research-article

An empirical study of hot/cold data separation policies in solid state drives (SSDs)

Authors:

Jin-Soo KimAuthors Info & Claims

SYSTOR '13: Proceedings of the 6th International Systems and Storage Conference

Article No.: 12, Pages 1 - 6

https://doi.org/10.1145/2485732.2485745

Published: 30 June 2013 Publication History

Abstract

Separating hot data from cold data is known to allow for efficient management of NAND flash memory in Solid State Drives (SSDs). However, most of previous work has been evaluated with the trace-driven simulations under different workloads and testing conditions. The goal of this paper is to empirically study the performance, computation overhead, and memory consumption of the existing hot/cold data separation policies on a real SSD platform. After devising a general framework where a different policy can be easily plugged in, we have evaluated three hot/cold data separation policies: 2-level LRU (LRU), Multiple Bloom Filter (MBF), and Dynamic dAta Clustering (DAC). Our evaluation results show that DAC performs best, improving the performance by up to 58% in real workloads with a reasonable computation and memory overhead.

References

[1]

Jasmine OpenSSD Platform. http://www.openssd-project.org/wiki/Jasmine_OpenSSD_Platform/.

[2]

Transaction Processing Performance Council. http://www.tpc.org/tpcc/.

[3]

UMass Trace Repository. http://traces.cs.umass.edu/index.php/Storage/Storage.

[4]

N. Agrawal, V. Prabhakaran, T. Wobber, J. D. Davis, M. Manasse, and R. Panigrahy. Design tradeoffs for ssd performance. In Proc. Annual Technical Conference on Annual Technical Conference, pages 57--70, 2008.

Digital Library

[5]

L.-P. Chang and T.-W. Kuo. An adaptive striping architecture for flash memory storage systems of embedded systems. In Proc. Real-Time and Embedded Technology and Applications Symposium, pages 187--196, 2002.

Digital Library

[6]

M.-L. Chiang, P. C. H. Lee, and R.-C. Chang. Using data clustering to improve cleaning performance for flash memory. Software -- Practice & Experience, 29(3):267--290, March 1999.

Digital Library

[7]

CompactFlash Association. http://www.compactflash.org/.

[8]

A. Gupta, Y. Kim, and B. Urgaonkar. DFTL: A flash translation layer employing demand-based selective caching of page-level address mappings. In Proc. Conference on Architectural support for programming languages and operating systems, pages 229--240, February 2009.

Digital Library

[9]

J.-W. Hsieh, T.-W. Kuo, and L.-P. Chang. Efficient identification of hot data for flash memory storage systems. ACM Transactions on Storage, (1):22--40, February 2006.

Digital Library

[10]

X.-Y. Hu, E. Eleftheriou, R. Haas, I. Iliadis, and R. Pletka. Write amplification analysis in flash-based solid state drives. In Proc. Conference on Systems and Storage, 2009.

Digital Library

[11]

Intel Co. Understanding the flash translation layer (FTL) specification. http://developer.intel.com/.

[12]

D. Park. Hot data identification for flash-based storage systems using multiple bloom filters. In Proc. Mass Storage Systems and Technologies, pages 1--11, 2011.

Digital Library

[13]

M. Rosenblum and J. K. Ousterhout. The design and implementation of a log-structured file system. In Proc. SOSP, pages 1--15, October 1991.

Digital Library

[14]

Samsung Electronics Co. NAND flash memory & smartmedia data book, 2005.

[15]

Wikipedia. Write amplification. http://en.wikipedia.org/wiki/Write_amplification, 2010.

Cited By

Yao XLi QLin KGan XZhang JGao CShen ZXu QYang CXue J(2024)Extremely-Compressed SSDs with I/O Behavior PredictionACM Transactions on Storage10.1145/367704420:4(1-38)Online publication date: 16-Jul-2024
https://dl.acm.org/doi/10.1145/3677044
Li QDang HWan ZGao CYe MZhang JKuo TXue C(2024)Midas Touch: Invalid-Data Assisted Reliability and Performance Boost for 3d High-Density Flash2024 IEEE International Symposium on High-Performance Computer Architecture (HPCA)10.1109/HPCA57654.2024.00057(657-670)Online publication date: 2-Mar-2024
https://doi.org/10.1109/HPCA57654.2024.00057
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
Show More Cited By

Index Terms

An empirical study of hot/cold data separation policies in solid state drives (SSDs)
1. Software and its engineering
  1. Software organization and properties
    1. Contextual software domains
      1. Operating systems
        Memory management
        Secondary storage

Recommendations

A Multi-Stream-aware DRAM Allocation Strategy inside Solid-State Drives (SSDs)
RACS '23: Proceedings of the 2023 International Conference on Research in Adaptive and Convergent Systems

The modern NVMe SSDs have a multi-queue architecture to increase overall performance, where a submission queue can serve a stream from the host. Because of the asymmetry of read/write latency in NAND flash memory, the modern NVMe SSDs usually use the ...
Performance of garbage collection algorithms for flash-based solid state drives with hot/cold data

To avoid a poor random write performance, flash-based solid state drives typically rely on an internal log-structure. This log-structure reduces the write amplification and thereby improves the write throughput and extends the drive's lifespan. In this ...
An empirical study of redundant array of independent solid-state drives (RAIS)

Solid-state drives (SSD) are popular storage media devices alongside magnetic hard disk drives (HDD). SSD flash chips are packaged in HDD form factors and SSDs are compatible with regular HDD device drivers and I/O buses. This compatibility allows easy ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

SYSTOR '13: Proceedings of the 6th International Systems and Storage Conference

June 2013

198 pages

ISBN:9781450321167

DOI:10.1145/2485732

General Chair:
Ronen Kat
IBM Research
,
Program Chairs:
Mary Baker
HP Labs
,
Sivan Toledo
Tel Aviv University

Copyright © 2013 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

INTEL: Intel Corporation
Riverbed: Riverbed
NetApp
Technion: Israel Institute of Technology
Google Inc.
SAP
SIGOPS: ACM Special Interest Group on Operating Systems
EMC<sup>2</sup>: EMC<sup>2</sup>
AXCIENT: AXCIENT
USENIX Assoc: USENIX Assoc
IBM: IBM
HP: HP

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 30 June 2013

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Conference

SYSTOR '13

Sponsor:

INTEL
Riverbed
Technion
SIGOPS
EMC<sup>2</sup>
AXCIENT
USENIX Assoc
IBM
HP

SYSTOR '13: 6th Annual International Systems and Storage Conference

June 30 - July 2, 2013

Haifa, Israel

Acceptance Rates

SYSTOR '13 Paper Acceptance Rate 20 of 49 submissions, 41%;

Overall Acceptance Rate 108 of 323 submissions, 33%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

26
Total Citations
View Citations
924
Total Downloads

Downloads (Last 12 months)91
Downloads (Last 6 weeks)8

Reflects downloads up to 05 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Yao XLi QLin KGan XZhang JGao CShen ZXu QYang CXue J(2024)Extremely-Compressed SSDs with I/O Behavior PredictionACM Transactions on Storage10.1145/367704420:4(1-38)Online publication date: 16-Jul-2024
https://dl.acm.org/doi/10.1145/3677044
Li QDang HWan ZGao CYe MZhang JKuo TXue C(2024)Midas Touch: Invalid-Data Assisted Reliability and Performance Boost for 3d High-Density Flash2024 IEEE International Symposium on High-Performance Computer Architecture (HPCA)10.1109/HPCA57654.2024.00057(657-670)Online publication date: 2-Mar-2024
https://doi.org/10.1109/HPCA57654.2024.00057
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
Bergman SCassel NBjørling MSilberstein M(2023)ZNSwap: un-Block your SwapACM Transactions on Storage10.1145/358243419:2(1-25)Online publication date: 6-Mar-2023
https://dl.acm.org/doi/10.1145/3582434
Yu FYan H(2023)An Efficient Hot-Cold Data Separation Garbage Collection Algorithm Based on Logical Interval in NAND Flash-Based Consumer ElectronicsIEEE Transactions on Consumer Electronics10.1109/TCE.2022.322840469:3(431-440)Online publication date: 1-Aug-2023
https://dl.acm.org/doi/10.1109/TCE.2022.3228404
Litz HGonzalez JKlimovic AKozyrakis C(2022)RAIL: Predictable, Low Tail Latency for NVMe FlashACM Transactions on Storage10.1145/346540618:1(1-21)Online publication date: 29-Jan-2022
https://dl.acm.org/doi/10.1145/3465406
Yong HLee JKim J(2021)Design and Implementation of Virtual Stream Management for NAND Flash-Based StorageIEEE Transactions on Consumer Electronics10.1109/TCE.2021.306652467:2(149-157)Online publication date: May-2021
https://doi.org/10.1109/TCE.2021.3066524
Zhou YWang KWu FXie CLv H(2021)Seer-SSD: Bridging Semantic Gap between Log-Structured File Systems and SSDs to Reduce SSD Write Amplification2021 IEEE 39th International Conference on Computer Design (ICCD)10.1109/ICCD53106.2021.00020(49-56)Online publication date: Oct-2021
https://doi.org/10.1109/ICCD53106.2021.00020
Jeong JLee GLee JChoi JSong Y(2021)Buffer Management With Append-Only Data Isolation for Improving SSD PerformanceIEEE Access10.1109/ACCESS.2021.31302789(157681-157698)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3130278
Gwak HShin D(2021)SCJ: Segment Cleaning Journaling for Log-Structured File SystemsIEEE Access10.1109/ACCESS.2021.31214239(142437-142448)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3121423
Show More Cited By

View Options

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

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten