Leveraging approximate data for robust flash storage

Qiao Li, Liang Shi*, Jun Yang, Youtao Zhang, Chun Jason Xue

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Scopus citations

Abstract

With the increasing bit density and adoption of 3D NAND, flash memory suffers from increased errors. To address the issue, flash devices adopt error correction codes (ECC) with strong error correction capability, like low-density parity-check (LDPC) code, to correct errors. The drawback of LDPC is that, to correct data with a high raw bit error rate (RBER), read latency will be amplified. This work proposes to address this issue with the assistance of approximate data. First, studies have been conducted and show there are ample amount of approximate data available in flash storage. Second, a novel data organization is proposed to fortify the reliability of regular data by leaving approximate data unprotected. Finally, a new data allocation strategy and modified garbage collection scheme are presented to complete the design. The experimental results show that the proposed approach can improve read performance by 30% on average comparing to current techniques.

Original languageEnglish
Title of host publicationProceedings of the 56th Annual Design Automation Conference 2019, DAC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781450367257
DOIs
StatePublished - 2 Jun 2019
Event56th Annual Design Automation Conference, DAC 2019 - Las Vegas, United States
Duration: 2 Jun 20196 Jun 2019

Publication series

NameProceedings - Design Automation Conference
ISSN (Print)0738-100X

Conference

Conference56th Annual Design Automation Conference, DAC 2019
Country/TerritoryUnited States
CityLas Vegas
Period2/06/196/06/19

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