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MemScale: active low-power modes for main memory

Authors:

Thomas F. Wenisch,

Ricardo BianchiniAuthors Info & Claims

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

Pages 225 - 238

https://doi.org/10.1145/1950365.1950392

Published: 05 March 2011 Publication History

Abstract

Main memory is responsible for a large and increasing fraction of the energy consumed by servers. Prior work has focused on exploiting DRAM low-power states to conserve energy. However, these states require entire DRAM ranks to be idled, which is difficult to achieve even in lightly loaded servers. In this paper, we propose to conserve memory energy while improving its energy-proportionality by creating active low-power modes for it. Specifically, we propose MemScale, a scheme wherein we apply dynamic voltage and frequency scaling (DVFS) to the memory controller and dynamic frequency scaling (DFS) to the memory channels and DRAM devices. MemScale is guided by an operating system policy that determines the DVFS/DFS mode of the memory subsystem based on the current need for memory bandwidth, the potential energy savings, and the performance degradation that applications are willing to withstand. Our results demonstrate that MemScale reduces energy consumption significantly compared to modern memory energy management approaches. We conclude that the potential benefits of the MemScale mechanisms and policy more than compensate for their small hardware cost.

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Chen JManivannan MGoel BPericàs M(2024)SWEEP: Adaptive Task Scheduling for Exploring Energy Performance Trade-offs2024 IEEE International Parallel and Distributed Processing Symposium (IPDPS)10.1109/IPDPS57955.2024.00036(325-336)Online publication date: 27-May-2024
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Index Terms

MemScale: active low-power modes for main memory
1. Computer systems organization

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MemScale: active low-power modes for main memory
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Main memory is responsible for a large and increasing fraction of the energy consumed by servers. Prior work has focused on exploiting DRAM low-power states to conserve energy. However, these states require entire DRAM ranks to be idled, which is ...
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Main memory accounts for a growing fraction of server energy usage. Investigating active low-power modes for managing main memory, with a system called MemScale, the authors offer a solution for performance-aware energy management. By creating a set of ...

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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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Chen JManivannan MGoel BPericàs M(2024)SWEEP: Adaptive Task Scheduling for Exploring Energy Performance Trade-offs2024 IEEE International Parallel and Distributed Processing Symposium (IPDPS)10.1109/IPDPS57955.2024.00036(325-336)Online publication date: 27-May-2024
https://doi.org/10.1109/IPDPS57955.2024.00036
Chen JManivannan MGoel BPericàs M(2023)JOSS: Joint Exploration of CPU-Memory DVFS and Task Scheduling for Energy EfficiencyProceedings of the 52nd International Conference on Parallel Processing10.1145/3605573.3605586(828-838)Online publication date: 7-Aug-2023
https://dl.acm.org/doi/10.1145/3605573.3605586
Oliveira GGhose SGómez-Luna JBoroumand ASavery ARao SQazi SGrignou GThakur RShiu EMutlu O(2023)Extending Memory Capacity in Modern Consumer Systems With Emerging Non-Volatile Memory: Experimental Analysis and Characterization Using the Intel Optane SSDIEEE Access10.1109/ACCESS.2023.331788411(105843-105871)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3317884
Muralidhar RBorovica-Gajic RBuyya R(2022)Energy Efficient Computing Systems: Architectures, Abstractions and Modeling to Techniques and StandardsACM Computing Surveys10.1145/351109454:11s(1-37)Online publication date: 9-Sep-2022
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