NCP-AIO Sample Questions Answers

Comprehensive and Detailed Explanation From Exact Extract:

TheBase View dashboardin NVIDIA Base Command Manager provides a centralized and real-time overview of GPU, CPU, and memory utilization across all nodes in the DGX SuperPOD cluster. This tool allows administrators to quickly identify bottlenecks and resource usage patterns efficiently, unlike manually checking logs or running commands node-by-node.

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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:

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.

Comprehensive and Detailed Explanation From Exact Extract:

NVIDIA’s Base Command Manager is the software stack designed specifically for configuration, management, and monitoring of NVIDIA DGX systems, from a single DGX BasePOD up to large-scale SuperPOD deployments. It provides centralized management capabilities to orchestrate AI infrastructure, simplifying deployment, hardware monitoring, and lifecycle management across multiple clusters and data centers.

NetQ is focused on network monitoring and diagnostics rather than overall hardware cluster management.

Fleet Command is an enterprise SaaS solution to deploy and manage AI infrastructure in hybrid cloud environments but is not specifically targeted at on-premises DGX BasePOD to SuperPOD scale hardware management.

Magnum IO is NVIDIA’s high-performance data and storage software stack for managing I/O but not hardware or cluster configuration management.

Therefore, Base Command Manager is the correct and dedicated tool for managing multiple installations of NVIDIA DGX hardware spanning from BasePOD to SuperPOD environments.

This is consistent with NVIDIA’s official AI Operations documentation and product descriptions highlighting Base Command Manager as the unified command and control platform for AI infrastructure management.

Comprehensive and Detailed Explanation From Exact Extract:

Before pulling and running an NVIDIA NGC container on a stand-alone server, you must:

InstallDockerand theNVIDIA Container Toolkitto enable container runtime with GPU support.

Generate anNGC API keyand authenticate with the NGC container registry usingdocker loginto pull private or public containers.

Setting up Kubernetes or manually installing deep learning frameworks is unnecessary when using containers as they include the required frameworks.

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Comprehensive and Detailed Explanation From Exact Extract:

TheUFM Telemetryplatform provides basic network monitoring and validation capabilities, making it suitable for organizations that require foundational insight into their network status without advanced analytics or AI-driven cybersecurity features. Other platforms such as UFM Enterprise or UFM Pro offer broader or more advanced functionalities, while UFM Cyber-AI focuses on AI-driven cybersecurity.

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Comprehensive and Detailed Explanation From Exact Extract:

In Kubernetes architecture, thecontrol planeis composed of several core components including thekube-apiserver,etcd(the cluster’s key-value store),kube-scheduler, andkube-controller-manager. These manage the overall cluster state, scheduling, and orchestration of workloads. Theworker nodesare responsible for running the actual containers and include thekubelet(agent that communicates with the control plane) andkube-proxy(handles network routing for services). Other options incorrectly assign these components or roles.

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Comprehensive and Detailed Explanation From Exact Extract:

NVIDIA Fabric Manager manages the NVLink and NVSwitch fabric resources within HGX systems, enabling efficient resource allocation, communication, and virtualization necessary for AI/ML workloads. This is critical for virtualization as it ensures optimized interconnect performance between GPUs. Video encoding, graphical rendering, or memory upgrades are outside the scope of Fabric Manager.

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Comprehensive and Detailed Explanation From Exact Extract:

NVIDIAFleet Commandis the platform designed specifically to optimize and manage the deployment and delivery of AI applications at the edge. It enables secure and scalable orchestration of AI workloads across distributed edge devices, providing lifecycle management, remote monitoring, and updates. Fleet Command facilitates running AI applications closer to where data is generated (edge), improving latency and operational efficiency.

Base Command Platform and Base Command Manager primarily target data center and AI cluster management for configuration, monitoring, and troubleshooting.

NetQ is focused on network telemetry and network state monitoring rather than application delivery.

Therefore, for AI application delivery and optimization at the edge,Fleet Commandis the recommended NVIDIA platform.

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Comprehensive and Detailed Explanation From Exact Extract:

The pre-configured GPU Operator in the NVIDIA Enterprise Catalog differs from the public NGC catalog GPU Operator primarily by its configuration to use aprebuilt vGPU driver imageand being configured to use theNVIDIA License System (NLS). These adaptations allow better support for enterprise environments where vGPU functionality and license management are critical.

Other options such as automatic installation of the Datacenter driver or additional installation of Network Operator are not specific differences highlighted between the two operators.

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Comprehensive and Detailed Explanation From Exact Extract:

The commandngc config setis used to configure the NGC CLI, including setting up API keys, access tokens, and other credentials necessary for full access to the Base Command Platform (BCP) CLI functionalities. This command enables users to authenticate and manage their access effectively.

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:

Misconfiguration related toMIG modecan cause Slurm to improperly allocate GPUs, leading to job failures. The administrator should verify whether MIG has been enabled on the GPUs and ensure that Slurm’s configuration matches the hardware setup. If MIG is enabled, Slurm must be configured to recognize and schedule MIG partitions correctly to avoid resource conflicts.

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Comprehensive and Detailed Explanation From Exact Extract:

The NVIDIA Virtual Machine Image (VMI) for machine learning provisioning automatically sets up anUbuntu Serverenvironment with essential components including Docker-CE, NVIDIA Container Toolkit, CSP CLI, NGC CLI, NVIDIA Driver, andRapids—a suite of GPU-accelerated data science and analytics libraries. This comprehensive stack enables immediate development and deployment of ML workloads.

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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:

NVIDIA Fabric Manager is responsible for managing the fabric interconnect in HGX systems, including:

Configuring routing among NVSwitch ports (A)to optimize communication paths.

Coordinating with the NVSwitch driver to train NVSwitch-to-NVSwitch NVLink interconnects (C)for high-speed link setup.

Coordinating with the GPU driver to initialize and train NVSwitch-to-GPU NVLink interconnects (D)ensuring optimal connectivity between GPUs and switches.

Installing the GPU operator and vGPU driver is typically handled separately and not part of Fabric Manager’s core tasks.

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