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Combing the Communication Hairball: Visualizing Parallel Execution Traces using Logical Time
University of California, USA. (IDAV)
Lawrence Livermore National Laboratory, USA.
University of California, Davis, USA. (IDAV)ORCID iD: 0000-0001-6745-4398
Lawrence Livermore National Laboratory, USA.
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2014 (English)In: IEEE Transactions on Visualization and Computer Graphics, ISSN 1077-2626, E-ISSN 1941-0506, Vol. 20, no 12, 2349-2358 p.Article in journal (Refereed) Published
Abstract [en]

With the continuous rise in complexity of modern supercomputers, optimizing the performance of large-scale parallel programs is becoming increasingly challenging. Simultaneously, the growth in scale magnifies the impact of even minor inefficiencies - potentially millions of compute hours and megawatts in power consumption can be wasted on avoidable mistakes or sub-optimal algorithms. This makes performance analysis and optimization critical elements in the software development process. One of the most common forms of performance analysis is to study execution traces, which record a history of per-process events and interprocess messages in a parallel application. Trace visualizations allow users to browse this event history and search for insights into the observed performance behavior. However, current visualizations are difficult to understand even for small process counts and do not scale gracefully beyond a few hundred processes. Organizing events in time leads to a virtually unintelligible conglomerate of interleaved events and moderately high process counts overtax even the largest display. As an alternative, we present a new trace visualization approach based on transforming the event history into logical time inferred directly from happened-before relationships. This emphasizes the code’s structural behavior, which is much more familiar to the application developer. The original timing data, or other information, is then encoded through color, leading to a more intuitive visualization. Furthermore, we use the discrete nature of logical timelines to cluster processes according to their local behavior leading to a scalable visualization of even long traces on large process counts. We demonstrate our system using two case studies on large-scale parallel codes.

Place, publisher, year, edition, pages
IEEE Press, 2014. Vol. 20, no 12, 2349-2358 p.
Keyword [en]
data visualisation;parallel programming;software engineering;code structural behavior;communication hairball;event history;interprocess messages;large-scale parallel programs;logical time;parallel execution trace visualization;per-process events;software development process;Data visualization;Image color analysis;Large-scale systems;Performance analysis;Supercomputers;Information visualization;performance analysis;software visualization;timelines;traces
National Category
Computer Science
Identifiers
URN: urn:nbn:se:lnu:diva-42279DOI: 10.1109/TVCG.2014.2346456OAI: oai:DiVA.org:lnu-42279DiVA: diva2:805065
Available from: 2015-04-14 Created: 2015-04-14 Last updated: 2015-04-14Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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