Traveler: Navigating Task Parallel Traces for Performance Analysis Article Swipe
Sayef Azad Sakin
,
Alex Bigelow
,
Rezaei Tohid
,
Connor Scully-Allison
,
Carlos Scheidegger
,
Steven R. Brandt
,
C. C. W. Taylor
,
Kevin Huck
,
Hartmut Kaiser
,
Katherine E. Isaacs
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1109/tvcg.2022.3209375
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1109/tvcg.2022.3209375
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.
Related Topics
Concepts
Computer science
TRACE (psycholinguistics)
Visualization
Task (project management)
Asynchronous communication
Artifact (error)
Human–computer interaction
Data visualization
Resource (disambiguation)
Software visualization
Task management
Data science
Software
Data mining
Software development
Artificial intelligence
Programming language
Component-based software engineering
Linguistics
Management
Economics
Computer network
Philosophy
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/tvcg.2022.3209375
- OA Status
- green
- Cited By
- 8
- References
- 40
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4297462966
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4297462966Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/tvcg.2022.3209375Digital Object Identifier
- Title
-
Traveler: Navigating Task Parallel Traces for Performance AnalysisWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-09-27Full publication date if available
- Authors
-
Sayef Azad Sakin, Alex Bigelow, Rezaei Tohid, Connor Scully-Allison, Carlos Scheidegger, Steven R. Brandt, C. C. W. Taylor, Kevin Huck, Hartmut Kaiser, Katherine E. IsaacsList of authors in order
- Landing page
-
https://doi.org/10.1109/tvcg.2022.3209375Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.osti.gov/biblio/2316108Direct OA link when available
- Concepts
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Computer science, TRACE (psycholinguistics), Visualization, Task (project management), Asynchronous communication, Artifact (error), Human–computer interaction, Data visualization, Resource (disambiguation), Software visualization, Task management, Data science, Software, Data mining, Software development, Artificial intelligence, Programming language, Component-based software engineering, Linguistics, Management, Economics, Computer network, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
8Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2024: 3, 2023: 3, 2022: 1Per-year citation counts (last 5 years)
- References (count)
-
40Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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