@inproceedings{462026d61a2144ba94ee8186bef27a7c,
title = "Deep Learning on Cryptocurrency-Challenges Processing GPU and CPU Architectures",
abstract = "Deep learning has made vast advances over the recent decade due to hardware, software, and architecture improvements. Applying deep learning still has some challenges to overcome, especially when processing on GPU or in parallel. This work seeks to apply RNN and LSTM over a variety of architectures to demonstrate the challenges and techniques encountered when applying deep learning. We apply RNN and LSTM over GPU and CPU across PC, high performance computing cluster, and cloud and present our challenges and results.",
keywords = "Bitcoin, Cryptocurrency, Deep Learning, GPU, LSTM, RNN",
author = "Alex Trawinski and Hayden Wimmer and Weitian Tong",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 12th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2021 ; Conference date: 27-10-2021 Through 30-10-2021",
year = "2021",
doi = "10.1109/IEMCON53756.2021.9623132",
language = "English",
series = "2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "371--377",
editor = "Satyajit Chakrabarti and Rajashree Paul",
booktitle = "2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2021",
address = "United States",
}