Interactive analysis of large distributed systems with scalable topology-based visualization

The performance of parallel and distributed applications is highly dependent on the characteristics of the execution environment. In such environments, the network topology and characteristics tell how fast data can be transmitted and placed in the resources. These are key phenomena to understand the behavior of such applications and possibly improve it. Unfortunately few visualization available to the analyst are capable of accounting for such phenomena. In this paper, we propose an interactive topology-based visualization technique based on data aggregation that enables to correlate network characteristics, such as bandwidth and topology, with application performance traces. We show that such kind of visualization enables to explore and understand non trivial behavior that are impossible to grasp with classical visualization techniques. We also show that the combination of multi-scale aggregation and dynamic graph layout allows our visualization technique to scale seamlessly to large distributed systems. These results are validated through a detailed analysis of a high performance computing scenario and of a grid computing scenario.