NCA-AIIO exam dumps

NCA-AIIO practice question 52 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 52

Select 3

Your team is tasked with running a large-scale AI training workload on a new infrastructure. The workload involves extensive matrix calculations and parallel computations. During a discussion, one of your colleagues suggests using CPUs instead of GPUs for the workload. Which of the following reasons justify using GPUs over CPUs in this scenario?

  1. A

    GPUs have thousands of cores optimized for parallel processing, making them ideal for matrix-heavy computations.

  2. B

    GPUs are generally more power-efficient for AI training workloads compared to CPUs.

  3. C

    GPUs have higher clock speeds than CPUs, making them faster for all types of computations.

  4. D

    GPUs are specifically designed to handle high-throughput tasks like deep learning training.

  5. E

    GPUs have more advanced branch prediction capabilities compared to CPUs, which improves their performance.

Show answer and explanation

Correct answers: A, B, D

Explanation

GPUs are specifically designed for parallel processing, making them ideal for workloads that involve matrix-heavy and high-throughput computations, such as AI training. They are also more power-efficient for these tasks compared to CPUs. However, GPUs do not outperform CPUs in all areas, such as clock speed or branch prediction, which are more relevant to sequential, general-purpose tasks.

  • A. Correct.

    Correct: GPUs are designed with thousands of smaller, efficient cores that excel at handling parallel computations like matrix operations, which are common in AI and deep learning tasks.

  • B. Correct.

    Correct: GPUs are optimized for high-throughput workloads, making them more power-efficient for AI training tasks compared to general-purpose CPUs.

  • C. Incorrect.

    Incorrect: While GPUs can be faster for parallel workloads, CPUs often have higher clock speeds than GPUs. The performance benefit of GPUs comes from their parallel architecture, not clock speed.

  • D. Correct.

    Correct: GPUs are purpose-built for high-throughput tasks such as AI training and deep learning, making them a better choice for these types of workloads.

  • E. Incorrect.

    Incorrect: CPUs generally have more advanced branch prediction capabilities, which are critical for sequential tasks. This feature is not relevant to the parallel nature of GPU workloads.

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