Visual and Audio Monitoring of Island Based Parallel Evolutionary Algorithms

Abstract : Monitoring and visualisation tools are currently attracting more and more attention in order to understand how search spaces are explored by complex optimisation ecosystems such as parallel evolutionary algorithms based on island models. Multilevel visualisation is actually a desirable feature for facilitating the monitoring of computationally expensive runs involving several hundreds of computers during hours or even days. In this paper we present two components of a future multilevel monitoring system: MusEAc, a high level, audio monitoring allowing to listen to a run and tune it in real time and GridVis, a lower lever, more precise a posteriori visualisation tool that lets the user understand why the algorithm has performed well or bad.
Type de document :
Article dans une revue
Journal of Grid Computing, Springer Verlag, 2015, 13 (3), pp.309-327. <10.1007/s10723-014-9321-8>
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-01536557
Contributeur : Archive Ouverte Prodinra <>
Soumis le : dimanche 11 juin 2017 - 20:45:04
Dernière modification le : samedi 17 juin 2017 - 01:17:15

Identifiants

Citation

Evelyne Lutton, Hugo Gilbert, Waldo Cancino, Benjamin Bach, Joseph Pallamidessi, et al.. Visual and Audio Monitoring of Island Based Parallel Evolutionary Algorithms. Journal of Grid Computing, Springer Verlag, 2015, 13 (3), pp.309-327. <10.1007/s10723-014-9321-8>. <hal-01536557>

Partager

Métriques

Consultations de la notice

52