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RealWear: Improving Performance and Lifetime of SSDs Using a NAND Aging Marker

Published:05 March 2021Publication History
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Abstract

NAND flash memory has revolutionized how we manage data in modern digital systems, significant improvements are needed in flash-based storage systems to meet the requirements of emerging data-intensive applications. In this paper, we address the problem of NAND aging markers that represent the wearing degree of NAND cells. Since all flash operations are affected by the wearing status of NAND cells, an accurate NAND aging marker is critical to develop flash optimization techniques. From our evaluation study, we first show that the existing P/E cyclebased aging marker (PeWear) is inadequate to estimate the actual aging status of NAND blocks, thus losing opportunities for further optimizations. To overcome the limitations of PeWear, we propose a new NAND aging marker, RealWear, based on extensive characterization studies using real 3D TLC flash chips. By considering multiple variables that can affect the NAND cell wear, RealWear can accurately indicate the actual wear status of NAND blocks during run time. Using three case studies, we demonstrate that RealWear is effective in enhancing the lifetime and performance of a flash storage system. Our experimental results showed that RealWear can extend the lifetime of individual NAND blocks by 63% and can reduce the GC overhead by 21%. Furthermore, RealWear significantly mitigates read latency fluctuations, guaranteeing that the read latency can be bounded with at most 2 read retry operations.

References

  1. M. Kim, Y. Song, M. Jung, and J. Kim. SARO: A State-Aware Reliability Optimization Technique for High Density NAND Flash Memory. In Proceedings of the ACM Great Lakes Symposium on VLSI (GLSVLSI), 2018.Google ScholarGoogle ScholarDigital LibraryDigital Library
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  • Published in

    cover image ACM SIGMETRICS Performance Evaluation Review
    ACM SIGMETRICS Performance Evaluation Review  Volume 48, Issue 3
    December 2020
    140 pages
    ISSN:0163-5999
    DOI:10.1145/3453953
    Issue’s Table of Contents

    Copyright © 2021 Copyright is held by the owner/author(s)

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 5 March 2021

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