research-article

Optimal Data Placement for Heterogeneous Cache, Memory, and Storage Systems

Authors:

Ymir VigfussonAuthors Info & Claims

Proceedings of the ACM on Measurement and Analysis of Computing Systems, Volume 4, Issue 1

Article No.: 06, Pages 1 - 27

https://doi.org/10.1145/3379472

Published: 27 May 2020 Publication History

Abstract

New memory technologies are blurring the previously distinctive performance characteristics of adjacent layers in the memory hierarchy. No longer are such layers orders of magnitude different in request latency or capacity. Beyond the traditional single-layer view of caching, we now must re-cast the problem as a data placement challenge: which data should be cached in faster memory if it could instead be served directly from slower memory? We present CHOPT, an offline algorithm for data placement across multiple tiers of memory with asymmetric read and write costs. We show that CHOPT is optimal and can therefore serve as the upper bound of performance gain for any data placement algorithm. We also demonstrate an approximation of CHOPT which makes its execution time for long traces practical using spatial sampling of requests incurring a small 0.2% average error on representative workloads at a sampling ratio of 1%. Our evaluation of CHOPT on more than 30 production traces and benchmarks shows that optimal data placement decisions could improve average request latency by 8.2%-44.8% when compared with the long-established gold standard: Belady and Mattson's offline, evict-farthest-in-the-future optimal algorithms. Our results identify substantial improvement opportunities for future online memory management research.

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cover image Proceedings of the ACM on Measurement and Analysis of Computing Systems

Proceedings of the ACM on Measurement and Analysis of Computing Systems Volume 4, Issue 1

SIGMETRICS

March 2020

467 pages

EISSN:2476-1249

DOI:10.1145/3402934

Editors:
Augustin Chaintreau
Columbia University
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Leana Golubchik
University of Southern California
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Zhi-Li Zhang
University of Minnesota

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Published: 27 May 2020

Online AM: 07 May 2020

Published in POMACS Volume 4, Issue 1

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https://dl.acm.org/doi/10.1145/3665926
Karimov EEvenblij TChamazcoti SCatthoor F(2025)PARL: Page Allocation in hybrid main memory using Reinforcement LearningJournal of Systems Architecture10.1016/j.sysarc.2024.103310159(103310)Online publication date: Feb-2025
https://doi.org/10.1016/j.sysarc.2024.103310
Ait-Oucheggou LRubini SBattou ABoukhobza J(2025)QM-ARC: QoS-aware Multi-tier Adaptive Cache Replacement StrategyFuture Generation Computer Systems10.1016/j.future.2024.107548163(107548)Online publication date: Feb-2025
https://doi.org/10.1016/j.future.2024.107548
Shang JWu ZXiao ZZhang YWang J(2024)BERT4Cache: a bidirectional encoder representations for data prefetching in cachePeerJ Computer Science10.7717/peerj-cs.225810(e2258)Online publication date: 29-Aug-2024
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