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Related Concept Videos

Adjusting a Traverse01:12

Adjusting a Traverse

96
In the site survey of a four-sided traverse, internal angles are essential to ensure geometric accuracy. The survey revealed that the sum of the measured internal angles was 359 degrees and 48 minutes, which is 12 minutes less than the expected 360 degrees. This discrepancy signals an error likely arising from measurement inaccuracies during the fieldwork.To rectify this error, the adjustment process involved distributing the 12-minute shortfall equally across the four internal angles. By...
96
Parallel Processing01:20

Parallel Processing

206
The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
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Design Example: Traverse Angle Computations01:25

Design Example: Traverse Angle Computations

129
Traverse angle computations are a critical component of surveying, used to compute the internal angles within a closed traverse. A traverse consists of a series of connected lines forming a closed loop, often used for land boundary delineation or mapping. Calculating the internal angles ensures accuracy in the traverse geometry and is essential for checking survey data integrity.The process begins with known azimuths and bearings of the traverse sides. Internal angles at each vertex are...
129
Interpreting Run Charts01:25

Interpreting Run Charts

278
Run charts, essentially line graphs plotted over time, serve as fundamental yet effective tools for process analysis. They chronicle data sequentially, facilitating the identification of trends, shifts, or cyclical movements. This graphical representation is instrumental in determining whether a process is stable or exhibits signs of potential instability indicative of special cause variation. In the healthcare domain, run charts depict infection rates over time, enabling hospitals to monitor...
278

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Related Experiment Video

Updated: Aug 27, 2025

Mapping Molecular Diffusion in the Plasma Membrane by Multiple-Target Tracing MTT
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Traveler: Navigating Task Parallel Traces for Performance Analysis.

Sayef Azad Sakin, Alex Bigelow, R Tohid

    IEEE Transactions on Visualization and Computer Graphics
    |September 27, 2022
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    Summary
    This summary is machine-generated.

    This study introduces Traveler, a visualization platform for high performance computing (HPC) execution traces. Traveler aids developers in analyzing complex task parallel program behavior, improving performance analysis and issue discovery.

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    Area of Science:

    • Computer Science
    • Software Engineering
    • High Performance Computing

    Background:

    • Software execution behavior analysis is crucial for performance optimization, especially in HPC.
    • Execution traces are valuable for identifying performance issues but are often large and complex.
    • Asynchronous task parallel programming increases the complexity of trace analysis.

    Purpose of the Study:

    • To address challenges in visualizing and analyzing large, complex HPC execution traces.
    • To develop an integrated visualization platform for task parallel traces.
    • To support exploratory performance analysis for HPC researchers.

    Main Methods:

    • Conducted a continuing design study in collaboration with HPC researchers.
    • Developed diverse and hierarchical methods for navigating and representing execution trace data.
    • Iteratively designed and developed the Traveler visualization platform.

    Main Results:

    • Traveler provides multiple linked interfaces for navigating trace data from multiple contexts.
    • User feedback and a case study evaluated Traveler's utility.
    • The platform supported performance analysis tasks and led to the discovery of unknown behavior.

    Conclusions:

    • Integrating multiple navigation modes in Traveler enhances performance analysis.
    • The platform facilitates the discovery of previously unknown behaviors in HPC applications.
    • Traveler is a valuable tool for interactive trace visualization and performance debugging.