Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/1250662.1250700acmconferencesArticle/Chapter ViewAbstractPublication PagesiscaConference Proceedingsconference-collections
Article

Power model validation through thermal measurements

Published: 09 June 2007 Publication History

Abstract

Simulation environments are an indispensable tool in the design, prototyping, performance evaluation, and analysis of computer systems. Simulator must beable to faithfully reflect the behavior of the system being analyzed. To ensure the accuracy of the simulator, it must be verified and determined to closely match empirical data. Modern processors provide enough performance counters to validate the majority of the performance models; nevertheless, the information provided is not enough to validate power and thermal models.
In order to address some of the difficulties associated with the validation of power andthermal models, this paper proposes an infrared measurement setup to capture run-time power consumption and thermal characteristics of modern chips. We use infrared cameras with high spatial resolution (10x10μm) and high frame rate (125fps) to capture thermal maps. To generate a detailed power breakdown (leakage and dynamic) for each processor floorplan unit, we employ genetic algorithms. The genetic algorithm finds a power equation for each floorplan block that produces the measured temperature for a given thermal package. The difference between the predicted power and the externally measured power consumption for an AMD Athlon analyzed in this paper has less than 1% discrepancy. As an example of applicability, we compare the obtained measurements with CACTI power models, and propose extensions to existing thermal models to increase accuracy.

References

[1]
D. Brooks, V. Tiwari, and M. Martonosi. Wattch: a Framework for Architectural-Level Power Analysis and Optimizations. In International Symposium on Computer Architecture, pages 83--94, Jun 2000.
[2]
Y. Cheng and C. Hu. MOSFET Modeling and Bsim3 User's Guide. Kluwer Academic Publishers, Norwell, MA, USA, 1999.
[3]
Y.K. Cheng, P. Raha, C.C. Teng, E. Rosenbaum, and S.M. Kang. ILLIADS-T: An Electrothermal Timing Simulator for Temperature-Sensitive Reliability Diagnosis of CMOS VLSI Chips. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 17(8):1434--1445, Aug 1998.
[4]
S.-W. Chung and K. Skadron. Using On-Chip Event Counters For High-Resolution, Real-Time Temperature Measurement. In Thermal and Thermomechanical Phenomena in Electronics Systems, 2006, pages 114--120. IEEE Computer Society, May 2006.
[5]
D.E. Goldberg. Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley Professional, January 1989.
[6]
H.F. Hamann, J. Lacey, A. Weger, and J. Wakil. Spatially-resolved imaging of microprocessor power (SIMP): hotspots in microprocessors. In Thermal and Thermomechanical Phenomena in Electronics Systems, 2006, pages 121--125. IEEE Computer Society, May 2006.
[7]
C. Isci and M. Martonosi. Runtime power monitoring in high-end processors: Methodology and empirical data. In MICRO 36: Proceedings of the 36th annual IEEE/ACM International Symposium on Microarchitecture. IEEE Computer Society, 2003.
[8]
M.N. Ozisik. Inverse Heat Transfer. Taylor and Francis, 2000.
[9]
M. Raudensky, K.A. Woodbury, J. Kral, and T. Brezina. Genetic Algorithm in Solution of Inverse Heat Conduction Problems. pages 293--306, 1995.
[10]
K. Skadron, M.R. Stan, W. Huang, S. Velusamy, K. Sankaranarayanan, and D. Tarjan. Temperature-Aware Microarchitecture. In Proceedings of the 30th Annual International Symposium on Computer Architecture, pages 2--13, Jun 2003.
[11]
S. Wilton and N. Jouppi. CACTI: An Enhanced Cache Access and Cycle Time Model. IEEE Journal on Solid-State Circuits, 31(5):677--688, May 1996.
[12]
W. Wu, L. Jin, J. Yang, P. Liu, and S.X.-D. Tan. A systematic method for functional unit power estimation in microprocessors. In DAC '06: Proceedings of the 43nd annual conference on Design automation, New York, NY, USA, 2006. ACM Press.
[13]
Y. Zhang, D. Parikh, K. Sankaranarayanan, K. Skadron, and M. Stan. Hotleakage: A temperature-aware model of subthreshold and gate leakage for architects. Technical Report CS-2003-05, Univ. of Virginia Dept. of Computer Science, March 2003.

Cited By

View all
  • (2022)NanoLeak: A Fast Analytical Green’s Function-based Leakage-aware Thermal Simulator2022 35th International Conference on VLSI Design and 2022 21st International Conference on Embedded Systems (VLSID)10.1109/VLSID2022.2022.00026(74-79)Online publication date: Feb-2022
  • (2021)Design and Performance Analysis of 4-bit Nano-processor Design for Low Area, Low Power and Minimum Delay Using 32nm FinFET TechnologyWSEAS TRANSACTIONS ON ELECTRONICS10.37394/232017.2021.12.112(1-8)Online publication date: 20-Jan-2021
  • (2021)$AP^{3}$: Adaptive Power Prediction Framework based on Spatial Partition Multi-Phase Model2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys)10.1109/HPCC-DSS-SmartCity-DependSys53884.2021.00039(89-98)Online publication date: Dec-2021
  • Show More Cited By

Index Terms

  1. Power model validation through thermal measurements

      Recommendations

      Comments

      Information & Contributors

      Information

      Published In

      cover image ACM Conferences
      ISCA '07: Proceedings of the 34th annual international symposium on Computer architecture
      June 2007
      542 pages
      ISBN:9781595937063
      DOI:10.1145/1250662
      • General Chair:
      • Dean Tullsen,
      • Program Chair:
      • Brad Calder
      • cover image ACM SIGARCH Computer Architecture News
        ACM SIGARCH Computer Architecture News  Volume 35, Issue 2
        May 2007
        527 pages
        ISSN:0163-5964
        DOI:10.1145/1273440
        Issue’s Table of Contents
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Sponsors

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 09 June 2007

      Permissions

      Request permissions for this article.

      Check for updates

      Author Tag

      1. power and thermal measurements

      Qualifiers

      • Article

      Conference

      SPAA07
      Sponsor:

      Acceptance Rates

      Overall Acceptance Rate 543 of 3,203 submissions, 17%

      Upcoming Conference

      ISCA '25

      Contributors

      Other Metrics

      Bibliometrics & Citations

      Bibliometrics

      Article Metrics

      • Downloads (Last 12 months)34
      • Downloads (Last 6 weeks)1
      Reflects downloads up to 13 Nov 2024

      Other Metrics

      Citations

      Cited By

      View all
      • (2022)NanoLeak: A Fast Analytical Green’s Function-based Leakage-aware Thermal Simulator2022 35th International Conference on VLSI Design and 2022 21st International Conference on Embedded Systems (VLSID)10.1109/VLSID2022.2022.00026(74-79)Online publication date: Feb-2022
      • (2021)Design and Performance Analysis of 4-bit Nano-processor Design for Low Area, Low Power and Minimum Delay Using 32nm FinFET TechnologyWSEAS TRANSACTIONS ON ELECTRONICS10.37394/232017.2021.12.112(1-8)Online publication date: 20-Jan-2021
      • (2021)$AP^{3}$: Adaptive Power Prediction Framework based on Spatial Partition Multi-Phase Model2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys)10.1109/HPCC-DSS-SmartCity-DependSys53884.2021.00039(89-98)Online publication date: Dec-2021
      • (2019)SimmaniProceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture10.1145/3352460.3358322(1050-1062)Online publication date: 12-Oct-2019
      • (2019)An Open-Hardware Platform for MPSoC Thermal ModelingEmbedded Computer Systems: Architectures, Modeling, and Simulation10.1007/978-3-030-27562-4_13(184-196)Online publication date: 8-Aug-2019
      • (2016)StroberACM SIGARCH Computer Architecture News10.1145/3007787.300115144:3(128-139)Online publication date: 18-Jun-2016
      • (2016)Catching the fluProceedings of the 53rd Annual Design Automation Conference10.1145/2897937.2897994(1-6)Online publication date: 5-Jun-2016
      • (2016)StroberProceedings of the 43rd International Symposium on Computer Architecture10.1109/ISCA.2016.21(128-139)Online publication date: 18-Jun-2016
      • (2015)A calibration based thermal modeling technique for complex multicore systemsProceedings of the 2015 Design, Automation & Test in Europe Conference & Exhibition10.5555/2755753.2757076(1138-1143)Online publication date: 9-Mar-2015
      • (2015)DARP-MPACM Transactions on Design Automation of Electronic Systems10.1145/275555821:1(1-21)Online publication date: 2-Dec-2015
      • Show More Cited By

      View Options

      Get Access

      Login options

      View options

      PDF

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader

      Media

      Figures

      Other

      Tables

      Share

      Share

      Share this Publication link

      Share on social media