Visualizing Hierarchical Performance Profiles of Parallel Codes Using CallFlow

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 performan...

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Bibliographic Details
Published in:IEEE transactions on visualization and computer graphics 2021-04, Vol.27 (4), p.2455-2468
Main Authors: Nguyen, Huu Tan, Bhatele, Abhinav, Jain, Nikhil, Kesavan, Suraj P., Bhatia, Harsh, Gamblin, Todd, Ma, Kwan-Liu, Bremer, Peer-Timo
Format: Article
Language:English
Subjects:
coordinated and multiple views
Data visualization
hierarchical data
Histograms
Layout
Measurement
Parallel programming
Performance analysis
Performance degradation
Performance measurement
software visualization
Vegetation
visual analytics
Visualization
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Summary: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.
ISSN:1077-2626
1941-0506
DOI:10.1109/TVCG.2019.2953746