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ALARM: A Location-Aware Redistribution Method to Improve 3D FG NAND Flash Reliability
KTH, School of Information and Communication Technology (ICT), Electronics.
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2017 (English)In: 2017 IEEE International Conference on Networking, Architecture, and Storage, NAS 2017 - Proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2017, article id 8026841Conference paper, Published paper (Refereed)
Abstract [en]

3D NAND flash memory is enjoying an increasing popularity as it dramatically increases the bit density, presenting a grand opportunity to satisfy the growing demand on the storage capacity. However, this vertically stacked structure also introduces more serious read disturb problems compared with planar flash devices. Characterization results show that the read disturb errors on 3D floating gate (FG) MLC NAND flash chips exhibit a large discrepancy on the locations and types of pages, implying that pages should not be treated equally when designing migration schemes. This paper makes a thorough observation on read access characteristics by analyzing contemporary workloads collected from a wide range of applications with various read ratios. Based on the characterization results, we build a read disturb error model and propose a location-aware redistribution method (ALARM) that utilizes the intrinsic characteristics of the 3D floating gate NAND flash and redistributes read-hot pages to locations inducing less read disturb errors to improve its reliability. We implement the read disturb error model and our proposed design on an event-driven simulator, and the experimental results show that ALARM can reduce the maximum and average raw bit error rates (RBERs) by up to 99.49% and 91.80% with an operation overhead of 0.70%.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017. article id 8026841
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-217127DOI: 10.1109/NAS.2017.8026841ISI: 000427036600012Scopus ID: 2-s2.0-85031741883ISBN: 9781538634868 OAI: oai:DiVA.org:kth-217127DiVA, id: diva2:1154054
Conference
2017 IEEE International Conference on Networking, Architecture, and Storage, NAS 2017, Shenzhen, China, 7 August 2017 through 9 August 2017
Note

QC 20171101

Available from: 2017-11-01 Created: 2017-11-01 Last updated: 2018-04-03Bibliographically approved

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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
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