Training of Neural Networks: Interactive Possibilities in a Distributed Framework

Authors:
O. Ponce;J. Cuevas;A. Fuentes;J. Marco;R. Marco;C. Martínez-Rivero;R. Menéndez;D. Rodríguez
Affiliations:
-;-;-;-;-;-;-;-
Venue:
Proceedings of the 9th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
Year:
2002

Citing 3
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Abstract

Training of Artificial Neural Networks in a Distributed Environment is considered and applied to a typical example in High Energy Physics interactive analysis. Promising results showing a reduction of the wait time from 5 hours to 5 minutes obtained in a local cluster with 64 nodes are described. Preliminary tests in a wide area network studying the impact of latency time are described; and the future work for integration in a GRID framework, that will be carried in the CrossGrid European Project, is outlined.