@inproceedings{4294b3dc1d0c437ca2669494792b9f95,
title = "DeepSwapper: A deep learning based page swap management scheme for hybrid memory systems",
abstract = "In this paper, we introduce DeepSwapper, a deep learning-basedpage swap management scheme that utilizes RNN to performfast, energy-efficient, and temperature-aware page swapping inhybrid memory systems. DeepSwapper comprises of LSTM unitsof RNN model to predict the future memory accesses to guide itsswap management scheme, a dynamic page swap managementscheme that utilizes DRAM capacity efficiently by enabling hotpages in a swap group to be swapped with cold pages of anotherswap group, and a temperature-aware page swap managementscheme, which first predicts the future writes to NVM pages andthen, decides to migrate those pages with frequent writes in hotNVM banks to DRAM to enhance the NVM lifetime. ",
keywords = "Hybrid Main Memory, Lifetime, Performance, RNN, Temperature",
author = "Beigi, {Majed Valad} and Bahareh Pourshirazi and Gokhan Memik and Zhichun Zhu",
note = "Publisher Copyright: {\textcopyright} 2020 Association for Computing Machinery.; 2020 ACM International Conference on Parallel Architectures and Compilation Techniques, PACT 2020 ; Conference date: 03-10-2020 Through 07-10-2020",
year = "2020",
month = sep,
day = "30",
doi = "10.1145/3410463.3414672",
language = "English (US)",
series = "Parallel Architectures and Compilation Techniques - Conference Proceedings, PACT",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "353--354",
booktitle = "PACT 2020 - Proceedings of the ACM International Conference on Parallel Architectures and Compilation Techniques",
address = "United States",
}