Traveler: Navigating Task Parallel Traces for Performance Analysis

TL;DR

Traveler is a visualization platform that helps high performance computing developers explore complex task parallel execution traces, enabling the discovery of performance issues and unknown behaviors through multi-faceted navigation tools.

Contribution

The paper introduces Traveler, an integrated visualization system with hierarchical navigation tailored for analyzing large, complex task parallel traces in high performance computing.

Findings

Supported performance analysis tasks effectively.

Enabled discovery of previously unknown behaviors.

Received positive user feedback and case study validation.

Abstract

Understanding the behavior of software in execution is a key step in identifying and fixing performance issues. This is especially important in high performance computing contexts where even minor performance tweaks can translate into large savings in terms of computational resource use. To aid performance analysis, developers may collect an execution trace - a chronological log of program activity during execution. As traces represent the full history, developers can discover a wide array of possibly previously unknown performance issues, making them an important artifact for exploratory performance analysis. However, interactive trace visualization is difficult due to issues of data size and complexity of meaning. Traces represent nanosecond-level events across many parallel processes, meaning the collected data is often large and difficult to explore. The rise of asynchronous task parallel programming paradigms complicates the relation between events and their probable cause. To address these challenges, we conduct a continuing design study in collaboration with high performance computing researchers. We develop diverse and hierarchical ways to navigate and represent execution trace data in support of their trace analysis tasks. Through an iterative design process, we developed Traveler, an integrated visualization platform for task parallel traces. Traveler provides multiple linked interfaces to help navigate trace data from multiple contexts. We evaluate the utility of Traveler through feedback from users and a case study, finding that integrating multiple modes of navigation in our design supported performance analysis tasks and led to the discovery of previously unknown behavior in a distributed array library.