time Scheduling Dynamics µProc. Speed Time Thread accomplishing more than expected, reduce speed Deadline exceeded, increase speed Higher-priority task Run faster to make up lost time Initial speed estimate Optimal schedule E(work) Workload calculated to be average of previous frames Periodically re-evaluate schedule to adjust for unforeseen events

32. VADA Lab.SungKyunKwan Univ. 32 Vertical Layering

33. VADA Lab.SungKyunKwan Univ. 33 Optimal Scheduling For a region spanned by a given task specification, each point in time will either be scheduled at the minimum speed spanned by that task or else the task will not be scheduled to run at that point. Algorithm n tasks to schedule O(n) speed settings to consider for each task O(n) linked tasks requiring adjustment for each setting: Total complexity: O(n 3 ) time.

34. VADA Lab.SungKyunKwan Univ. 34 Scheduling step0

35. VADA Lab.SungKyunKwan Univ. 35 Scheduling step1

36. VADA Lab.SungKyunKwan Univ. 36 Scheduling step2

37. VADA Lab.SungKyunKwan Univ. 37 Scheduling step3

38. VADA Lab.SungKyunKwan Univ. 38 Scheduling step4

39. VADA Lab.SungKyunKwan Univ. 39 Scheduling step5

40. VADA Lab.SungKyunKwan Univ. 40 References [Lin97] Lin et al., "Scheduling Techniques for Variable Voltage Low Power Designs," ACM Transactions on Design Automation of Electronic Systems, vol. 2, no. 2, pp. 81-97, 1997. [Govil95] - Extended simulation with practical algorithms on traces of UNIX workstations [Kuroda98] - Implementation of DVS processor to mitigate effects of process variation [Ishihara98] - Dynamic voltage scaling with non- constant capacitances S. Gary, et. al., "The PowerPC 603 Microprocessor: A Low-Power Design for Portable Applications," Proceedings of the Thirty-Ninth IEEE Computer Society International Conference, Mar. 1994, pp. 307-15. A. Chandrakasan, Low Power Digital CMOS Design, Boston: Kluwer Academic Publishers, 1995. C. Nagendra, et.al., "A Comparison of the Power-Delay Characteristics of CMOS Adders,” Proceedings of the International Workshop on Low Power Design, Apr. 1994, pp. 231-6. T. Callaway and E. Swartzlander, "Optimizing Arithmetic Elements for Signal Processing," VLSI Signal Processing, Vol. 5, New York: IEEE Special Publications, 1992, pp. 91-100. T. Biggs, et. al., "A 1 Watt 68040-Compatible Microprocessor," Proceedings of the IEEE Symposium on Low Power Electronics, Oct. 1994, pp. 8-11. J. Lorch, A Complete Picture of the Energy Consumption of a Portable Computer, M.S. Thesis, University of California, Berkeley, 1995

41. VADA Lab.SungKyunKwan Univ. 41 References S. Kunii, "Means of Realizing Long Battery Life in Portable PCs," Proceedings of the IEEE Symposium on Low Power Electronics, Oct. 1995, pp. 12-3. M. Culbert, "Low Power Hardware for a High Performance PDA," Proceedings of the Thirty-Ninth IEEE Computer Society International Conference, Mar. 1994, pp. 144-7. T. Ikeda, "ThinkPad Low-Power Evolution," Proceedings of the IEEE Symposium on Low Power Electronics, Oct. 1995, pp. 6-7. A. Chandrakasan, A. Burstein, and R.W. Brodersen, "A Low Power Chipset for Portable Multimedia Applications," IEEE Journal of Solid State Circuits, Vol. 29, Dec. 1994, pp. 1415-28. M. Horowitz, T. Indermaur, and R. Gonzalez, "Low-Power Digital Design," Proceedings of the IEEE Symposium on Low Power Electronics, Oct. 1994, pp. 8-11. D. Lidsky and J. Rabaey, "Early Power Exploration - A World Wide Web Application," Proceedings of the Thirty-Third Design Automation Conference, June 1996. T. Burd, Low-Power CMOS Cell Library Design Methodology, M.S. Thesis, University of California, Berkeley, UCB/ERL M94/89, 1994.

42. VADA Lab.SungKyunKwan Univ. 42 A. Chandrakasan, S. Sheng, and R.W. Brodersen, "Low-Power CMOS Digital Design," IEEE Journal of Solid State Circuits, Apr. 1992, pp. 473-84. Advanced RISC Machines, Ltd., ARM710 Data Sheet, Technical Document, Dec. 1994. Integrated Device Technology, Inc., Enhanced Orion 64-Bit RISC Microprocessor, Data Sheet, Sep. 1995. Intel Corp., Embedded Ultra-Low Power Intel486TM GX Processor, SmartDieTM Product Specification, Dec. 1995. A. Stratakos, S. Sanders, and R.W. Brodersen, "A Low-voltage CMOS DC-DC Converter for Portable Battery-operated Systems," Proceedings of the Twenty-Fifth IEEE Power Electronics Specialist Conference, June 1994, pp. 619-26. J. Bunda, et. al., "16-Bit vs. 32-Bit Instructions for Pipelined Architectures," Proceedings of the 20th International Symposium on Computer Architecture, May 1993, pp. 237-46. Advanced RISC Machines, Ltd., Introduction to Thumb, Developer Technical Document, Mar. 1995.

43. VADA Lab.SungKyunKwan Univ. 43 J. Bunda, W.C. Athas, and D. Fussell, "Evaluating Power Implications of CMOS Microprocessor Design Decisions," Proceedings of the International Workshop on Low Power Design, Apr. 1994, pp. 147-52. P. Freet, "The SH Microprocessor: 16-Bit Fixed Length Instruction Set Provides Better Power and Die Size," Proceedings of the Thirty-Ninth IEEE Computer Society International Conference, Mar. 1994, pp. 486-8. T. Burd, B. Peters, A Power Analysis of a Microprocessor: A Study of an Implementation of the MIPS R3000 Architecture, ERL Technical Report, University of California, Berkeley, 1994. J. Montanaro, et. al., "A 160MHz 32b 0.5W CMOS RISC Microprocessor," Proceedings of the Thirty-Ninth IEEE International Solid-State Circuits Conference - Slide Supplement, Feb. 1996, pp. 170-1. J. Bunda, Instruction-Processing Optimization Techniques for VLSI Microprocessors, Ph.D. Thesis, The University of Texas at Austin, 1993. R. Gonzalez and M. Horowitz, "Energy Dissipation in General Purpose Processors," Proceedings of the IEEE Symposium on Low Power Electronics, Oct. 1995, pp. 12-3.