Affiliation:
1. University of Texas at Dallas
2. Yonsei University
3. Pennsylvania State University
Abstract
The paradigm shift from planar (two dimensional (2D)) to vertical (three-dimensional (3D)) models has placed the NAND flash technology on the verge of a design evolution that can handle the demands of next-generation storage applications. However, it also introduces challenges that may obstruct the realization of such 3D NAND flash. Specifically, we observed that the fast threshold drift (fast-drift) in a charge-trap flash-based 3D NAND cell can make it lose a critical fraction of the stored charge relatively soon after programming and generate errors.
In this work, we first present an elastic read reference (
V
Ref
) scheme (ERR) for reducing such errors in ReveNAND—our fast-drift aware 3D NAND design. To address the inherent limitation of the adaptive
V
Ref
, we introduce a new intra-block page organization (hitch-hike) that can enable stronger error correction for the error-prone pages. In addition, we propose a novel reinforcement-learning-based smart data refill scheme (iRefill) to counter the impact of fast-drift with minimum performance and hardware overhead. Finally, we present the first analytic model to characterize fast-drift and evaluate its system-level impact. Our results show that, compared to conventional 3D NAND design, our ReveNAND can reduce fast-drift errors by 87%, on average, and can lower the ECC latency and energy overheads by 13× and 10×, respectively.
Publisher
Association for Computing Machinery (ACM)
Subject
Hardware and Architecture,Information Systems,Software
Cited by
7 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献