Imperial College London
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ProfessorGerardGorman

Faculty of Engineering, Department of Earth Science & Engineering

Professor of Computational Science and Engineering
 
 
 
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Contact

 

+44 (0)20 7594 9985g.gorman Website

 
 
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Location

 

R4.92Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@unpublished{Kukreja:2019,
author = {Kukreja, N and Shilova, A and Beaumont, O and Huckelheim, J and Ferrier, N and Hovland, P and Gorman, G},
publisher = {arXiv},
title = {Training on the Edge: The why and the how},
url = {https://arxiv.org/abs/1903.03051v1},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - UNPB
AB  - Edge computing is the natural progression from Cloud computing, where, instead of collecting all data and processing it centrally, like in a cloud computing environment, we distribute the computing power and try to do as much processing as possible, close to the source of the data. There are various reasons this model is being adopted quickly, including privacy, and reduced power and bandwidth requirements on the Edge nodes. While it is common to see inference being done on Edge nodes today, it is much less common to do training on the Edge. The reasons for this range from computational limitations, to it not being advantageous in reducing communications between the Edge nodes. In this paper, we explore some scenarios where it is advantageous to do training on the Edge, as well as the use of checkpointing strategies to save memory.
AU  - Kukreja,N
AU  - Shilova,A
AU  - Beaumont,O
AU  - Huckelheim,J
AU  - Ferrier,N
AU  - Hovland,P
AU  - Gorman,G
PB  - arXiv
PY  - 2019///
TI  - Training on the Edge: The why and the how
UR  - https://arxiv.org/abs/1903.03051v1
UR  - http://hdl.handle.net/10044/1/75882
ER  -
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