@inproceedings{ab1b7f0c4d404e468d22b07dae103e61,
title = "Optimising flash non-volatile memory using machine learning: A project overview",
abstract = "While near ubiquitous, the physical principles of Flash memory mean that its performance degrades with use. During fabrication and operation, its ability to be repeatedly programmed/ erased (endurance) needs to be balanced with its ability to store information over months/years (retention). This project overview describes how our modelling of data we obtain experimentally from Flash chips uniquely allows us to optimise the settings of their internal configuration registers, thereby mitigating these problems.",
keywords = "Endurance, Flash memory, Machine learning, Memory performance optimisation, Non-volatile memory, Retention",
author = "Tom Arbuckle and Damien Hogan and Conor Ryan",
year = "2012",
doi = "10.1145/2371316.2371363",
language = "English",
isbn = "9781450312400",
series = "ACM International Conference Proceeding Series",
pages = "235--238",
booktitle = "5th Balkan Conference in Informatics, BCI 2012 - Proceedings",
note = "5th Balkan Conference in Informatics, BCI 2012 ; Conference date: 16-09-2012 Through 20-09-2012",
}