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Visualizing Hierarchical Performance Profiles of Parallel Codes Using CallFlow.

作者信息

Nguyen Huu Tan, Bhatele Abhinav, Jain Nikhil, Kesavan Suraj P, Bhatia Harsh, Gamblin Todd, Ma Kwan-Liu, Bremer Peer-Timo

出版信息

IEEE Trans Vis Comput Graph. 2021 Apr;27(4):2455-2468. doi: 10.1109/TVCG.2019.2953746. Epub 2021 Feb 25.

Abstract

Calling context trees (CCTs) couple performance metrics with call paths, helping understand the execution and performance of parallel programs. To identify performance bottlenecks, programmers and performance analysts visually explore CCTs to form and validate hypotheses regarding degraded performance. However, due to the complexity of parallel programs, existing visual representations do not scale to applications running on a large number of processors. We present CallFlow, an interactive visual analysis tool that provides a high-level overview of CCTs together with semantic refinement operations to progressively explore CCTs. Using a flow-based metaphor, we visualize a CCT by treating execution time as a resource spent during the call chain, and demonstrate the effectiveness of our design with case studies on large-scale, production simulation codes.

摘要

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