Managing Performance and Efficiency of a Processor Advisor: Dr. Vishwani Agrawal Committee: Dr. Adit Singh and Dr. Victor Nelson Department of Electrical.

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Presentation transcript:

Managing Performance and Efficiency of a Processor Advisor: Dr. Vishwani Agrawal Committee: Dr. Adit Singh and Dr. Victor Nelson Department of Electrical and Computer Engineering Auburn University November 1, 2012Aditi Shinde: MEE Project Defense1 Master’s Project Defense Aditi Shinde

OUTLINE  Motivation  Chip Power Density  System Optimization Triangle  Performance  Characteristic of a Performance Metric  Existing Metrics  Energy Efficiency  Energy Efficiency Metrics  Problem Statement  Proposed Work  Characterization of Intel Pentium M  Cycle Efficiency  Cycle Efficiency and Performance  Conclusion  Limitations  Future Work  References Aditi Shinde: MEE Project DefenseNovember 1, 20122

Aditi Shinde: MEE Project Defense Pentium® P Year Power Density (W/cm 2 ) Hot Plate Nuclear Reactor Rocket Nozzle Sun’s Surface Source: Patrick P. Gelsinger, Keynote, ISSCC, Feb VLSI Chip Power Density 3

Performance System Optimization Triangle Aditi Shinde: MEE Project DefenseNovember 1, 20124

 How fast is your computer ?  Performance = Aditi Shinde: MEE Project DefenseNovember 1, Source: D. A. Patterson and J. L. Hennessy, Computer Organization & Design, the hardware/Software Interface, Fourth Edition, San Francisco, California: Morgan Kaufman Publishers, Inc., 2008.

 Linearity  Reliability  Repeatability  Easiness of measurement  Consistency  Independence Aditi Shinde: MEE Project DefenseNovember 1, Source: D. J. Lilja, ”Measuring Computer Performance: A Practitioner’s Guide”, Cambridge University Press, New York, NY, 2000

 Clock Rate  MIPS  MFLOPS  SPEC  QUIPS  Synthetic Benchmarks  Execution Time Aditi Shinde: MEE Project DefenseNovember 1, 20127

 Performance achieved per unit power.  Useful in determining battery life of a computer system. Aditi Shinde: MEE Project DefenseNovember 1, 20128

 Et 2 Energy and Time (square) Product  Power × Time (Energy per Operation) Aditi Shinde: MEE Project DefenseNovember 1, Source: M. Hicks,” Energy Efficient Branch Prediction” in Doctor of Philosophy thesis, University of Hertfordshire, Dec. 2007

 Given a limited source of energy, can we determine the number of cycles (and hence the number of instructions) that can be executed for a given processor? Aditi Shinde: MEE Project DefenseNovember 1,

 We characterize the Intel Pentium M processor and define a new metric called ‘Cycle Efficiency’ and analyze it. 11

 Source: K. Kim, “Ultra Low Power CMOS Design” in Doctor of Philosophy’s dissertation, Auburn University, Dept. of ECE, Auburn, Alabama, May Aditi Shinde: MEE Project DefenseNovember 1,

Aditi Shinde: MEE Project DefenseNovember 1,

 We define new metric, cycle efficiency as Aditi Shinde: MEE Project DefenseNovember 1,

Aditi Shinde: MEE Project DefenseNovember 1,

 For a program that executes in 1.3 billion clock cycles. VoltageFrequencyCycle EfficiencyTimeTotal Energy Consumed 1.2 V1.3 GHz15 megacycles/joule1 seconds86.7 Joules 0.6 V350 MHz70 megacycles/joule4 seconds18.6 Joules 200 mV100 MHz660 megacycles/joule 13 seconds1.97 Joules November 1, 2012Aditi Shinde: MEE Project Defense16

 November 1, 2012Aditi Shinde: MEE Project Defense 17

 Performance = Say, Time factor =  Energy Efficiency = = Aditi Shinde: MEE Project DefenseNovember 1,

 Performance proportional to Time Factor.  Energy Efficiency proportional to Cycle Efficiency.  Role played is analogous. Aditi Shinde: MEE Project DefenseNovember 1,

 Number of cycles that can be completed per given energy resource can be determined.  Number of instructions and hence what part of the program that can be executed knowing the cycles taken per instruction can be determined. Aditi Shinde: MEE Project DefenseNovember 1,

 Power values are benchmark program dependent.  ‘Almost Perfect Approximation’ by curve fitting and trend line insertion techniques. Aditi Shinde: MEE Project DefenseNovember 1,

 Running benchmark programs on actual processor and finding the energy per cycle.  Averaging values over number of benchmark programs to reduce program dependency. Aditi Shinde: MEE Project DefenseNovember 1,

 Other approaches, like using the Alpha Power Law Model for MOSFETS can also be used for characterization.  Designing a method where operating points between ‘best energy efficient’ and ‘best performance’ can be derived depending on our requirements. Aditi Shinde: MEE Project DefenseNovember 1,

1. Synopsys, Inc., “HSPICE User Guide: Simulation and Analysis”, 2. H. Hanson, K. Rajamani, S. Keckler, F. Rawson, S. Ghiasi, J. Rubio, “Thermal Response to DVFS: Analysis with an Intel Pentium M,” In Proceedings of International Symposium on Low Power Electronics and Design, August 27–29, 2007, Portland, Oregon, pp M. Hicks,” Energy Efficient Branch Prediction” in Doctor of Philosophy thesis, University of Hertfordshire, Dec D. J. Lilja, ”Measuring Computer Performance: A Practitioner’s Guide,” Cambridge University Press, New York, NY, K. Kim, “Ultra Low Power CMOS Design,” Doctor of Philosophy’s dissertation, Auburn University, Dept. of ECE, Auburn, Alabama, May Patrick P. Gelsinger, Keynote, ISSCC, Feb Aditi Shinde: MEE Project DefenseNovember 1,

7. D. A. Patterson and J. L. Hennessy, Computer Organization & Design, the Hardware/Software Interface, Fourth Edition, San Francisco, California: Morgan Kaufman Publishers, Inc., W. Zhao and Y. Cao, “New Generation of Predictive Technology Model for Sub-45nm Early Design Exploration,“ IEEE Transactions on Electron Devices, vol. 53, no. 11, pp. 2816–2823,

Aditi Shinde: MEE Project DefenseNovember 1,

 Aditi Shinde: MEE Project DefenseNovember 1, 2012