An Efficient Independent Read Scheme for Contemporary QLC SSDs

QLC solid-state disks (SSDs) are increasingly deployed in large-scale storage systems. While achieving remarkable storage density and cost-effectiveness, QLC NAND exhibits degraded performance. To alleviate the issue, Independent Multi-Plane (IMP) read has been proposed to leverage the plane-level parallelism under random read workloads. However, compared to the previous generations of chips, the variation in read latency of QLC chip has widened significantly, and the number of planes in a QLC chip has increased. As a result, the idle time in IMP commands has escalated dramatically. Moreover, the conventional layout of data and parities in redundant array of independent NAND (RAIN) increases the probability of high latency read occureneces, exacerbating the contribution to idle time. Consequently, the incorporation of IMP is inherently inefficient in contemporary QLC NAND flash chips. In this paper, we propose an efficient independent read (EFFIR) scheme to tackle this challenge. EFFIR features a read latency variation aware transaction service that properly combines read transactions to minimize idle time and proactively transfers read data to eliminate unnecessary delays. Moreover, EFFIR incorporates a read latency variation aware RAIN that reorganizes the layout of data and parity to mitigate the impact of high-latency data access on idle time. Our comprehensive experimental results demonstrate and elucidate how EFFIR significantly enhances SSD responsiveness while consistently delivering favorable performance across a diverse range of read-intensive workloads.

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Publication Details

Journal
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Published
2025-04-29
DOI
https://doi.org/10.1109/tcad.2025.3565484
Primary Topic
Advanced Data Storage Technologies
Type
article
Field-Weighted Citation Impact
0.00

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article

An Efficient Independent Read Scheme for Contemporary QLC SSDs

Xueliang Wei, Dan Feng, Jie Yang, Qiankun Liu et al.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Advanced Data Storage Technologies
article

An Efficient Independent Read Scheme for Contemporary QLC SSDs

Xueliang Wei, Dan Feng, Jie Yang, Qiankun Liu, Wei Zhao, Shu Li, Feng Zhu, Wei Tong, Dong Huang, Bo Ding, M. Yuan
article en

Abstract

QLC solid-state disks (SSDs) are increasingly deployed in large-scale storage systems. While achieving remarkable storage density and cost-effectiveness, QLC NAND exhibits degraded performance. To alleviate the issue, Independent Multi-Plane (IMP) read has been proposed to leverage the plane-level parallelism under random read workloads. However, compared to the previous generations of chips, the variation in read latency of QLC chip has widened significantly, and the number of planes in a QLC chip has increased. As a result, the idle time in IMP commands has escalated dramatically. Moreover, the conventional layout of data and parities in redundant array of independent NAND (RAIN) increases the probability of high latency read occureneces, exacerbating the contribution to idle time. Consequently, the incorporation of IMP is inherently inefficient in contemporary QLC NAND flash chips. In this paper, we propose an efficient independent read (EFFIR) scheme to tackle this challenge. EFFIR features a read latency variation aware transaction service that properly combines read transactions to minimize idle time and proactively transfers read data to eliminate unnecessary delays. Moreover, EFFIR incorporates a read latency variation aware RAIN that reorganizes the layout of data and parity to mitigate the impact of high-latency data access on idle time. Our comprehensive experimental results demonstrate and elucidate how EFFIR significantly enhances SSD responsiveness while consistently delivering favorable performance across a diverse range of read-intensive workloads.

IEEE Transactions on Computer-Aided Design of Integrated Circuits and SystemsVol. 44(11)
Wuhan National Laboratory for Optoelectronics (CN), Alibaba Group (China) (CN), Huazhong University of Science and Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 91%
Advanced Data Storage Technologies
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