XDANNG: XML based Distributed Artificial Neural Network with Globus Toolkit

TL;DR

This paper introduces XDANNG, an XML-based framework utilizing the Globus Toolkit to enhance parallelism, flexibility, and scalability in implementing artificial neural networks on grid computing platforms.

Contribution

It presents a novel XML-based distributed ANN framework that leverages the Globus Toolkit for improved parallelism and scalability in neural network simulations.

Findings

Enhanced parallelism in ANN implementation using grid computing.

XML-based framework improves flexibility and scalability.

Demonstrated effective use of Globus Toolkit for neural network simulation.

Abstract

Artificial Neural Network is one of the most common AI application fields. This field has direct and indirect usages most sciences. The main goal of ANN is to imitate biological neural networks for solving scientific problems. But the level of parallelism is the main problem of ANN systems in comparison with biological systems. To solve this problem, we have offered a XML-based framework for implementing ANN on the Globus Toolkit Platform. Globus Toolkit is well known management software for multipurpose Grids. Using the Grid for simulating the neuron network will lead to a high degree of parallelism in the implementation of ANN. We have used the XML for improving flexibility and scalability in our framework.