Proceedings of the 2017 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2017)

Preprocessing of DAG Tasks based on Optimal Frequency Determination Method

Authors
Yuxiang Ge, Youlin Ruan
Corresponding Author
Yuxiang Ge
Available Online March 2017.
DOI
10.2991/mecae-17.2017.11How to use a DOI?
Keywords
DAG, Global Optimization, Multi-core, Optimal frequency, Energy conservation, Global DVFS.
Abstract

With the application of multi-core processor, the data processing ability has been improved. More and more scholars pay more attention to the processing optimization of the task with the constraint of each other. Marco E.T. Gerards et al. have given the way to choose the optimal clock frequencies that minimize the energy consumption for global DVFS when processing real-time tasks. This article presents a kind of DAG task preprocessing, then the energy consumption reduces 7%.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2017)
Series
Advances in Engineering Research
Publication Date
March 2017
ISBN
10.2991/mecae-17.2017.11
ISSN
2352-5401
DOI
10.2991/mecae-17.2017.11How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yuxiang Ge
AU  - Youlin Ruan
PY  - 2017/03
DA  - 2017/03
TI  - Preprocessing of DAG Tasks based on Optimal Frequency Determination Method
BT  - Proceedings of the 2017 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2017)
PB  - Atlantis Press
SP  - 62
EP  - 65
SN  - 2352-5401
UR  - https://doi.org/10.2991/mecae-17.2017.11
DO  - 10.2991/mecae-17.2017.11
ID  - Ge2017/03
ER  -