Paper Info
Title
Software-Managed Read and Write Wear-Leveling for Non-Volatile Main Memory
Abstract
AbstractIn-memory wear-leveling has become an important research field for emerging non-volatile main memories over the past years. Many approaches in the literature perform wear-leveling by making use of special hardware. Since most non-volatile memories only wear out from write accesses, the proposed approaches in the literature also usually try to spread write accesses widely over the entire memory space. Some non-volatile memories, however, also wear out from read accesses, because every read causes a consecutive write access. Software-based solutions only operate from the application or kernel level, where read and write accesses are realized with different instructions and semantics. Therefore different mechanisms are required to handle reads and writes on the software level. First, we design a method to approximate read and write accesses to the memory to allow aging aware coarse-grained wear-leveling in the absence of special hardware, providing the age information. Second, we provide specific solutions to resolve access hot-spots within the compiled program code (text segment) and on the application stack. In our evaluation, we estimate the cell age by counting the total amount of accesses per cell. The results show that employing all our methods improves the memory lifetime by up to a factor of 955×.
Year
DOI
Venue
2022
10.1145/3483839
ACM Transactions on Embedded Computing Systems
Keywords
DocType
Volume
Non-volatile memory, wear-leveling, read-destructive, age approximation
Journal
21
Issue
ISSN
Citations 
1
1539-9087
1
PageRank 
References 
Authors
0.35
0
9
Name
Order
Citations
PageRank
Christian Hakert111.70
Kuan-Hsun Chen2239.48
Horst Schirmeier310.35
Lars Bauer420.71
Paul R. Genssler510.35
Georg von der Bruggen613.05
Hussam Amrouch725150.22
J. Henkel84471366.50
Jian-Jia Chen92007129.20