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What Your DRAM Power Models Are Not Telling You: Lessons from a Detailed Experimental Study

Published: 12 June 2018 Publication History

Abstract

Main memory (DRAM) consumes as much as half of the total system power in a computer today, due to the increasing demand for memory capacity and bandwidth. There is a growing need to understand and analyze DRAM power consumption, which can be used to research new DRAM architectures and systems that consume less power. A major obstacle against such research is the lack of detailed and accurate information on the power consumption behavior of modern DRAM devices. Researchers have long relied on DRAM power models that are predominantly based off of a set of standardized current measurements provided by DRAM vendors, called IDD values. Unfortunately, we find that state-of-the-art DRAM power models are often highly inaccurate when compared with the real power consumed by DRAM. This is because existing DRAM power models (1) are based off of the worst-case power consumption of devices, as vendor specifications list the current consumed by the most power-hungry device sold; (2) do not capture variations in DRAM power consumption due to different data value patterns; and (3) do not account for any variation across different devices or within a device.

References

[1]
S. Ghose, A. G. Yaglikçi, R. Gupta, D. Lee, K. Kudrolli, W. X. Liu, H. Hassan, K. K. Chang, N. Chatterjee, A. Agrawal, M. O'Connor, and O. Mutlu, "What Your DRAM Power Models Are Not Telling You: Lessons from a Detailed Experimental Study," POMACS, 2018.
[2]
SAFARI Research Group, "VAMPIRE - GitHub Repository," https://github.com/Carnegie Mellon University-SAFARI/VAMPIRE.

Cited By

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  • (2024)Spatial Variation-Aware Read Disturbance Defenses: Experimental Analysis of Real DRAM Chips and Implications on Future Solutions2024 IEEE International Symposium on High-Performance Computer Architecture (HPCA)10.1109/HPCA57654.2024.00048(560-577)Online publication date: 2-Mar-2024
  • (2024)Functionally-Complete Boolean Logic in Real DRAM Chips: Experimental Characterization and Analysis2024 IEEE International Symposium on High-Performance Computer Architecture (HPCA)10.1109/HPCA57654.2024.00030(280-296)Online publication date: 2-Mar-2024
  • (2024)SpyHammer: Understanding and Exploiting RowHammer Under Fine-Grained Temperature VariationsIEEE Access10.1109/ACCESS.2024.340938912(80986-81003)Online publication date: 2024
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Published In

cover image ACM SIGMETRICS Performance Evaluation Review
ACM SIGMETRICS Performance Evaluation Review  Volume 46, Issue 1
SIGMETRICS '18
June 2018
142 pages
ISSN:0163-5999
DOI:10.1145/3292040
Issue’s Table of Contents
  • cover image ACM Conferences
    SIGMETRICS '18: Abstracts of the 2018 ACM International Conference on Measurement and Modeling of Computer Systems
    June 2018
    155 pages
    ISBN:9781450358460
    DOI:10.1145/3219617
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 June 2018
Published in SIGMETRICS Volume 46, Issue 1

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Author Tags

  1. data encoding
  2. dram
  3. energy
  4. experimental characterization
  5. low-power design
  6. memory systems
  7. power consumption
  8. power modeling

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  • United States Department of Energy

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Cited By

View all
  • (2024)Spatial Variation-Aware Read Disturbance Defenses: Experimental Analysis of Real DRAM Chips and Implications on Future Solutions2024 IEEE International Symposium on High-Performance Computer Architecture (HPCA)10.1109/HPCA57654.2024.00048(560-577)Online publication date: 2-Mar-2024
  • (2024)Functionally-Complete Boolean Logic in Real DRAM Chips: Experimental Characterization and Analysis2024 IEEE International Symposium on High-Performance Computer Architecture (HPCA)10.1109/HPCA57654.2024.00030(280-296)Online publication date: 2-Mar-2024
  • (2024)SpyHammer: Understanding and Exploiting RowHammer Under Fine-Grained Temperature VariationsIEEE Access10.1109/ACCESS.2024.340938912(80986-81003)Online publication date: 2024
  • (2023)DRAM Bender: An Extensible and Versatile FPGA-Based Infrastructure to Easily Test State-of-the-Art DRAM ChipsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2023.328217242:12(5098-5112)Online publication date: Dec-2023
  • (2021)ROMANet: Fine-Grained Reuse-Driven Off-Chip Memory Access Management and Data Organization for Deep Neural Network AcceleratorsIEEE Transactions on Very Large Scale Integration (VLSI) Systems10.1109/TVLSI.2021.306050929:4(702-715)Online publication date: Apr-2021
  • (2019)Exploiting Latency and Error Tolerance of GPGPU Applications for an Energy-Efficient DRAM2019 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)10.1109/DSN.2019.00046(362-374)Online publication date: Jun-2019
  • (2019)Understanding and Modeling On-Die Error Correction in Modern DRAM: An Experimental Study Using Real Devices2019 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)10.1109/DSN.2019.00017(13-25)Online publication date: Jun-2019
  • (2024)An Energy-Efficient Parallelism Scheme for Deep Neural Network Training And Inferencing on Heterogeneous Cloud ResourcesProceedings of the 2024 9th International Conference on Intelligent Information Technology10.1145/3654522.3654596(493-498)Online publication date: 23-Feb-2024
  • (2023)Locally-Adaptive Level-of-Detail for Hardware-Accelerated Ray TracingACM Transactions on Graphics10.1145/361835942:6(1-15)Online publication date: 5-Dec-2023
  • (2023)DRAM Bender: An Extensible and Versatile FPGA-Based Infrastructure to Easily Test State-of-the-Art DRAM ChipsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2023.328217242:12(5098-5112)Online publication date: Dec-2023
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