Ocelotl: Large Trace Overviews Based on Multidimensional Data Aggregation

Damien Dosimont 1, * Youenn Corre 1 Lucas Mello Schnorr 2 Guillaume Huard 1 Jean-Marc Vincent 3
* Auteur correspondant
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
3 MESCAL - Middleware efficiently scalable
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
Abstract : Performance analysis of parallel applications is commonly based on execution traces that might be investigated through visualization techniques. The weak scalability of such techniques appears when traces get larger both in time (many events registered) and space (many processing elements), a very common situation for current large-scale HPC applications. In this paper we present an approach to tackle such scenarios in order to give a correct overview of the behavior registered in very large traces. Two configurable and controlled aggregation-based techniques are presented: one based exclusively on the temporal aggregation, and another that consists in a spatiotemporal aggregation algorithm. The paper also details the implementation and evaluation of these techniques in Ocelotl, a performance analysis and visualization tool that overcomes the current graphical and interpretation limitations by providing a concise overview registered on traces. The experimental results show that Ocelotl helps in detecting quickly and accurately anomalies in 8 GB traces containing up to two hundred million of events.
Type de document :
Communication dans un congrès
8th International Parallel Tools Workshop, Oct 2014, Stuttgart, Germany
Liste complète des métadonnées

Littérature citée [16 références]  Voir  Masquer  Télécharger
https://hal.inria.fr/hal-01120179
Contributeur : Damien Dosimont <>
Soumis le : mercredi 25 février 2015 - 07:48:10
Dernière modification le : mercredi 11 avril 2018 - 01:52:38
Document(s) archivé(s) le : mardi 26 mai 2015 - 13:26:13

Fichier

ocelotl.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01120179, version 1

Collections

INRIA | LIG | LIG_SRCPR_MOAIS | UGA | LIG_SRCPR | INRIA-RENGRE

Citation

Damien Dosimont, Youenn Corre, Lucas Mello Schnorr, Guillaume Huard, Jean-Marc Vincent. Ocelotl: Large Trace Overviews Based on Multidimensional Data Aggregation. 8th International Parallel Tools Workshop, Oct 2014, Stuttgart, Germany. 〈hal-01120179〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

245

Téléchargements de fichiers

157

Contact


archive-ouverte@inria.fr