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1+1>2: variation-aware lifetime enhancement for embedded 3D NAND flash systems

Published: 23 June 2019 Publication History

Abstract

Three-dimensional (3D) NAND flash has been developed to boost the storage capacity by stacking memory cells vertically. One critical characteristic of 3D NAND flash is its large endurance variation. With this characteristic, the lifetime will be determined by the unit with the worst endurance. However, few works can exploit the variations with acceptable overhead for lifetime improvement. In this paper, a variation-aware lifetime improvement framework is proposed. The basic idea is motivated by an observation that there is an elegant matching between unit endurance and wearing variations when wear leveling and implicit compression are applied together. To achieve the matching goal, the framework is designed from three-type-unit levels, including cell, line, and block, respectively. Series of evaluations are conducted, and the evaluation results show that the lifetime improvement is encouraging, better than that of the combination with the state-of-the-art schemes.

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Cited By

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  • (2024)Balancing Page Endurance Variation Between Layers to Extend 3D NAND Flash Memory LifetimeMicromachines10.3390/mi1512144715:12(1447)Online publication date: 29-Nov-2024
  • (2023)Towards LDPC Read Performance of 3D Flash Memories with Layer-induced Error CharacteristicsACM Transactions on Design Automation of Electronic Systems10.1145/358507528:3(1-25)Online publication date: 27-Feb-2023
  • (2022)Tail Latency Optimization for LDPC-Based High-Density and Low-Cost Flash Memory DevicesIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2021.306276841:3(544-557)Online publication date: Mar-2022
  • Show More Cited By

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Published In

cover image ACM Conferences
LCTES 2019: Proceedings of the 20th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems
June 2019
218 pages
ISBN:9781450367240
DOI:10.1145/3316482
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]

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Publication History

Published: 23 June 2019

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Author Tags

  1. 3D NAND Flash
  2. Compression
  3. Endurance
  4. Variations
  5. Wear Leveling

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LCTES '19

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Overall Acceptance Rate 116 of 438 submissions, 26%

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Cited By

View all
  • (2024)Balancing Page Endurance Variation Between Layers to Extend 3D NAND Flash Memory LifetimeMicromachines10.3390/mi1512144715:12(1447)Online publication date: 29-Nov-2024
  • (2023)Towards LDPC Read Performance of 3D Flash Memories with Layer-induced Error CharacteristicsACM Transactions on Design Automation of Electronic Systems10.1145/358507528:3(1-25)Online publication date: 27-Feb-2023
  • (2022)Tail Latency Optimization for LDPC-Based High-Density and Low-Cost Flash Memory DevicesIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2021.306276841:3(544-557)Online publication date: Mar-2022
  • (2021)Layer-Aware Request Scheduling for 3D Flash-Based SSDsIEEE Access10.1109/ACCESS.2021.30787209(72025-72032)Online publication date: 2021
  • (2020)Error Diluting: Exploiting 3D-NAND Flash Process Variation for Efficient Read on LDPC-based SSDsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2020.3012646(1-1)Online publication date: 2020
  • (2020)DeepPrefetcher: A Deep Learning Framework for Data Prefetching in Flash Storage DevicesIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2020.3012173(1-1)Online publication date: 2020

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