Modeling Retention Errors of 3D NAND Flash for Optimizing Data Placement-Reference-Cited by-同舟云学术

Modeling Retention Errors of 3D NAND Flash for Optimizing Data Placement

Published:2024-06-21 Issue:4 Volume:29 Page:1-24
ISSN:1084-4309
Container-title:ACM Transactions on Design Automation of Electronic Systems
language:en
Short-container-title:ACM Trans. Des. Autom. Electron. Syst.

Author:

Tian Huan¹^ORCID,Tang Jiewen²^ORCID,Li Jun²^ORCID,Sha Zhibing²^ORCID,Yang Fan¹^ORCID,Cai Zhigang²^ORCID,Liao Jianwei¹^ORCID

Affiliation:

1. College of Computer and Information Science, Southwest University, Chongqing, China

2. Southwest University, Chongqing, China

Abstract

Considering 3D NAND flash has a new property of process variation (PV) , which causes different raw bit error rates (RBER) among different layers of the flash block. This article builds a mathematical model for estimating the retention errors of flash cells, by considering the factor of layer-to-layer PV in 3D NAND flash memory, as well as the factors of program/erase (P/E) cycle and retention time of data. Then, it proposes classifying the layers of flash block in 3D NAND flash memory into profitable and unprofitable categories, according to the error correction overhead. After understanding the retention error variation of different layers in 3D NAND flash, we design a mechanism of data placement, which maps the write data onto a suitable layer of flash block, according to the data hotness and the error correction overhead of layers, to boost read performance of 3D NAND flash. The experimental results demonstrate that our proposed retention error estimation model can yield a R 2 value of 0.966 on average, verifying the accuracy of the model. Based on the estimated retention error rates of layers, the proposed data placement mechanism can noticeably reduce the read latency by 29.8 % on average, compared with state-of-the-art methods against retention errors for 3D NAND flash memory.

Funder

National Natural Science Foundation of China

Natural Science Foundation Project of CQ CSTC

Publisher

Association for Computing Machinery (ACM)

Link

https://dl.acm.org/doi/pdf/10.1145/3659101

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