NCP-AIO Exam Dumps : NVIDIA AI Operations

Comprehensive and Detailed Explanation From Exact Extract:

To optimize scheduling of multi-GPU jobs in Slurm, it is essential to correctly specify GPU requests in job scripts using--gres=gpu:and enable/configureSlurm’s backfill scheduler. Backfill allows smaller jobs to run opportunistically in gaps without delaying larger multi-GPU jobs, improving cluster utilization and reducing wait times for multi-GPU jobs. Proper configuration ensures efficient packing and priority handling of GPU resources.

=============

Comprehensive and Detailed Explanation From Exact Extract:

To diagnose disk IO performance issues, the system administrator should use theiostatcommand, which reports CPU statistics and input/output statistics for devices and partitions. It helps identify bottlenecks in disk throughput or latency affecting application performance.

tcpdumpis used for network traffic analysis, not disk IO.

nvidia-smimonitors NVIDIA GPU status but not disk IO.

htopshows CPU, memory, and process usage but provides limited disk IO details.

Therefore,iostatis the appropriate tool to assess disk IO performance and diagnose bottlenecks impacting training times.

=============

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.