NCP-AIO Exam Dumps : NVIDIA AI Operations

Comprehensive and Detailed Explanation From Exact Extract:

To restrict users’ access strictly to the GPUs allocated to their jobs, Slurm usescgroups (control groups)for resource isolation. Enabling device cgroup enforcement by settingConstrainDevices=yesincgroup.confenforces device access restrictions, ensuring jobs cannot access GPUs beyond those assigned.

Increasing memory allocation or setting job priorities does not restrict device access.

Modifying job scripts to request additional CPU cores does not limit GPU access.

Hence, enablingcgroup enforcement with ConstrainDevices=yesis the correct method to prevent users from accessing unallocated GPUs.

Comprehensive and Detailed Explanation From Exact Extract:

NVIDIA's Multi-Instance GPU (MIG) technology provideshardware-level isolationof critical GPU resources such as memory, cache, and compute units for each GPU instance. This ensures that workloads running in one instance are fully isolated and cannot interfere with the performance of workloads in other instances, supporting multi-tenancy without contention.

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Comprehensive and Detailed Explanation From Exact Extract:

To ensure continued operation of AI applications at the edge despite server failures, NVIDIA Fleet Command allows administrators toenable high availability (HA) for edge clusters. This HA configuration ensures redundancy and failover capabilities, so applications remain operational when an edge server goes down.

Over-the-air updates handle software patching but do not inherently provide failover. MIG manages GPU resource partitioning, not failover. Secure NFS supports storage redundancy but is not the primary solution for application failover.

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