A First Step Towards Automatically Building Network Representations

TL;DR

This paper evaluates existing and new algorithms for automatically constructing network topology models, revealing limitations in current methods and proposing new algorithms that improve accuracy in predicting application performance.

Contribution

It introduces a methodology to assess network model building tools and proposes new algorithms that outperform existing techniques in accuracy.

Findings

Existing techniques fail to accurately predict application kernel runtimes.

Some new algorithms achieve excellent prediction accuracy across various scenarios.

The methodology provides a standardized way to evaluate network model quality.

Abstract

To fully harness Grids, users or middlewares must have some knowledge on the topology of the platform interconnection network. As such knowledge is usually not available, one must uses tools which automatically build a topological network model through some measurements. In this article, we define a methodology to assess the quality of these network model building tools, and we apply this methodology to representatives of the main classes of model builders and to two new algorithms. We show that none of the main existing techniques build models that enable to accurately predict the running time of simple application kernels for actual platforms. However some of the new algorithms we propose give excellent results in a wide range of situations.