Distributing SOM Ensemble Training using Grid Middleware
- Resource Type
- Conference
- Authors
- Vrusias, Bogdan L.; Vomvoridis, Leonidas; Lee Gillam
- Source
- 2007 International Joint Conference on Neural Networks Neural Networks, 2007. IJCNN 2007. International Joint Conference on. :2712-2717 Aug, 2007
- Subject
- Computing and Processing
Components, Circuits, Devices and Systems
Signal Processing and Analysis
Middleware
Neural networks
Training data
Artificial neural networks
Computer networks
Clocks
Network topology
Partitioning algorithms
Testing
Boosting
- Language
- ISSN
- 2161-4393
2161-4407
In this paper we explore the distribution of training of self-organised maps (SOM) on Grid middleware. We propose a two-level architecture and discuss an experimental methodology comprising ensembles of SOMs distributed over a Grid with periodic averaging of weights. The purpose of the experiments is to begin to systematically assess the potential for reducing the overall time taken for training by a distributed training regime against the impact on precision. Several issues are considered: (i) the optimum number of ensembles; (ii) the impact of different types of training data; and (iii) the appropriate period of averaging. The proposed architecture has been evaluated in a Grid environment, with clock-time performance recorded.