Modern HPC systems, such as Cray’s XE and IBM’s Blue Gene line,
feature sophisticated network architectures, often in the form of high dimensional tori. In order to fully exploit the performance of these systems, it is necessary to carefully map an application’s communication structure to the underlying network topology. In this step, both latency (i.e., physical distance between nodes) and bandwidth (i.e., number of concurrently used links) have to be taken into account, leading to mappings that are often non-intuitive. To help developers with this complex problem, we are developing a set of tools that aim at helping users understand the communication behavior of their codes, map them onto the network architecture, and create better-performing topology-aware node mappings.
In this paper, we present initial steps towards this goal, including a measurement environment capturing both communication patterns and network metrics within the same run, a methodology to compare these measurements, and a visualization tool that helps users understand the impact of their application’s characteristics on the network behavior.