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Comprehensive and Detailed Explanation From Exact Extract:

In Slurm GPU resource management, thegres.conffile defines the available GPUs (generic resources) per node, whileslurm.confconfigures the cluster-wide GPU scheduling policies. To prevent jobs from using GPUs reserved for other purposes (e.g., display rendering GPUs), administrators must ensure that only the GPUs intended for compute workloads are listed in these configuration files.

Properly configuringgres.confallows Slurm to recognize and expose only those GPUs meant for jobs.

slurm.confmust be aligned to exclude or restrict unconfigured GPUs.

Manual GPU assignment usingnvidia-smiis not scalable or integrated with Slurm scheduling.

Reinstalling drivers or increasing GPU requests does not solve resource exclusion.

Thus, the correct approach is to verify and configure GPU listings accurately ingres.confandslurm.confto restrict job allocations to intended GPUs.

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Comprehensive and Detailed Explanation From Exact Extract:

For troubleshooting and performance optimization on NVIDIA DGX systems such as DGX H100, theNVIDIA System Management (nvsm)tool is used to gather system health and diagnostic data. The command nvsm dump health is the correct command to generate and export detailed system logs related to the health report of the DGX system.

nvsm show logs --save is not a recognized command format.

nvsm get logs retrieves logs but does not specifically dump the health report logs.

nvsm health --dump-log is not a standard documented nvsm command.

Therefore, nvsm dump health is the valid and documented command used to generate system logs focused on health reporting, useful for diagnosing performance issues in DGX H100 systems.

This usage aligns with NVIDIA’s system management tools guidance for DGX platforms as described in NVIDIA AI Operations documentation for troubleshooting and performance optimization.

Comprehensive and Detailed Explanation From Exact Extract:

Communication issues between UFM server and InfiniBand switches often result from misconfigured or missingsubnet manager configurationon the switches. The subnet manager controls fabric membership and routing, so verifying and correcting its setup is essential for proper UFM operation. Rebooting, adding GPUs, or disabling firewalls are less likely to resolve fabric-level communication problems.

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Comprehensive and Detailed Explanation From Exact Extract:

Core dumps capture thememory state of a process at the time of its crash, providing a snapshot useful for post-mortem debugging. Analyzing core dumps helps identify the cause of segmentation faults or other critical errors by revealing what the process was doing at failure, including stack traces, variable states, and memory content.

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Comprehensive and Detailed Explanation From Exact Extract:

The first step in troubleshooting Kubernetes pods that cannot detect GPUs is to verify whether theNVIDIA GPU Operatoris properly installed and running. The GPU Operator manages the installation and configuration of all NVIDIA GPU components in the cluster, including drivers, device plugins, and monitoring tools. Without it, pods will not have access to GPU resources. Ensuring correct installation and operational status of the GPU Operator is essential before checking application-level versions or resource allocations.

Comprehensive and Detailed Explanation From Exact Extract:

In an HA cluster, thefailover mechanismis responsible for detecting node failures and automatically transferring workloads to a standby or redundant node to maintain service availability. This process ensures mission-critical applications continue running without interruption. Load balancing helps distribute traffic but does not handle node failures. Manual intervention is not ideal for HA, and data replication ensures data integrity but does not itself manage workload continuity.

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Comprehensive and Detailed Explanation From Exact Extract:

The Slurm commandscontrol show job provides detailed information about a specific job, including its current status and, crucially, the reason why a job might be pending. This command shows job details such as resource requirements, dependencies, and any issues blocking the job from running.

sinfo -Rdisplays information about nodes and their reasons for being in various states but does not provide job-specific reasons.

sacct -jshows accounting data for jobs but typically does not explain pending causes.

squeue -ulists jobs by user but does not detail the pending reasons.

Hence,scontrol show job is the appropriate command to diagnose why a Slurm job remains in the pending state.

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Comprehensive and Detailed Explanation From Exact Extract:

In Slurm cluster administration, the command to submit a batch job script is sbatch. This command schedules the job to be executed by the Slurm workload manager. The option -begin=tomorrow (or --begin=tomorrow) specifies the start time for the job execution, which in this case is set for tomorrow. The other commands have different purposes:

submit is not a valid Slurm command.

salloc is used to allocate resources interactively but does not submit batch jobs for scheduled execution.

srun runs jobs immediately on allocated resources but is typically used to launch tasks in an active job or interactively, not for batch job submission.

Therefore, the correct command to submit a batch job script for future execution is sbatch -begin=tomorrow.

Comprehensive and Detailed Explanation From Exact Extract:

When configuring BCM for cloudbursting across multiple cloud providers such as AWS and Azure, it is necessary toconfigure separate credentials for each cloud providerwithin BCM. This allows BCM to authenticate and manage resources appropriately in each distinct cloud environment. BCM does not automatically replicate or detect credentials, nor can a single credential set typically work across providers.