research-article

Stable Greedy: Adaptive Garbage Collection for Durable Page-Mapping Multichannel SSDs

Authors:

Wen-Huei LinAuthors Info & Claims

ACM Transactions on Embedded Computing Systems (TECS), Volume 15, Issue 1

Article No.: 13, Pages 1 - 25

https://doi.org/10.1145/2820613

Published: 13 January 2016 Publication History

Abstract

Commodity solid state drives (SSDs) have recently begun involving the adoption of powerful controllers for multichannel flash management at the page level. However, many of these models still use primitive garbage-collection algorithms, because previous approaches are subject to poor scalability with high-capacity flash memory. This study presents Stable Greedy for garbage collection in page-mapping multichannel SSDs. Stable Greedy identifies page-accurate data hotness using block-level information, and jointly considers block space utilization and block stability for victim selection. Its design considers flash wear leveling for SSD lifetime enhancement at the block level as well as at the channel level. Stable Greedy runs at a constant time, and requires limited RAM space. The simulation results revealed that Stable Greedy outperformed previous methods considerably under various workloads and multichannel architectures. Stable Greedy was successfully implemented on the OpenSSD platform, and the actual performance measurements were consistent with the simulation results.

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Index Terms

Stable Greedy: Adaptive Garbage Collection for Durable Page-Mapping Multichannel SSDs

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Published In

cover image ACM Transactions on Embedded Computing Systems

ACM Transactions on Embedded Computing Systems Volume 15, Issue 1

February 2016

530 pages

ISSN:1539-9087

EISSN:1558-3465

DOI:10.1145/2872313

Editor:
Sandeep K. Shukla
Indian Institute of Technology, India

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Copyright © 2016 ACM.

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ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 13 January 2016

Accepted: 01 August 2015

Revised: 01 May 2015

Received: 01 October 2014

Published in TECS Volume 15, Issue 1

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https://dl.acm.org/doi/10.1145/3605779
Niknafs MEles PPeng Z(2023)Runtime Resource Management with Multiple-Step-Ahead Workload PredictionACM Transactions on Embedded Computing Systems10.1145/360521322:4(1-34)Online publication date: 20-Jun-2023
https://dl.acm.org/doi/10.1145/3605213
Terway PJha N(2023)REPAIRS: Gaussian Mixture Model-based Completion and Optimization of Partially Specified SystemsACM Transactions on Embedded Computing Systems10.1145/360514722:4(1-36)Online publication date: 24-Jul-2023
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