Abstract
We present FF-SSD, a machine learning-based SSD aging framework that generates representative future wear-out states. FF-SSD is accurate (up to 99% similarity), efficient (accelerates simulation time by 2×), and modular (can be integrated with existing simulators and emulators).
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CITATION STYLE
APA
Jiao, Z., & Kim, B. S. (2022). Generating realistic wear distributions for SSDs. In HotStorage 2022 - Proceedings of the 2022 14th ACM Workshop on Hot Topics in Storage and File Systems (pp. 65–71). Association for Computing Machinery, Inc. https://doi.org/10.1145/3538643.3539757
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