Configure Multi-Instance GPU (MIG): Practice Questions — Administration (NVIDIA-Certified Professional: AI Operations)

Configure Multi-Instance GPU (MIG) — Practice Questions This set of practice questions is designed to help candidates prepare for the Configure...

Configure Multi-Instance GPU (MIG) — Practice Questions

This set of practice questions is designed to help candidates prepare for the Configure Multi-Instance GPU (MIG) section of the NVIDIA-Certified Professional: AI Operations exam. Each question includes four options, the correct answer, and a brief explanation to reinforce key concepts.

  1. What is the primary benefit of enabling Multi-Instance GPU (MIG) on an NVIDIA A100 GPU?

    • A) Increasing the GPU clock speed for single workloads
    • B) Partitioning a single GPU into multiple isolated instances for concurrent workloads
    • C) Reducing power consumption by disabling unused GPU cores
    • D) Automatically optimizing GPU memory allocation for deep learning models

    Correct Answer: B

    Explanation: MIG allows a single physical GPU to be partitioned into multiple isolated GPU instances, enabling concurrent execution of multiple workloads with guaranteed resource isolation.

  2. Which command-line tool is used to configure MIG instances on supported NVIDIA GPUs?

    • A) nvidia-smi
    • B) kubectl
    • C) slurmctld
    • D) runai

    Correct Answer: A

    Explanation: The nvidia-smi tool provides commands to enable, configure, and manage MIG instances on supported GPUs.

  3. Before creating MIG instances, what is a necessary step to prepare the GPU?

    • A) Disable the GPU driver
    • B) Enable MIG mode on the GPU
    • C) Restart the Kubernetes cluster
    • D) Install Run:ai platform

    Correct Answer: B

    Explanation: MIG mode must be enabled on the GPU before creating and managing MIG instances.

  4. How many MIG instances can be created on a single NVIDIA A100 40GB GPU at maximum?

    • A) 2
    • B) 4
    • C) 7
    • D) 8

    Correct Answer: C

    Explanation: The NVIDIA A100 40GB GPU supports up to 7 MIG instances, each with isolated compute and memory resources.

  5. Which of the following is NOT a valid MIG instance profile?

    • A) 1g.5gb
    • B) 2g.10gb
    • C) 3g.20gb
    • D) 7g.40gb

    Correct Answer: D

    Explanation: Valid MIG profiles are named with the format ng.mb, where n is the number of GPU compute units and mb is the memory size in GB. There is no 7g.40gb profile; the maximum number of compute units per instance is 3g.

  6. What is the effect of deleting a MIG instance on a GPU?

    • A) It disables MIG mode on the GPU
    • B) It frees the allocated resources for reuse
    • C) It permanently reduces GPU memory
    • D) It restarts the GPU driver

    Correct Answer: B

    Explanation: Deleting a MIG instance releases the allocated GPU resources, making them available for new instances or workloads.

  7. Which Kubernetes feature is essential for scheduling workloads on specific MIG instances?

    • A) Node affinity
    • B) Persistent volumes
    • C) Device plugins
    • D) ConfigMaps

    Correct Answer: C

    Explanation: NVIDIA’s device plugin for Kubernetes enables the scheduler to recognize and assign workloads to specific MIG instances.

  8. What is the recommended practice when configuring MIG instances for AI workloads?

    • A) Create the largest possible MIG instance for all workloads
    • B) Partition the GPU into multiple smaller instances to maximize utilization
    • C) Disable MIG mode to maximize raw GPU performance
    • D) Use MIG only for non-AI workloads

    Correct Answer: B

    Explanation: Partitioning the GPU into multiple smaller MIG instances allows concurrent AI workloads to run efficiently, improving overall GPU utilization.

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Related topics:

#NVIDIA #MIG #AI-Operations #GPU-Administration #AI-Infrastructure

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