Towards Visualization Scalability through Time Intervals and Hierarchical Organization of Monitoring Data

Lucas Mello Schnorr 1 Guillaume Huard 1 Philippe Olivier Alexandre Navaux 2
1 MOAIS - PrograMming and scheduling design fOr Applications in Interactive Simulation
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
2 UFRGS - Instituto de Informática da UFRGS
Abstract : Highly distributed systems such as grids are used today to the execution of large-scale parallel applications. The behavior analysis of these applications is not trivial. The complexity appears because of the event correlation among processes, external influences like time-sharing mechanisms and saturation of network links, and also the amount of data that registers the application behavior. Almost all visualization tools to analysis of parallel applications offer a space-time representation of the application behavior. This paper presents a novel technique that combines traces from grid applications with a treemap visualization of the data. With this combination, we dynamically create an annotated hierarchical structure that represents the application behavior for the selected time interval. The experiments in the grid show that we can readily use our technique to the analysis of large-scale parallel applications with thousands of processes.
Type de document :
Communication dans un congrès
The 9th IEEE International Symposium on Cluster Computing and the Grid, CCGRID, 2009, May 2009, Shanghai, China. 2009, 〈10.1109/CCGRID.2009.19〉
Liste complète des métadonnées
https://hal.inria.fr/hal-00684521
Contributeur : Ist Rennes <>
Soumis le : lundi 2 avril 2012 - 13:14:16
Dernière modification le : jeudi 11 janvier 2018 - 06:22:02

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INRIA | GRID5000 | LIG_SRCPR_MOAIS | UGA | LIG_SRCPR | LIG

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Lucas Mello Schnorr, Guillaume Huard, Philippe Olivier Alexandre Navaux. Towards Visualization Scalability through Time Intervals and Hierarchical Organization of Monitoring Data. The 9th IEEE International Symposium on Cluster Computing and the Grid, CCGRID, 2009, May 2009, Shanghai, China. 2009, 〈10.1109/CCGRID.2009.19〉. 〈hal-00684521〉

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