Install Run:ai and Slurm: Practice Questions — Installation and Deployment (NVIDIA-Certified Professional: AI Operations)

Practice Questions: Installing Run:ai and Slurm for NVIDIA AI Operations

This set of multiple-choice questions is designed to help candidates prepare for the Installation and Deployment section of the NVIDIA-Certified Professional: AI Operations exam, focusing specifically on installing and configuring Run:ai and Slurm.

1. Which of the following is the primary purpose of Run:ai in an AI infrastructure environment?

   • A. Managing Kubernetes cluster networking
   • B. Providing a container runtime for AI workloads
   • C. Orchestrating AI workload scheduling and resource allocation
   • D. Monitoring GPU hardware health

   Correct Answer: C

   Explanation: Run:ai is a workload orchestration platform that optimizes scheduling and resource allocation for AI workloads, enabling efficient use of GPU clusters.

2. When installing Slurm on an NVIDIA AI cluster, which component is responsible for managing job queues and scheduling?

   • A. Slurmctld (Slurm controller daemon)
   • B. Slurmd (Slurm node daemon)
   • C. Slurmdbd (Slurm database daemon)
   • D. Slurmrestd (Slurm REST API daemon)

   Correct Answer: A

   Explanation: The Slurm controller daemon (slurmctld) manages job queues, scheduling, and overall cluster resource management.

3. Which command is typically used to initialize the Slurm configuration after installation on the cluster nodes?

   • A. slurm_init
   • B. scontrol reconfigure
   • C. slurm_start
   • D. slurm_setup

   Correct Answer: B

   Explanation: The scontrol reconfigure command reloads the Slurm configuration without restarting the daemons, applying any changes made.

4. During Run:ai installation, which of the following is a prerequisite to ensure proper integration with the existing cluster?

   • A. Installing the NVIDIA DOCA SDK on all nodes
   • B. Having a functioning Kubernetes cluster with configured nodes
   • C. Disabling Slurm job scheduling
   • D. Installing Base Command Manager (BCM) on the master node

   Correct Answer: B

   Explanation: Run:ai requires a properly installed and configured Kubernetes cluster to orchestrate AI workloads effectively.

5. Which file format is commonly used to define Slurm configuration settings during installation?

   • A. slurm.yaml
   • B. slurm.conf
   • C. slurm.json
   • D. slurm.xml

   Correct Answer: B

   Explanation: The slurm.conf file contains all the configuration parameters for Slurm, including nodes, partitions, and scheduling policies.

6. What is the recommended approach to synchronize container images when installing Run:ai in a multi-node environment?

   • A. Manually copy images to each node using SCP
   • B. Use a centralized container registry accessible by all nodes
   • C. Build images locally on each node
   • D. Use Slurm to distribute images

   Correct Answer: B

   Explanation: A centralized container registry ensures consistent and efficient image distribution across all cluster nodes.

7. Which Run:ai component is responsible for managing user quotas and access permissions during installation?

   • A. Run:ai Scheduler
   • B. Run:ai Controller
   • C. Run:ai Portal
   • D. Run:ai Resource Manager

   Correct Answer: C

   Explanation: The Run:ai Portal provides user management features, including quotas and role-based access control.

8. After installing Slurm and Run:ai, which tool can be used to verify that jobs are being scheduled correctly?

   • A. squeue
   • B. kubectl get pods
   • C. nvidia-smi
   • D. slurmctl status

   Correct Answer: A

   Explanation: The squeue command displays the status of jobs in the Slurm queue, confirming scheduling and execution.

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