@inproceedings{Hoelscher:2023,
abstract = {In emerging computing systems, non-volatile memory ({NVM}) is becoming an alternative to conventional main memory technologies such as {DRAM}. With its many advantages it also yields disadvantages, such as shorter memory cell life times. Due to its shorter lived nature, wear-leveling on main memory becomes an important aspect of systems using {NVM}. Hardware methods are implemented such as iterative write schemes (repeatedly sense and write), which will check a memory cell before changing it. But hardware methods alone do not provide optimal wear-leveling, so they should be used together with software based methods, which try to evenly distribute wear over large memory regions. However, for software wear leveling on {NVM} main memory no standardized evaluation setup exists. Which leaves most of these approaches incomparable to each other. In this work we will leverage existing solutions for evaluation such as Gem5 [1] and {NVMain} [20] and extend them with our own methods, analysis setup and benchmark suite. We thoroughly explain our setup in this article and provide a tool for a comparable and easy to use evaluation setup for software based {NVM} main memory wear-leveling.},
author = {Hölscher, Nils and Truong, Minh Duy and Hakert, Christian and Seidl, Tristan and Chen, Kuan-Hsun and Chen, Jian-Jia},
booktitle = {2023 {IEEE} 12th Non-Volatile Memory Systems and Applications Symposium ({NVMSA})},
date = {2023-08},
doi = {10.1109/NVMSA58981.2023.00012},
eventtitle = {2023 {IEEE} 12th Non-Volatile Memory Systems and Applications Symposium ({NVMSA})},
issn = {2575-257X},
keywords = {Measurement, Nonvolatile memory, Random access memory, Benchmark testing, Software, Hardware, Iterative methods, Simulation, Non-Volatile Memory, Wear-Out, Benchmark, Tool, Wear-Leveling},
note = {{ISSN}: 2575-257X},
pages = {50–55},
title = {Rapid {NVM} Simulation and Analysis on Single Bit Granularity Featuring Gem5 and {NVMain}},
url = {https://ieeexplore.ieee.org/document/10254342},
}
