research-article

Scaling the Memory Power Wall With DRAM-Aware Data Management

Authors:

Raja Appuswamy,

Matthaios Olma,

Anastasia AilamakiAuthors Info & Claims

DaMoN'15: Proceedings of the 11th International Workshop on Data Management on New Hardware

Article No.: 3, Pages 1 - 9

https://doi.org/10.1145/2771937.2771947

Published: 31 May 2015 Publication History

Abstract

Improving the energy efficiency of database systems has emerged as an important topic of research over the past few years. While significant attention has been paid to optimizing the power consumption of tradition disk-based databases, little attention has been paid to the growing cost of DRAM power consumption in main-memory databases (MMDB).

In this paper, we bridge this divide by examining power--performance tradeoffs involved in designing MMDBs. In doing so, we first show how DRAM will soon emerge as the dominating source of power consumption in emerging MMDB servers unlike traditional database servers, where CPU power consumption overshadows that of DRAM. Second, we show that using DRAM frequency scaling and power-down modes can provide substantial improvement in performance/Watt under both transactional and analytical workloads. This, again contradicts rules of thumb established for traditional servers, where the most energy-efficient configuration is often the one with highest performance.

Based on our observations, we argue that the long-overlooked task of optimizing DRAM power consumption should henceforth be considered a first-class citizen in designing MMDBs. In doing so, we highlight several promising research directions and identify key design challenges that must be overcome towards achieving this goal.

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Cited By

Guo BWu JPu YZhang JYu J(2024)Energy consumption estimation and profiling for queries in distributed database systems based on a bottom-up comprehensive energy modelFuture Generation Computer Systems10.1016/j.future.2024.04.059159:C(379-394)Online publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1016/j.future.2024.04.059
Jin WJang WPark HLee JKim SLee JSolihin YHeinrich M(2023)DRAM Translation Layer: Software-Transparent DRAM Power Savings for Disaggregated MemoryProceedings of the 50th Annual International Symposium on Computer Architecture10.1145/3579371.3589051(1-13)Online publication date: 17-Jun-2023
https://dl.acm.org/doi/10.1145/3579371.3589051
Dembele SBellatreche LLorusso AMarongiu FSantaniello D(2023)In-Memory Database Query Energy Estimation: Modeling & Green Strategy Support2023 IEEE World Conference on Applied Intelligence and Computing (AIC)10.1109/AIC57670.2023.10263900(278-285)Online publication date: 29-Jul-2023
https://doi.org/10.1109/AIC57670.2023.10263900
Show More Cited By

Index Terms

Scaling the Memory Power Wall With DRAM-Aware Data Management
1. Hardware
  1. Integrated circuits
    1. Semiconductor memory
      1. Dynamic memory
2. Information systems
  1. Data management systems
    1. Database management system engines

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cover image ACM Conferences

DaMoN'15: Proceedings of the 11th International Workshop on Data Management on New Hardware

May 2015

100 pages

ISBN:9781450336383

DOI:10.1145/2771937

Copyright © 2015 ACM.

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]

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SIGMOD: ACM Special Interest Group on Management of Data

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New York, NY, United States

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Published: 31 May 2015

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SIGMOD/PODS'15: International Conference on Management of Data

May 31 - June 4, 2015

VIC, Melbourne, Australia

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DaMoN'15 Paper Acceptance Rate 12 of 16 submissions, 75%;

Overall Acceptance Rate 94 of 127 submissions, 74%

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Cited By

Guo BWu JPu YZhang JYu J(2024)Energy consumption estimation and profiling for queries in distributed database systems based on a bottom-up comprehensive energy modelFuture Generation Computer Systems10.1016/j.future.2024.04.059159:C(379-394)Online publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1016/j.future.2024.04.059
Jin WJang WPark HLee JKim SLee JSolihin YHeinrich M(2023)DRAM Translation Layer: Software-Transparent DRAM Power Savings for Disaggregated MemoryProceedings of the 50th Annual International Symposium on Computer Architecture10.1145/3579371.3589051(1-13)Online publication date: 17-Jun-2023
https://dl.acm.org/doi/10.1145/3579371.3589051
Dembele SBellatreche LLorusso AMarongiu FSantaniello D(2023)In-Memory Database Query Energy Estimation: Modeling & Green Strategy Support2023 IEEE World Conference on Applied Intelligence and Computing (AIC)10.1109/AIC57670.2023.10263900(278-285)Online publication date: 29-Jul-2023
https://doi.org/10.1109/AIC57670.2023.10263900
Lannelongue LAronson HBateman ABirney ECaplan TJuckes MMcEntyre JMorris AReilly GInouye M(2023)GREENER principles for environmentally sustainable computational scienceNature Computational Science10.1038/s43588-023-00461-y3:6(514-521)Online publication date: 26-Jun-2023
https://doi.org/10.1038/s43588-023-00461-y
Guo BYu JYang DLeng HLiao B(2022)Energy-Efficient Database Systems: A Systematic SurveyACM Computing Surveys10.1145/353822555:6(1-53)Online publication date: 7-Dec-2022
https://dl.acm.org/doi/10.1145/3538225
Lee DWon YPark YLee SHung CCerny TShin DBechini A(2020)Two-tier garbage collection for persistent objectProceedings of the 35th Annual ACM Symposium on Applied Computing10.1145/3341105.3373986(1246-1255)Online publication date: 30-Mar-2020
https://dl.acm.org/doi/10.1145/3341105.3373986
Karyakin ASalem K(2019)DimmStoreProceedings of the VLDB Endowment10.14778/3342263.3342262912:11(1499-1512)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.14778/3342263.33422629
Appuswamy RGraefe GBorovica-Gajic RAilamaki A(2019)The five-minute rule 30 years later and its impact on the storage hierarchyCommunications of the ACM10.1145/331816362:11(114-120)Online publication date: 24-Oct-2019
https://dl.acm.org/doi/10.1145/3318163
Zhao YLiu YLi WChen M(2019)HCMA: Supporting High Concurrency of Memory Accesses with Scratchpad Memory in FPGAs2019 IEEE International Conference on Networking, Architecture and Storage (NAS)10.1109/NAS.2019.8834726(1-8)Online publication date: Aug-2019
https://doi.org/10.1109/NAS.2019.8834726
Korkmaz MKarsten MSalem KSalihoglu SDas GJermaine CBernstein P(2018)Workload-Aware CPU Performance Scaling for Transactional Database SystemsProceedings of the 2018 International Conference on Management of Data10.1145/3183713.3196901(291-306)Online publication date: 27-May-2018
https://dl.acm.org/doi/10.1145/3183713.3196901
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