research-article

Free access

Impact of Data Locality on Garbage Collection in SSDs: A General Analytical Study

Authors:

Patrick P.C. Lee,

Yinlong XuAuthors Info & Claims

ICPE '15: Proceedings of the 6th ACM/SPEC International Conference on Performance Engineering

Pages 305 - 315

https://doi.org/10.1145/2668930.2688036

Published: 31 January 2015 Publication History

Abstract

Solid-state drives (SSDs) necessitate garbage collection (GC) to erase data blocks and reclaim the space of invalidated data, and GC inevitably introduces additional writes due to data relocation. The performance of GC, which is quantified by cleaning cost or write amplification, is critical to the overall performance of SSDs. However, characterizing GC performance is complicated by the general implementations of GC algorithms and the complex data locality characteristics of real-world workloads. This paper presents a general analytical study to characterize the performance impact of data locality on a general family of GC algorithms. We develop probabilistic models to address two fundamental issues: (1) What is the impact of data locality on the performance of locality-oblivious GC? (2) How can data locality be leveraged to improve the performance in locality-aware GC? We further conduct extensive trace-driven simulations on real-world workloads to validate the findings of our models.

References

[1]

N. Agrawal, V. Prabhakaran, T. Wobber, J. D. Davis, M. Manasse, and R. Panigrahy. Design Tradeoffs for SSD Performance. In Proc. of USENIX ATC, Jun 2008.

Digital Library

[2]

A. Birrell, M. Isard, C. Thacker, and T. Wobber. A Design for High-performance Flash Disks. ACM SIGOPS Oper. Syst. Rev., 41(2):88--93, Apr 2007.

Digital Library

[3]

W. Bux and I. Iliadis. Performance of Greedy Garbage Collection in Flash-based Solid-state Drives. Performance Evaluation, Nov 2010.

Digital Library

[4]

F. Chen, D. A. Koufaty, and X. Zhang. Understanding Intrinsic Characteristics and System Implications of Flash Memory based Solid State Drives. In Proc. of ACM SIGMETRICS, Jun 2009.

Digital Library

[5]

F. Chen, T. Luo, and X. Zhang. CAFTL: A Content-aware Flash Translation Layer Enhancing the Lifespan of Flash Memory Based Solid State Drives. In Proceedings of USENIX, FAST, 2011.

Digital Library

[6]

T.-S. Chung, D.-J. Park, S. Park, D.-H. Lee, S.-W. Lee, and H.-J. Song. System Software For Flash Memory: A Survey. In Proc. of Int. Conf. on Embedded and Ubiquitous Computing, Aug 2006.

Digital Library

[7]

P. Desnoyers. Analytic Modeling of SSD Write Performance. In Proceedings of SYSTOR, Jun 2012.

Digital Library

[8]

E. Gal and S. Toledo. Algorithms and Data Structures for Flash Memories. ACM Computing Surveys, 37(2):138--163, Jun 2005.

Digital Library

[9]

A. Gupta, Y. Kim, and B. Urgaonkar. DFTL: A Flash Translation Layer Employing Demand-based Selective Caching of Page-level Address Mappings. In Proc. of ACM ASPLOS, Mar 2009.

Digital Library

[10]

A. Gupta, R. Pisolkar, B. Urgaonkar, and A. Sivasubramaniam. Leveraging Value Locality in Optimizing NAND Flash-based SSDs. In Proc. of USENI FAST, 2011.

Digital Library

[11]

J.-W. Hsieh, T.-W. Kuo, and L.-P. Chang. Efficient Identification of Hot Data for Flash Memory Storage Systems. ACM TOS, Feb 2006.

Digital Library

[12]

X.-Y. Hu, E. Eleftheriou, R. Haas, I. Iliadis, and R. Pletka. Write Amplification Analysis in Flash-based Solid State Drives. In Proc. of SYSTOR, May 2009.

Digital Library

[13]

M. Jung and M. Kandemir. Revisiting Widely Held SSD Expectations and Rethinking System-level Implications. In Proc. of ACM SIGMETRICS, Jun 2013.

Digital Library

[14]

H.-S. Lee, H.-S. Yun, and D.-H. Lee. HFTL: Hybrid Flash Translation Layer based on Hot Data Identification for Flash Memory. IEEE Trans. on Consumer Electronics, 55(4):2005--2011, 2009.

Digital Library

[15]

S.-W. Lee, D.-J. Park, T.-S. Chung, D.-H. Lee, S. Park, and H.-J. Song. A Log Buffer-based Flash Translation Layer Using Fully-associative Sector Translation. ACM TECS, 6(3), Jul 2007.

Digital Library

[16]

Y. Li, P. P. C. Lee, and J. C. S. Lui. Stochastic Analysis on RAID Reliability for Solid-State Drives. In Proc. of IEEE SRDS, 2013.

Digital Library

[17]

Y. Li, P. P. C. Lee, and J. C. S. Lui. Stochastic Modeling of Large-Scale Solid-State Storage Systems: Analysis, Design Tradeoffs and Optimization. In Proc. of ACM SIGMETRICS, 2013.

Digital Library

[18]

Y. Lu, J. Shu, and W. Zheng. Extending the Lifetime of Flash-based Storage through Reducing Write Amplification from File Systems. In Proc. of USENIX FAST, 2013.

Digital Library

[19]

Micron Technology. Bad Block Management in NAND Flash Memory. Technical Note, TN-29-59, 2011.

[20]

D. Narayanan, A. Donnelly, and A. Rowstron. Write off-loading: Practical power management for enterprise storage. ACM TOS, 4(3):10:1--10:23, Nov 2008.

Digital Library

[21]

C. Park, W. Cheon, J. Kang, K. Roh, W. Cho, and J.-S. Kim. A Reconfigurable FTL (Flash Translation Layer) Architecture for NAND Flash-based Applications. ACM TECS, 7(4):38:1--38:23, Aug 2008.

Digital Library

[22]

Z. Qin, Y. Wang, D. Liu, and Z. Shao. Demand-based Block-level Address Mapping in Large-scale NAND Flash Storage Systems. In Proc. of IEEE/ACM/IFIP CODES+ISSS, Oct 2010.

Digital Library

[23]

M. Rosenblum and J. K. Ousterhout. The Design and Implementation of a Log-structured File System. ACM Trans. Comput. Syst., 10(1):26--52, Feb 1992.

Digital Library

[24]

A. Soga, C. Sun, and K. Takeuchi. NAND Flash Aware Data Management System for High-speed SSDs by Garbage Collection Overhead Suppression. In IEEE 6th International Memory Workshop (IMW), May 2014.

[25]

Storage Performance Council. http://traces.cs.umass.edu/index.php/Storage/Storage, 2002.

[26]

B. Van Houdt. A Mean Field Model for a Class of Garbage Collection Algorithms in Flash-based Solid State Drives. In Proc. of ACM SIGMETRICS, Jun 2013.

Digital Library

[27]

B. Van Houdt. Performance of Garbage Collection Algorithms for Flash-based Solid State Drives with Hot/cold Data. Performance Evaluation, 70(10):692--703, Sep 2013.

Digital Library

[28]

A. Verma, R. Koller, L. Useche, and R. Rangaswami. SRCMap: Energy Proportional Storage using Dynamic Consolidation. In Proc. of USENIX FAST, Feb 2010.

Digital Library

[29]

Y. Yang and J. Zhu. Analytical Modeling of Garbage Collection Algorithms in Hotness-aware Flash-based Solid State Drives. In Proc. of IEEE MSST, June 2014.

Cited By

Hsu YWu CTsai YLiu C(2023)A Granularity-Based Clustering Method for Reducing Write Amplification in Solid-State DrivesACM Transactions on Embedded Computing Systems10.1145/360577922:4(1-32)Online publication date: 24-Jul-2023
https://dl.acm.org/doi/10.1145/3605779
Kim JChoi KLee WKim J(2021)Performance Modeling and Practical Use Cases for Black-Box SSDsACM Transactions on Storage10.1145/344002217:2(1-38)Online publication date: 8-Jun-2021
https://dl.acm.org/doi/10.1145/3440022
Chen TChi SYang MChien T(2021)Enabling the Duo-phase Data Management to Realize Longevity Bit-alterable Flash MemoryIEEE Transactions on Computers10.1109/TC.2021.3116862(1-1)Online publication date: 2021
https://doi.org/10.1109/TC.2021.3116862
Show More Cited By

Index Terms

Impact of Data Locality on Garbage Collection in SSDs: A General Analytical Study

Recommendations

Profile-guided proactive garbage collection for locality optimization
PLDI '06: Proceedings of the 27th ACM SIGPLAN Conference on Programming Language Design and Implementation

Many applications written in garbage collected languages have large dynamic working sets and poor data locality. We present a new system for continuously improving program data locality at run time with low overhead. Our system proactively reorganizes ...
Profile-guided proactive garbage collection for locality optimization
Proceedings of the 2006 PLDI Conference

Many applications written in garbage collected languages have large dynamic working sets and poor data locality. We present a new system for continuously improving program data locality at run time with low overhead. Our system proactively reorganizes ...
Age-based garbage collection
OOPSLA '99: Proceedings of the 14th ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications

Modern generational garbage collectors look for garbage among the young objects, because they have high mortality; however, these objects include the very youngest objects, which clearly are still live. We introduce new garbage collection algorithms, ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

ICPE '15: Proceedings of the 6th ACM/SPEC International Conference on Performance Engineering

January 2015

366 pages

ISBN:9781450332484

DOI:10.1145/2668930

General Chairs:
Lizy K. John
UT Austin, USA
,
Connie U. Smith
L&S Computer Technology, Inc., USA
,
Program Chairs:
Kai Sachs
SAP SE, Germany
,
Catalina M. Lladó
University of the Balearic Islands, Spain

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]

Sponsors

SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
SIGSOFT: ACM Special Interest Group on Software Engineering
SPEC: SPEC Research Group

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 31 January 2015

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

The Fundamental Research Funds for the Central Universities
National Nature Science Foundation of China

Conference

ICPE'15

Sponsor:

ICPE'15: ACM/SPEC International Conference on Performance Engineering

January 28 - February 4, 2015

Texas, Austin, USA

Acceptance Rates

ICPE '15 Paper Acceptance Rate 23 of 74 submissions, 31%;

Overall Acceptance Rate 252 of 851 submissions, 30%

Upcoming Conference

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

13
Total Citations
View Citations
397
Total Downloads

Downloads (Last 12 months)83
Downloads (Last 6 weeks)20

Reflects downloads up to 03 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Hsu YWu CTsai YLiu C(2023)A Granularity-Based Clustering Method for Reducing Write Amplification in Solid-State DrivesACM Transactions on Embedded Computing Systems10.1145/360577922:4(1-32)Online publication date: 24-Jul-2023
https://dl.acm.org/doi/10.1145/3605779
Kim JChoi KLee WKim J(2021)Performance Modeling and Practical Use Cases for Black-Box SSDsACM Transactions on Storage10.1145/344002217:2(1-38)Online publication date: 8-Jun-2021
https://dl.acm.org/doi/10.1145/3440022
Chen TChi SYang MChien T(2021)Enabling the Duo-phase Data Management to Realize Longevity Bit-alterable Flash MemoryIEEE Transactions on Computers10.1109/TC.2021.3116862(1-1)Online publication date: 2021
https://doi.org/10.1109/TC.2021.3116862
Pei SYang JLi B(2021)Edges: Evenly Distributing Garbage-Collections for Enterprise SSDs via Stochastic Optimization2021 IEEE International Conference on Networking, Architecture and Storage (NAS)10.1109/NAS51552.2021.9605402(1-4)Online publication date: Oct-2021
https://doi.org/10.1109/NAS51552.2021.9605402
Kim SSon Y(2021)Optimizing Key-Value Stores for Flash-Based SSDs via Key ReshapingIEEE Access10.1109/ACCESS.2021.31054289(115135-115144)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3105428
Li YChan HLee PXu Y(2019)Enabling Efficient Updates in KV Storage via HashingACM Transactions on Storage10.1145/334028715:3(1-29)Online publication date: 13-Aug-2019
https://dl.acm.org/doi/10.1145/3340287
Liu CKotra JJung MKandemir MAgrawal NRangaswami R(2018)PENProceedings of the 16th USENIX Conference on File and Storage Technologies10.5555/3189759.3189766(67-82)Online publication date: 12-Feb-2018
https://dl.acm.org/doi/10.5555/3189759.3189766
Kim JPark PAhn JKim JKim JKim JOskin MInoue K(2018)SSDcheckProceedings of the 51st Annual IEEE/ACM International Symposium on Microarchitecture10.1109/MICRO.2018.00044(455-468)Online publication date: 20-Oct-2018
https://dl.acm.org/doi/10.1109/MICRO.2018.00044
Shahidi NKandemir M(2018)CachedGC: Cache-Assisted Garbage Collection in Modern Solid State Drives2018 IEEE 26th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)10.1109/MASCOTS.2018.00015(79-86)Online publication date: Sep-2018
https://doi.org/10.1109/MASCOTS.2018.00015
Park CLee SWon YAhn SBinder WCortellessa VKoziolek ASmirni EPoess M(2017)Practical Implication of Analytical Models for SSD Write AmplificationProceedings of the 8th ACM/SPEC on International Conference on Performance Engineering10.1145/3030207.3030219(257-262)Online publication date: 17-Apr-2017
https://dl.acm.org/doi/10.1145/3030207.3030219
Show More Cited By

View Options

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Figures

Tables

Media

View Table of Conten