Ordering Traces Logically to Identify Lateness in Parallel Programs

Abstract

Event traces are a valuable tool for understanding the behavior of parallel programs. Automatically analyzing a large trace, however, especially without a specific objective, is difficult. We aid this process by extracting a trace’s logical structure, an ordering of events derived from their happened before relationships. From this perspective, we can calculate delays relative to peers rather than duration and determine where they begin and how they propagate. The logical structure also acts as a platform for comparing and clustering processes as well as showing communication patterns in a trace visualization. We present an algorithm for determining this idealized logical structure from a trace and develop metrics to quantify delays and differences among processes. We implement this in our novel trace visualizer, Ravel, and apply our approach to several applications, demonstrating the accuracy of our extracted structure and its utility in analyzing these codes.