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LPCA: learned MRC profiling based cache allocation for file storage systems

Authors:

Zhuo ChengAuthors Info & Claims

DAC '22: Proceedings of the 59th ACM/IEEE Design Automation Conference

Pages 511 - 516

https://doi.org/10.1145/3489517.3530662

Published: 23 August 2022 Publication History

Abstract

File storage system (FSS) uses multi-caches to accelerate data accesses. Unfortunately, efficient FSS cache allocation remains extremely difficult. First, as the key of cache allocation, existing miss ratio curve (MRC) constructions are limited to LRU. Second, existing techniques are suitable for same-layer caches but not for hierarchical ones.

We present a Learned MRC Profiling based Cache Allocation (LPCA) scheme for FSS. To the best of our knowledge, LPCA is the first to apply machine learning to model MRC under non-LRU, LPCA also explores optimization target for hierarchical caches, in that LPCA can provide universal and efficient cache allocation for FSSs.

References

[1]

George Almási et al. 2002. Calculating stack distances efficiently. In Proceedings of the 2002 workshop on Memory system performance. 37--43.

[2]

Asaf Cidon et al. 2017. Memshare: a Dynamic Multi-tenant Key-value Cache. In ATC 17. USENIX Association, Santa Clara, CA, 321--334.

[3]

Nosayba El-Sayed et al. 2018. KPart: A Hybrid Cache Partitioning-Sharing Technique for Commodity Multicores. In 2018 HPCA. 104--117.

[4]

Ajay Gulati et al. 2012. Demand Based Hierarchical QoS Using Storage Resource Pools. In ATC 12. USENIX Association, Boston, MA, 1--13.

[5]

Xiameng Hu et al. 2016. Kinetic Modeling of Data Eviction in Cache. In ATC 16. USENIX Association, Denver, CO, 351--364.

[6]

Theodore Johnson et al. 1994. 2Q: A Low Overhead High Performance Buffer Management Replacement Algorithm. In VLDB. 439--450.

[7]

Zaoxing Liu et al. 2019. DistCache: Provable Load Balancing for Large-Scale Storage Systems with Distributed Caching. In FAST 19. USENIX Association, Boston, MA, 143--157.

[8]

R.L. Mattson et al. 1970. Evaluation techniques for storage hierarchies. IBM Systems Journal 9, 2 (1970), 78--117.

Digital Library

[9]

Nimrod Megiddo et al. 2003. ARC: A Self-Tuning, Low Overhead Replacement Cache. In FAST 03. USENIX Association, San Francisco, CA.

[10]

Sparsh Mittal. 2017. A survey of techniques for cache partitioning in multicore processors. ACM Computing Surveys (CSUR) 50, 2 (2017), 1--39.

Digital Library

[11]

Qingpeng Niu et al. 2012. PARDA: A Fast Parallel Reuse Distance Analysis Algorithm. In IPDPS. 1284--1294.

[12]

Stuart J. Russell et al. 2003. Artificial intelligence - a modern approach, 2nd Edition. In Prentice Hall series in artificial intelligence.

[13]

SNIA. [n. d.]. SNIA iotta repository block I/O traces. http://iotta.snia.org/tracetypes/3.

[14]

JianTanet al. 2018. On resource pooling and separation for LRU caching. POMACS 2, 1 (2018), 1--31.

[15]

Carl Waldspurger et al. 2017. Cache Modeling and Optimization using Miniature Simulations. In ATC 17. USENIX Association, Santa Clara, CA, 487--498.

[16]

Carl A. Waldspurger et al. 2015. Efficient MRC Construction with SHARDS. In FAST 15. USENIX Association, Santa Clara, CA, 95--110.

[17]

Jake Wires et al. 2014. Characterizing Storage Workloads with Counter Stacks. In OSDI 14. USENIX Association, Broomfield, CO, 335--349.

[18]

Juncheng Yang et al. 2020. A large scale analysis of hundreds of in-memory cache clusters at Twitter. In OSDI 20. USENIX Association, 191--208.

[19]

Y. Yasuda et al. 2003. Concept and evaluation of X-NAS: a highly scalable NAS system. In MSST 2003. 219--227.

[20]

Yu Zhang et al. 2020. OSCA: An Online-Model Based Cache Allocation Scheme in Cloud Block Storage Systems. In ATC 20. USENIX Association, 785--798.

Cited By

Guo XWang HZhou KJiang HHan YXing G(2024)FLOWS: Balanced MRC Profiling for Heterogeneous Object-Size CacheProceedings of the Nineteenth European Conference on Computer Systems10.1145/3627703.3650078(421-440)Online publication date: 22-Apr-2024
https://dl.acm.org/doi/10.1145/3627703.3650078
Wang PLiu YLiu ZZhao ZLiu KZhou KHuang Z(2024)-LAP: A Lightweight and Adaptive Cache Partitioning Scheme With Prudent Resizing Decisions for Content Delivery NetworksIEEE Transactions on Cloud Computing10.1109/TCC.2024.342045412:3(942-953)Online publication date: Jul-2024
https://doi.org/10.1109/TCC.2024.3420454

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cover image ACM Conferences

DAC '22: Proceedings of the 59th ACM/IEEE Design Automation Conference

July 2022

1462 pages

ISBN:9781450391429

DOI:10.1145/3489517

General Chair:
Rob Oshana
NXP

Copyright © 2022 ACM.

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SIGDA: ACM Special Interest Group on Design Automation
IEEE CEDA

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 August 2022

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National Natural Science Foundation of China

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DAC '22

Sponsor:

SIGDA

DAC '22: 59th ACM/IEEE Design Automation Conference

July 10 - 14, 2022

California, San Francisco

Acceptance Rates

Overall Acceptance Rate 1,770 of 5,499 submissions, 32%

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DAC '25

Sponsor:
sigda

62nd ACM/IEEE Design Automation Conference

June 22 - 26, 2025

San Francisco , CA , USA

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Cited By

Guo XWang HZhou KJiang HHan YXing G(2024)FLOWS: Balanced MRC Profiling for Heterogeneous Object-Size CacheProceedings of the Nineteenth European Conference on Computer Systems10.1145/3627703.3650078(421-440)Online publication date: 22-Apr-2024
https://dl.acm.org/doi/10.1145/3627703.3650078
Wang PLiu YLiu ZZhao ZLiu KZhou KHuang Z(2024)-LAP: A Lightweight and Adaptive Cache Partitioning Scheme With Prudent Resizing Decisions for Content Delivery NetworksIEEE Transactions on Cloud Computing10.1109/TCC.2024.342045412:3(942-953)Online publication date: Jul-2024
https://doi.org/10.1109/TCC.2024.3420454

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