Paper Info
Title
ApproxRefresh: Enabling Uncorrectable Data Reuse on Flash Memory with Approximate Read Awareness
Abstract
With the increased density and the technology scaling, flash memory is more vulnerable to noise effects, overwhelmingly lowering the data retention time. The periodic data refresh technique is commonly used to retain the long-term data integrity. However, the frequent refresh requests also introduce the increased access conflict and severe write amplification, leading to sub-optimal performance and lifetime improvement. In this paper, we propose ApproxRefresh, which enables the uncorrectable data reuse with the assistance of approximate-computing applications in order to reduce the refresh costs. Specifically, we design a lightweight remapping-free refresh technique, called RFR, to periodically correct, compute an enhanced ECC and only remap new ECC parity bits, which dramatically reduces the refresh costs. Then, with approximate-read and precise-read hotness awareness, ApproxRefresh selectively adopts RFR or the traditional remapping-based refresh technique to reduce the refresh costs and the read disturbance. In addition, a corresponding ApproxRefresh-aware garbage collection algorithm is proposed to complete the design. Evaluations show that ApproxRefresh reduces the refresh latency by 35.09% over the state-of-the-art.
Year
DOI
Venue
2020
10.1145/3372799.3394362
LCTES '20: 21st ACM SIGPLAN/SIGBED Conference on Languages, Compilers, and Tools for Embedded Systems London United Kingdom June, 2020
Keywords
DocType
ISBN
flash memory, solid state drives, data refresh, garbage collection, approximate computing
Conference
978-1-4503-7094-3
Citations 
PageRank 
References 
0
0.34
13
Authors
5
Name
Order
Citations
PageRank
Jinhua Cui121.04
Junwei Liu221.07
Jianhang Huang3136.37
Haoran Zhu400.34
Laurence T. Yang56870682.61