DocumentCode :
3591149
Title :
Coupling-aware graph partitioning algorithms: Preliminary study
Author :
Predari, Maria ; Esnard, Aurelien
Author_Institution :
LaBRI, Univ. Bordeaux, Talence, France
fYear :
2014
Firstpage :
1
Lastpage :
10
Abstract :
In the field of scientific computing, load balancing is a major issue that determines the performance of parallel applications. Nowadays, simulations of real-life problems are becoming more and more complex, involving numerous coupled codes, representing different models. In this context, reaching high performance can be a great challenge. In this paper, we present graph partitioning techniques, called co-partitioning, that address the problem of load balancing for two coupled codes: the key idea is to perform a “coupling-aware” partitioning, instead of partitioning these codes independently, as it is usually done. Finally, we present a preliminary experimental study which compares our methods against the usual approach.
Keywords :
graph theory; parallel processing; resource allocation; co-partitioning; coupling-aware graph partitioning algorithm; load balancing; parallel application; scientific computing; Atmospheric modeling; Computational modeling; Couplings; Load management; Load modeling; Partitioning algorithms; Program processors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
High Performance Computing (HiPC), 2014 21st International Conference on
Print_ISBN :
978-1-4799-5975-4
Type :
conf
DOI :
10.1109/HiPC.2014.7116879
Filename :
7116879
Link To Document :
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