Automated characterization of parallel application communication patterns

A concise description of an application's communication pattern is often useful, for example, as an efficient way to communicate application behavior to a system vendor. Several existing performance analysis tools can capture aspects of an application's communication behavior such as which processes communicated with which others and the communications operations they used. However, a human with a high degree of expertise is still required to recognize and characterize common communication idioms within the performance data collected by those tools. To simplify this characterization for non-experts, we have developed an approach for automatically characterizing a MPI application's communication behavior. We use the mpiP profiling tool to collect information about an application's communication topology and message volume. We then use a post-mortem search-based analysis to compare the application's observed communication pattern against a library of common communication patterns. By comparing the result of the various search paths, our approach identifies the combination of patterns that best matches the observed behavior. To evaluate our approach, we applied it to a synthetic example communication matrix and communication matrices obtained from two scientific applications. We determined that our automated approach was highly effective in characterizing the communication patterns represented in the matrices.