NCA-AIIO exam dumps

NCA-AIIO practice question 82 of 119

NVIDIA-Certified Associate - AI Infrastructure and Operations. Free level, NVIDIA. Free question with the correct answer and a full explanation.

NCA-AIIO Question 82

Select 2

You are tasked with analyzing GPU utilization data from a cluster running AI workloads. After completing the analysis, you need to create a visualization to effectively communicate the results to stakeholders. Which of the following visualizations would be most appropriate for showcasing patterns in GPU utilization over time and comparing utilization across multiple GPUs?

  1. A

    Line chart

  2. B

    Bar chart

  3. C

    Scatter plot

  4. D

    Pie chart

  5. E

    Heatmap

Show answer and explanation

Correct answers: A, E

Explanation

When analyzing GPU utilization over time and across multiple GPUs, a line chart is best for showing temporal trends, while a heatmap is ideal for comparing utilization across multiple GPUs in a visually intuitive manner. These two visualization types together can effectively convey the analysis results to stakeholders.

  • A. Correct.

    A line chart is effective for visualizing trends over time, such as GPU utilization patterns. It helps stakeholders see how utilization changes throughout the timeline.

  • B. Incorrect.

    A bar chart is better suited for comparing discrete values rather than continuous patterns over time. It is not ideal for showcasing GPU utilization trends over time.

  • C. Incorrect.

    A scatter plot is used to show relationships or correlations between two variables, but it is not ideal for showing time-based trends or comparisons across multiple GPUs.

  • D. Incorrect.

    A pie chart is used to represent proportions or percentages of a whole and is not suitable for showcasing GPU utilization trends or comparisons.

  • E. Correct.

    A heatmap is effective for comparing GPU utilization across multiple GPUs and time intervals, using color intensity to convey the level of utilization at different points in time.

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