Loading...
Loading...

Go to the content (press return)

Energy optimization and analysis with EAR

Author
Corbalan, J.; Alonso, L.; Aneas, J.; Brochard, L.
Type of activity
Presentation of work at congresses
Name of edition
22nd IEEE International Conference on Cluster Computing
Date of publication
2020
Presentation's date
2020-09
Book of congress proceedings
2020 IEEE International Conference on Cluster Computing: 14–17 September 2020, Kobe, Japan: proceedings
First page
464
Last page
472
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
DOI
10.1109/CLUSTER49012.2020.00067
Project funding
Models de programació i entorns d'execució paral·lels
UPC-High Performance Computing VIII
Repository
http://hdl.handle.net/2117/338290 Open in new window
URL
https://ieeexplore.ieee.org/document/9229570 Open in new window
Abstract
EAR is an energy management framework which offers three main services: energy accounting, energy control, and energy optimization. The latter is done through the EAR runtime library (EARL). EARL is a dynamic, transparent, and lightweight runtime library that provides energy optimisation and control. EARL optimises energy by selecting the optimal CPU frequency, based on the energy policy selected and application runtime characteristics without any application modification or user input. Currentl...
Citation
Corbalán, J. [et al.]. Energy optimization and analysis with EAR. A: IEEE International Conference on Cluster Computing. "2020 IEEE International Conference on Cluster Computing: 14–17 September 2020, Kobe, Japan: proceedings". Institute of Electrical and Electronics Engineers (IEEE), 2020, p. 464-472. ISBN 978-1-7281-6677-3. DOI 10.1109/CLUSTER49012.2020.00067.
Keywords
Data centers, Energy, Optimization, System software
Group of research
CAP - High Performace Computing Group

Participants

  • Corbalan Gonzalez, Julita  (author and speaker )
  • Alonso Jane, Lluís  (author and speaker )
  • Aneas Gómez, Jordi  (author and speaker )
  • Brochard, Luigi  (author and speaker )