Question 6 of 66

You are managing a Slurm cluster with multiple GPU nodes, each equipped with different types of GPUs. Some jobs are being allocated GPUs that should be reserved for other purposes, such as display rendering.
How would you ensure that only the intended GPUs are allocated to jobs?
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Question 7 of 66

A data scientist is training a deep learning model and notices slower than expected training times. The data scientist alerts a system administrator to inspect the issue. The system administrator suspects the disk IO is the issue.
What command should be used?
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The suggested answer is B.

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Question 8 of 66

You have noticed that users can access all GPUs on a node even when they request only one GPU in their job script using --gres=gpu:1. This is causing resource contention and inefficient GPU usage.
What configuration change would you make to restrict users’ access to only their allocated GPUs?
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Question 9 of 66

A new researcher needs access to GPU resources but should not have permission to modify cluster settings or manage other users.
What role should you assign them in Run:ai?
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Question 10 of 66

When troubleshooting Slurm job scheduling issues, a common source of problems is jobs getting stuck in a pending state indefinitely.
Which Slurm command can be used to view detailed information about all pending jobs and identify the cause of the delay?
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The suggested answer is A.

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