Lune

DAC2020顶会

Layer RBER Variation Aware Read Performance Optimization for 3D Flash Memories

Shiqiang Nie, Youtao Zhang, Weiguo Wu, Jun Yang

2020年份
16被引次数
1顶会引用

摘要

3D NAND flash enables the construction of large capacity Solid-State Drives (SSDs) for modern computer systems. While effectively reducing per bit cost, 3D NAND flash exhibits non-negligible process variations and thus RBER (raw bit error rate) difference across layers, which leads to sub-optimal read performance for applications with either small or large I/O requests. In this paper, we propose LRR, Layer RBER variation aware Read optimization schemes, to address the challenge. LRR consists of two schemes - LRR subpage read scheduling (SRS) and LRR fullpage allocation (FPA). SRS groups small read requests from the layers with similar RBERs to reduce the average read latency of subpage sized read requests. FPA distributes the data of a large write to multiple layers, which improves the read latency when reading from layers with large RBERs. Our experimental results show that our proposed scheme LRR reduces 46% read latency on average over the state-of-the-art.

问问这篇 Paper

智能体会读完全文。

Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。

可以从这些问题问起

智能体调用

Luneget_paper_fulltext

在 Lune 里问

免费开始,无需绑卡

引用它的顶会 Paper1

问问它们各自怎么用它

相关 Paper

黄昏的海面,两侧是细线勾勒的悬崖