research-article

Flikker: saving DRAM refresh-power through critical data partitioning

Authors:

Karthik Pattabiraman,

Thomas Moscibroda,

Benjamin G. ZornAuthors Info & Claims

ASPLOS XVI: Proceedings of the sixteenth international conference on Architectural support for programming languages and operating systems

Pages 213 - 224

https://doi.org/10.1145/1950365.1950391

Published: 05 March 2011 Publication History

Abstract

Energy has become a first-class design constraint in computer systems. Memory is a significant contributor to total system power. This paper introduces Flikker, an application-level technique to reduce refresh power in DRAM memories. Flikker enables developers to specify critical and non-critical data in programs and the runtime system allocates this data in separate parts of memory. The portion of memory containing critical data is refreshed at the regular refresh-rate, while the portion containing non-critical data is refreshed at substantially lower rates. This partitioning saves energy at the cost of a modest increase in data corruption in the non-critical data. Flikker thus exposes and leverages an interesting trade-off between energy consumption and hardware correctness. We show that many applications are naturally tolerant to errors in the non-critical data, and in the vast majority of cases, the errors have little or no impact on the application's final outcome. We also find that Flikker can save between 20-25% of the power consumed by the memory sub-system in a mobile device, with negligible impact on application performance. Flikker is implemented almost entirely in software, and requires only modest changes to the hardware.

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Index Terms

Flikker: saving DRAM refresh-power through critical data partitioning
1. Hardware
  1. Communication hardware, interfaces and storage
  2. Hardware test
    1. Memory test and repair

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cover image ACM Conferences

ASPLOS XVI: Proceedings of the sixteenth international conference on Architectural support for programming languages and operating systems

March 2011

432 pages

ISBN:9781450302661

DOI:10.1145/1950365

General Chair:
Rajiv Gupta
University of California, Riverside
,
Program Chair:
Todd C. Mowry
Carnegie Mellon University

ACM SIGARCH Computer Architecture News Volume 39, Issue 1
ASPLOS '11
March 2011
407 pages
ISSN:0163-5964
DOI:10.1145/1961295
Issue’s Table of Contents
ACM SIGPLAN Notices Volume 46, Issue 3
ASPLOS '11
March 2011
407 pages
ISSN:0362-1340
EISSN:1558-1160
DOI:10.1145/1961296
Issue’s Table of Contents

Copyright © 2011 ACM.

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Published: 05 March 2011

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March 5 - 11, 2011

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Cited By

Liu MFeng SShan WQue HWang JYang X(2025)A New Low-Power Circuit Design Optimization for Image ProcessingElectronics10.3390/electronics1402027714:2(277)Online publication date: 11-Jan-2025
https://doi.org/10.3390/electronics14020277
Kundu SRaha ABanerjee SNatarajan SBasu K(2023)Analysis and Mitigation of DRAM Faults in Sparse-DNN AcceleratorsIEEE Design & Test10.1109/MDAT.2022.318354540:2(90-99)Online publication date: Apr-2023
https://doi.org/10.1109/MDAT.2022.3183545
Ki SByun GCho KBahn H(2023)Co-Optimizing CPU Voltage, Memory Placement, and Task Offloading for Energy-Efficient Mobile SystemsIEEE Internet of Things Journal10.1109/JIOT.2022.323383010:10(9177-9192)Online publication date: 15-May-2023
https://doi.org/10.1109/JIOT.2022.3233830
Nam SBahn H(2023)Adaptive Swapping for Variable Workloads in Real-time Task Scheduling2023 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI)10.1109/CCCI58712.2023.10290800(1-6)Online publication date: 18-Oct-2023
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Saraswat AAbhishek KAzad HShitharth S(2023)MSI-A: An Energy Efficient Approximated Cache Coherence ProtocolIEEE Access10.1109/ACCESS.2023.327321911(48123-48135)Online publication date: 2023
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Isquierdo MSoares RSampaio FZatt BPalomino D(2023)VVC decoder intra prediction using approximate storage: an error resilience evaluationAnalog Integrated Circuits and Signal Processing10.1007/s10470-023-02189-1117:1-3(95-111)Online publication date: 21-Oct-2023
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Giardino MSchwyn DFerri BFerri A(2022)Low-Overhead Reinforcement Learning-Based Power Management Using 2QoSMJournal of Low Power Electronics and Applications10.3390/jlpea1202002912:2(29)Online publication date: 19-May-2022
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