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When F2FS Meets Compression-Based SSD!

Published: 10 July 2023 Publication History

Abstract

Compression-based schemes have been widely studied to improve the lifetime and performance of solid-state drives (SSDs). Recently, the most popular flash-friendly file system (F2FS) started supporting compression to maximize the lifetime of NAND flash-based storage. Also, compression-based computational SSDs (CSDs) are developed due to their high performance, transparency, and easy adoption. This paper will first study the compression of F2FS and CSD to understand their features. Then, cooperative compression (COCO) is proposed to optimize performance and power consumption based on the combination of F2FS and CSD. Experiments on real devices show that COCO has encouraged optimization.

References

[1]
BTRFS compression. https://btrfs.wiki.kernel.org/index.php/Compression.
[2]
CSD3000 solid state drive. https://scaleflux.com/products/csd-3000/.
[3]
Data compression - intel. https://www.intel.com/support/ssdc/hpssd/sb/CS034293.htm.
[4]
F2FS compression. https://en.wikipedia.org/wiki/F2FS.
[5]
Fio: Flexible i/o tester. https://github.com/axboe/fio.
[6]
LSI durawrite data reduction. https://www.lsi.com/company/technology/duraclass/pages/durawrite.aspx.
[7]
Xubin Chen and Ning Zheng et al. Kallaxdb: A table-less hash-based key-value store on storage hardware with built-in transparent compression. In DaMoN, 2021.
[8]
Xiang Gao and Mingkai Dong et al. Erofs: A compression-friendly readonly file system for resource-scarce devices. In USENIX ATC, 2019.
[9]
MW Green. Pareto distributions, 1986.
[10]
Danny Harnik and Ronen Kat et al. To zip or not to zip: Effective resource usage for Real-Time compression. In 11th USENIX Conference on File and Storage Technologies (FAST 13), pages 229--241, San Jose, CA, February 2013. USENIX Association.
[11]
Martin Jambor and Tomas et al Hruby. Implementation of a linux log-structured file system with a garbage collector. SIGOPS Oper. Syst. Rev., 41(1):24--32, jan 2007.
[12]
Cheng Ji and Li-Pin Chang et al. Pattern-guided file compression with user-experience enhancement for log-structured file system on mobile devices. In FAST, 2021.
[13]
Juwon Kim and Minsu Kim et al. IPLFS: Log-structured file system without garbage collection. In USENIX ATC, 2022.
[14]
Changman Lee and Dongho Sim et al. F2FS: A new file system for flash storage. In FAST, 2015.
[15]
Junghee Lee and Youngjae et al. Kim. A semi-preemptive garbage collector for solid state drives. In (IEEE ISPASS) IEEE International Symposium on Performance Analysis of Systems and Software, pages 12--21, 2011.
[16]
Sungjin Lee and Jihoon Park et al. Improving performance and lifetime of solid-state drives using hardware-accelerated compression. IEEE TOCE, 2011.
[17]
Cangyuan Li and Ying Wang et al. GLIST: Towards in-storage graph learning. In USENIX ATC, 2021.
[18]
Qiao Li and Liang Shi et al. Improving ldpc performance via asymmetric sensing level placement on flash memory. In 2017 22nd Asia and South Pacific Design Automation Conference (ASP-DAC), pages 560--565, 2017.
[19]
Shengwen Liang and Ying Wang et al. Cognitive SSD: A deep learning engine for in-storage data retrieval. In USENIX ATC, 2019.
[20]
Yina Lv and Liang Shi et al. MGC: Multiple-gray-code for 3d nand flash based high-density ssds. In 2023 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pages 122--136, 2023.
[21]
Youngjo Park and Jin-Soo Kim et al. zftl: Power-efficient data compression support for NAND flash-based consumer electronics devices. IEEE TOCE, 2011.
[22]
Yifan Qiao and Xubin Chen et al. Improving relational database upon the arrival of storage hardware with built-in transparent compression. In IEEE NAS, 2021.
[23]
Yifan Qiao and Xubin Chen et al. Closing the b+-tree vs.LSM-tree write amplification gap on modern storage hardware with built-in transparent compression. In FAST, 2022.
[24]
Liang Shi and Kaijie Wu et al. Retention trimming for lifetime improvement of flash memory storage systems. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 35(1):58--71, 2016.
[25]
Yunpeng Song and Qiao et al. Li. Dwr: Differential wearing for read performance optimization on high-density nand flash memory. In 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE), pages 897--902, 2022.
[26]
Yunpeng Song and Yina et al. Lv. DECC: Differential ecc for read performance optimization on high-density nand flash memory. ASPDAC '23, page 104--109, New York, NY, USA, 2023. Association for Computing Machinery.
[27]
Jon Tate and Christian Burns et al. IBM Real-time Compression in IBM SAN Volume Controller and IBM Storwize V7000. IBM Redbooks, 2018.
[28]
Tarasov V. and Zadok E. et al. Filebench: A flexible framework for file system benchmarking. https://github.com/filebench/filebench.
[29]
Chao Wu and Cheng et al. Ji. Reinforcement learning based background segment cleaning for log-structured file system on mobile devices. In 2019 IEEE International Conference on Embedded Software and Systems (ICESS), pages 1--8, 2019.
[30]
Lihua Yang and Fang Wang et al. Ars: Reducing F2FS fragmentation for smartphones using decision trees. In DATE, 2020.
[31]
Aviad Zuck and Sivan Toledo et al. Compression and ssds: Where and how? In INFLOW, 2014.

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cover image ACM Conferences
HotStorage '23: Proceedings of the 15th ACM Workshop on Hot Topics in Storage and File Systems
July 2023
131 pages
ISBN:9798400702242
DOI:10.1145/3599691
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 the author(s) 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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Published: 10 July 2023

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Author Tags

  1. F2FS
  2. CSD
  3. compression
  4. power consumption

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  • NSFC
  • Shanghai Science and Technology Project

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Overall Acceptance Rate 34 of 87 submissions, 39%

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