No full text
Contribution to collective works (Parts of books)
Energy aware ultrascale systems
Oleksiak, Ariel; Lefèvre, Laurent; Alonso, Pedro et al.
2019In Carretero, J.; Jeannot, E.; Zomaya, A.Y. (Eds.) Ultrascale Computing Systems
Peer reviewed
 

Files


Full Text
No document available.

Send to



Details



Abstract :
[en] Energy consumption is one of the main limiting factors for the design of ultrascale infrastructures. Multi-level hardware and software optimizations must be designed and explored in order to reduce energy consumption for these largescale equipment. This chapter addresses the issue of energy efficiency of ultrascale systems in front of other quality metrics. The goal of this chapter is to explore the design of metrics, analysis, frameworks and tools for putting energy awareness and energy efficiency at the next stage. Significant emphasis will be placed on the idea of “energy complexity,” reflecting the synergies between energy efficiency and quality of service, resilience and performance, by studying computation power, communication/data sharing power, data access power, algorithm energy consumption, etc.
Research center :
ULHPC - University of Luxembourg: High Performance Computing
Disciplines :
Computer science
Author, co-author :
Oleksiak, Ariel
Lefèvre, Laurent
Alonso, Pedro
Da Costa, Georges
De Maio, Vincenzo
Frasheri, Neki
Garcia, Victor M.
Guerrero, Joel
Lafond, Sebastien
Lastovetsky, Alexey L.
Manumachu, Ravi Reddy
Muite, Benson
Orgerie, Anne-Cecile
Piatek, Wojciech
Pierson, Jean-Marc
Prodan, Radu
Stolf, Patricia
Sheme, Enida
VARRETTE, Sébastien ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Computer Science and Communications Research Unit (CSC)
More authors (9 more) Less
External co-authors :
yes
Language :
English
Title :
Energy aware ultrascale systems
Publication date :
January 2019
Main work title :
Ultrascale Computing Systems
Editor :
Carretero, J.
Jeannot, E.
Zomaya, A.Y.
Publisher :
IET
ISBN/EAN :
978-178-5618-33-8
Pages :
127-188
Peer reviewed :
Peer reviewed
Focus Area :
Computational Sciences
Available on ORBilu :
since 24 January 2020

Statistics


Number of views
45 (0 by Unilu)
Number of downloads
0 (0 by Unilu)

Scopus citations®
 
0
Scopus citations®
without self-citations
0
OpenAlex citations
 
0

Bibliography


Similar publications



Contact ORBilu