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Hakert/Chen/2022b: Software-Managed Read and Write Wear-Leveling for Non-Volatile Main Memory

Bibtype Article
Bibkey Hakert/Chen/2022b
Author Hakert, Christian and Chen, Kuan-Hsun and Schirmeier, Horst and Chen, Jian-Jia and Genssler, Paul R. and von der Br\"uggen, Georg and Amrouch, Hussam and Henkel, J\"org and Chen, Jian-Jia
Title Software-Managed Read and Write Wear-Leveling for Non-Volatile Main Memory
Journal ACM Transactions on Embedded Computing Systems
Volume 21
Number 1
Abstract In-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 955x.
Year 2022
Projekt SFB876-A1
Doi 10.1145/3483839
Issn 1539-9087
Url https://doi.org/10.1145/3483839
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