1. Department of Electrical and Computer Engineering Auburn University, AL 36849 USA

2.  Prof. Vishwani Agrawal and Prof. Prathima Agrawal for their invaluable guidance throughout my work,  Prof. Victor P Nelson for being my committee member and for his courses that helped me understand various tools,  All staff members of EE department,  My friends and family for their support throughout my research. July 18, 20162

3.  Introduction  Problem Statement  Background  Methodology  Simulation setup  Results  Applications  Conclusion July 18, 20163

4.  Microprocessors—single-chip computers—are the building blocks of the information world.  In the next two decades, diminishing transistor-speed scaling and practical energy limits create new challenges for continued performance scaling.  Energy efficiency is the new fundamental limiter of processor performance, way beyond numbers of processors. July 18, 20164

5.  Performance, Power and Area are three conflicting goals, and industry demands that all three aspects be co-optimized.  To obtain a complete performance modelling requires marrying everything from high-level modelling and synthesis to better characterization and verification. 5

6.  Obtain data on voltage, frequency and cycle efficiency of the processor for time and energy optimization.  Determine operating conditions (voltage and frequency) for optimal time energy operations. July 18, 20166

8.  There are three main sources of power dissipation:  Dynamic power dissipation  Short circuit dissipation  Static/Leakage dissipation 8

9. Power = Energy/transition Transition rate  Due to charging and discharging of capacitances. = C L V DD f 0  1(1) = C L V DD 2 f P 0  1(2) = C switched V DD 2 f (3)  Power dissipation is data dependent – depends on the switching probability  Switched capacitance C switched = P 0  1 C L = α C L (α is called the switching activity) 9

10.  Short Circuit Power  Occurs during signal transitions when both pullup and pulldown paths are partially conducting causing a direct path between Vdd and GND.  Static Power  This power dissipation occurs all the time through leakage even when the device is in standby mode and is given as: P static = I static V dd July 18, 201610

11.  What is Characterization?  Characterization over Process, Voltage, Frequency, Power, Temperature  Performance Metric  Energy Efficiency Metric July 18, 201611

12.  PDP(Power Delay Product)/Energy per Cycle ▪ PDP = P avg x t p  Energy Delay Product.  Cycle Efficiency July 18, 201612

13.  Clock Frequency  MIPS  MFLOPS  Synthetic Benchmarks  Performance per Watt July 18, 201613

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15.  Time Performance of Processor.  Speed of a processor is measured in cycles per second or clock frequency (f). ▪ Here a clock cycle means 1/f second in time  Execution time of a program using C clock cycles = C/f  Time performance = f/C  Energy Performance of a Processor.  Efficiency of a processor may be measured in cycles per joule or cycle efficiency (η). ▪ Also, a clock cycle means 1/ η joule in energy  Energy dissipated by a program using C clock cycles = C/η  Energy performance = η/C  So the power consumed can be given as, P = f/ η (Product of Energy and Time) July 18, 201615

16.  Technology Characterization  Simulate a reasonable size adder circuit using selected vectors.  Scale adder data to obtain processor power (cycle efficiency) and frequency at different operating points using scale factors.  Develop power management scenarios using cycle efficiency and frequency. July 18, 201616

17.  Questa Sim  Design, compile and simulate designs  Leonardo Spectrum  ASIC and standard cell synthesis  Design Architect-IC  Schematic Capture  HSPICE  Circuit simulation and verification July 18, 201617

18. July 18, 2016  Adder circuit  Fundamental block of functional units  Often in processor’s critical path  Used 16-bit Ripple Carry Adder.  PTM Models  Characterized in two PTM models: bulk CMOS and High-K  Technology node: 45nm, 32nm and 22nm 18

20.  1000 random vectors were generated using a MATLAB code  Simulation in H-spice in 90nm Bulk CMOS PTM at 1.4 volts and frequency 1.45 GHz gives cycle avg. power per vector. July 18, 2016 20

21. July 18, 2016  Out of 1000 random vectors 50 vector pair were selected such that:  16 consume avg. power  17 consume above avg. power including the peak power vector pair  17 consume below avg. power including the min. power vector pair 21

22. Simulation Data from H-spice for 32nm Bulk CMOS PTM Model VoltagePower from simulationTiming from simulationEnergy per cycle V dd (v) p avg. (µW) p dyn (µW) p static (µW) P peak (µW) Critical path Delay (ps) f max (GHz) e dyn (fJ) e static (fJ) e avg. (fJ) 1.2124.0391.3732.66397.71320.853.1229.3210.4839.8 1.15100.578.3122.19335.74338.912.9526.547.5234.06 1.181.9366.7215.21261.9360.462.7724.055.4829.53 1.0566.2155.7410.47217.46386.52.5921.544.0525.59 153.7746.517.26178.2418.722.3919.473.0422.51 0.9542.6537.585.07144.77459.032.1817.252.3319.58 0.933.429.833.57115.34509.721.9615.211.820217.03 0.819.0817.321.75173.71666.651.511.551.16712.72 0.79.598.730.85635.76986.511.0148.620.8449.46 0.63.973.570.40614.711792.10.5586.390.7277.12 0.51.1380.9560.1824.014511.70.2224.310.8195.13 0.40.2290.150.0790.695189280.0532.841.4884.33 0.350.10.0480.0510.233441680.0232.132.274.4 0.30.0470.0140.0330.091127600.0091.6013.755.35 0.250.0250.0040.0210.0362793100.0041.0565.856.91 0.20.0140.00090.0130.0177161500.00140.6459.089.73 0.150.00740.00020.00720.008618517000.00050.349413.2713.62 July 18, 201622

23. AVERAGE, PEAK, DYNAMIC AND STATIC POWER PDP/ENERGY PER CYCLE July 18, 201623

24. July 18, 2016 Intel i5 Sandy Bridge 2500K Specifications Technology Node 32nm Voltage Range1.2 - 1.5 volts 3.3 GHz 5.01 GHz Thermal Design Power, TDP95 Watts Peak Power132 Watts 24

25.  TDP- is the average maximum power in watts the processor dissipates when operating at base frequency with all cores active under a manufacturer defined, high complexity workload.  Peak power is the maximum power dissipated by the processor. July 18, 201625

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30. Scale FactorsCalculated Values Voltage factor, σ1 f nom, δ1.0588 f max, γ1.6075 Area factor, β July 18, 201630

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32. VoltageScaled PowerScaled FrequencyEnergy per cycleCycle efficiency V dd (v) P avg. (W) P dyn (W) P static (W) f nom (GHz) f max (GHz) E fnom (nJ) E fmax (nJ) η ( 10 6 cycles/J ) ηo (10 6 cycles/J ) 1.29571.0223.983.35.0128.7926.3134.7438.01 1.1577.1660.8716.293.124.7424.722.9240.4943.63 1.163.0351.8611.172.944.4621.4620.1646.649.6 1.0551.0143.337.692.744.1618.6217.6653.756.61 141.4836.155.332.533.8416.415.6860.9663.76 0.9532.9329.213.722.313.514.2813.7370.0472.85 0.925.8123.192.622.083.1512.4311.9980.4883.37 0.814.7513.471.2861.5882.419.299.01107.66110.96 0.77.426.790.6281.0731.6296.916.71144.71149.02 0.63.072.770.2980.5910.8975.25.02192.43199.02 0.50.8770.7430.1330.2350.3563.743.54267.7282.35 0.40.1740.1170.0580.0560.0853.122.76321.02361.92 0.350.0750.038 0.0240.0363.142.6318.66384.45 0.30.0350.0110.0240.00940.0143.772.89265.04346.44 0.250.0180.00290.0150.00380.00584.833.45206.93290.03 0.20.010.00070.00930.00150.00226.774.62147.71216.41 0.150.00540.00010.00530.00060.00099.466.32105.74158.31 July 18, 201632

33.  Because our own greatest access and insight involves Intel designs and data, our graphs and estimates draw heavily on them. July 18, 201633

35. July 18, 2016 Plot showing proposed “Power Management Method" for three different regions. 35

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37. July 18, 2016 Voltage V dd (Volts) Clock Frequencies (MHz)Cycle efficiency Structure Constrained (f max ) Power Constrained (f TDP ) Peak η 0 at f max (10 6 cycles/J) η TDP at f TDP (10 6 cycles/J) 1.35486224331.0923.57 1.255257276134.2229.04 1.25010330038.0134.74 1.154740404043.6342.52 1.1124531 47.91 1.14460475049.649.98 1.054160552056.6158.11 13840627063.7666.02 0.953500721072.8575.87 0.93150828083.3787.11 37

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41. TIME AND ENERGY FOR A PROGRAM THAT EXECUTES IN c= 2 BILLION CLOCK CYCLES Operating Modes Voltage (volts) Clock Frequency f (MHz) Cycle Efficiency η (10 6 cycles/J) Nominal Operating Point 1.2330034.7495W0.6157.57 Overclocked Operating Point 20% Ovrclk At 3300 (80% task) 34.7495W 0.485+0.0798 =0.57 46.06+10.52 = 56.58 1.2 At 5010 (20% task) 38.01132W Optimum Operating Point 1.112453147.9195W 0.44 (-28%) 41.75 (-28%) Dynamic Voltage scale point 0.92330079.01 41.77W (-56%) 0.61 (0%) 25.31 (-56%) Energy Efficient point 0.3536.39384.450.094654.965.2 41

42. PTM Models Intel Processor used Nominal Operation Performance Optimization Energy Optimization Rated SpecificationsOptimized f TDP (MHz) V dd (v) η TDP (10 6 c/J) V dd (v) η TDP (10 6 c/J) V ddopt (v) f opt (MHz) η opt (10 6 c/J) V dd (v) f η0 (MHz) η 0 (10 6 c/J) 45nm bulk Core 2 Duo T9500 26001.2574.291.07108.581.2292082.280.3533.51829.29 45nm High-K Core 2 Duo T9500 26001.2574.290.79350.911.226312089.080.3304.481795 32nm bulk Core i5- 2500K 33001.234.740.9279.011.112453147.910.3536.39384.45 32nm High-K Core i5- 2500K 33001.234.740.67267.571.155494051.770.3414.23953.81 22nm bulk Core i7- 3820QM 27000.8600.796.220.771349475.460.38177.25213.99 22nm High-K Core i7- 3820QM 27000.8600.61137.650.76362680.380.3332.58375.76 42

43. July 18, 2016  Present Work  Simulation based evaluation.  Power management is described through: ▪ Improving rated cycle efficiency ▪ Performance optimization ▪ Energy optimization  Future Work  Process variation can be taken in account  Effect of noise margin in sub-threshold region  Better evaluation of activity factor 43

44. July 18, 2016 [1] Harshit Goyal and V. D. Agrawal, “Characterizing Processors for Energy and Performance Management” in Proc. 16th International Workshop on Microprocessor/SoC Test and Verification (MTV), Austin, Texas, Dec. 3-4, 2015 [2] Harshit Goyal and V. D. Agrawal, “Characterizing Processors for Energy and Performance Management” IEEE VLSI Test Symposium, Las vegas, CA, April 2016 (Poster) [3] D. A. Patterson and J. L. Hennessy, Computer Organization& Design, the Hardware/Software Interface. San Francisco, California: Morgan Kaufman, fourth edition, 2008. [4] Aditi shinde and V. D. Agrawal, “Managing Performance and Efficiency of a Processor”, in proc. 45 th Southeastern Symp. System Theory, 2013. [5] K. Kim and V. D. Agrawal, “Dual Voltage Design for Minimum Energy using Gate Slack,” in Proc. International Conf. on Industrial Technology, 2011, pp. 419–424. [6] K. Kim and V. D. Agrawal, “Minimum Energy CMOS Design with Dual Subthreshold Supply and Multiple Logic-Level Gates,” in Proc. International Symp. Quality Electronic Design, 2011, pp. 689–694. [7]. Bienia, C. et. al. The PARSEC benchmark suite: Characterization and architectural implications. The 17th International Symposium on Parallel Architectures and Compilation Techniques (2008). [8]. Borkar, Shekhar, and Andrew A. Chien. "The future of microprocessors."Communications of the ACM 54.5 (2011): 67-77. 44

45. July 18, 2016 [9] Wang, A; Chandrakasan, AP.; Kosonocky, S.V., "Optimal supply and threshold scaling for subthreshold CMOS circuits," VLSI, 2002. Proceedings. IEEE Computer Society Annual Symposium on, vol., no., pp.5,9, 2002 [10] Venkataramani, P. Reducing ATE Test Time by Voltage and Frequency Scaling. PhD thesis, Auburn University, Auburn, AL, May 2014. [11] Venkataramani, P., Sindia, S., and Agrawal, V. D. A Test Time Theorem and its Applications. Journal of Electronic Testing: Theory and Applications 30, 2 (2014), 229-236. [12] Venkataramani, P., and Agrawal, V. D. Reducing Test Time of Power Constrained Test by Optimal Selection of Supply Voltage. In Proc. 26th International Conf. VLSI Design (Jan. 2013), pp. 273-278. [13] Design Architect User Guide. Mentor Graphics Corp., Wilsonville, OR, 1991-1995. [14] HSPICE Signal Integrity User Guide. Synopsys, Inc., 700, East Middlefield Road, Mountain View, CA 94043, 2010. [15] Leonardo Spectrum User Guide. Mentor Graphics Corp., Wilsonville, OR, 2011. [16] Questa Sim User Guide. Mentor Graphics Corp., Wilsonville, OR, 2011. [17] Intel Core i5-2500K Processor (6M Cache, up to 3.70 GHz) Specifications, 2016. http://ark.intel.com/products/52210/Intel-Core-i5-2500K-Processor-6M-Cache- up-to-3 70-GHz. 45

46. July 18, 201646 Thank You