NCP-AIN NVIDIA-Certified Professional AI Networking Questions and Answers

To enable SHARP (Scalable Hierarchical Aggregation and Reduction Protocol) aggregation using theNCCL-SHARP plugin, the following two environment variables are required:

NCCL_COLLNET_ENABLE=1

Enables NCCL’s support for CollNet (Collective Network) operations, including SHARP.

NCCL_SHARP_AUTOINIT=1

Automatically initializes the SHARP plugin when available, activating SHARP-based collectives.

From theNVIDIA NCCL User Guide – SHARP Plugin Section:

"NCCL_COLLNET_ENABLE must be set to enable collective network acceleration features."

"NCCL_SHARP_AUTOINIT enables automatic SHARP plugin integration at NCCL runtime."

Incorrect Options:

B. NCCL_ALGO=CollNet– This variable controls the algorithm used for collectives but does not enable SHARP.

C. NCCLSPECTRUM_ENABLE– This is not a documented NCCL variable.

TheNVIDIA UFM Cyber-AI Platformis specifically designed to enhance security and operational efficiency in InfiniBand data centers. It leverages AI-powered analytics to detect security threats, operational anomalies, and predict potential network failures. By analyzing real-time telemetry data, it identifies abnormal behaviors and performance degradation, enabling proactive maintenance and threat mitigation.​

This platform integrates with existing UFM Enterprise and Telemetry services to provide a comprehensive view of the network's health and security posture. It utilizes machine learning algorithms to establish baselines for normal operations and detect deviations that may indicate security breaches or hardware issues.​

MLNX_OFED (Mellanox OpenFabrics Enterprise Distribution) is an NVIDIA-tested and packaged version of the OpenFabrics Enterprise Distribution (OFED) for Linux. It provides the necessary drivers and tools to support InfiniBand and Ethernet interconnects using the same RDMA (Remote Direct Memory Access) and kernel bypass APIs. MLNX_OFED enables high-performance networking capabilities essential for AI clusters, including support for up to 400Gb/s InfiniBand and RoCE (RDMA over Converged Ethernet).​

Reference Extracts from NVIDIA Documentation:

"MLNX_OFED is an NVIDIA tested and packaged version of OFED that supports two interconnect types using the same RDMA (remote DMA) and kernel bypass APIs called OFED verbs – InfiniBand and Ethernet."​

"Up to 400Gb/s InfiniBand and RoCE (based on the RDMA over Converged Ethernet standard) over 10/25/40/50/100/200/400GbE are supported."​

According to theNVIDIA Spectrum-X Switch Operating System (SX_OS) Troubleshooting Guide, theSystem Status LED behavioris a critical indicator of the switch’s internal operational state.

From the document:

“The System Status LED will blink green during system initialization. If the LED continues blinking for more than 5 minutes, it indicates that the Onyx OS hasfailed to load properly. The system may be stuck in the boot process, or the file system may be corrupted.”

This blinking LED beyond normal initialization time indicates that the system has either encountered a failure during software boot or is unable to transition from bootloader to the OS runtime environment (i.e., Onyx).

Key causes include:

Corrupted or missing system files.

Failed firmware or OS upgrade attempts.

Boot device (e.g., eMMC or SSD) issues or corrupted partitions.

Technically, during power-on:

The switch performs POST (Power-On Self Test).

Then the Onyx OS attempts to load from the boot partition.

If the Onyx OS kernel or root filesystem is invalid, the system halts boot, and the LED remains in ablinking state, as no successful OS load confirmation is triggered.

Remediation Steps (as per NVIDIA guide):

Access the switch throughconsoleandmonitor boot logs.

UseONIE recoveryor re-flash a stable Onyx OS version.

Check system storage integrity using built-in diagnostics.

Exact Extract Reference:

Source: NVIDIA SX_OS 3.9.3000 Documentation

Topic: Troubleshooting System Status LED

Extract: "If the LED blinks for more than 5 minutes and the switch is not accessible via CLI, the Onyx software failed to load properly and recovery procedures must be initiated."

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In Cumulus Linux, configuring a bond interface with Link Aggregation Control Protocol (LACP) involves setting the bond mode to 'lacp'. The correct command to achieve this is:​

nv set interface bond1 bond mode lacp​

This command sets the bonding mode of 'bond1' to LACP, enabling dynamic link aggregation for increased bandwidth and redundancy.​

Reference Extracts from NVIDIA Documentation:

"To reset the link aggregation mode for bond1 to the default value of 802.3ad, run the nv set interface bond1 bond mode lacp command."​

FromNVIDIA Performance Tuning Guide (ib_write_bw Tool Usage):

"-S <SL>: Specifies the Service Level (SL) to use for the InfiniBand traffic. SL is used for setting priority and mapping to virtual lanes (VLs) on the IB fabric."

This flag is useful when testing QoS-aware setups or validating SL/VL mappings.

Incorrect Options:

A– No such flag for burst size.

B– -q defines number of QPs.

C– --rate or -R is used for rate-limiting.

TheNVIDIA DGX SuperPODis a turnkey AI supercomputing infrastructure designed for large-scale deep learning and high-performance computing workloads. It integrates multiple DGX systems with high-speed networking and storage solutions, providing a scalable and efficient platform for AI research institutions. The architecture supports rapid deployment and is optimized for training complex models, making it the ideal choice for environments demanding top-tier AI performance.​

The NVIDIA Spectrum-X Reference Architecture (RA) 1.0.1 is designed for Ethernet AI cloud deployments and includes the SN5600 Spectrum-4 switches and BlueField-3 SuperNICs. This architecture supports adaptive routing and DOCA programmable congestion control (PCC) for lossless RoCE traffic, optimizing performance for AI workloads.

The SN5600 switch offers 64 ports of 800GbE in a dense 2U form factor, providing high throughput and low latency essential for AI applications.

The NVIDIA Spectrum-X networking platform is an Ethernet-based solution optimized for AI workloads, combining Spectrum-4 switches, BlueField-3 SuperNICs, and advanced software to deliver high performance and low latency. Gathering telemetry data is critical for optimizing Spectrum-X networks, as it provides visibility into network performance, congestion, and potential issues. The question asks for the tool used to collect telemetry data in a Spectrum-X network.

According to NVIDIA’s official documentation, NVIDIA NetQ is the primary tool for gathering telemetry data in Ethernet-based networks, including those running on Spectrum-X platforms with Cumulus Linux or SONiC. NetQ is a network operations toolset that provides real-time monitoring, telemetry collection, and analytics for network health, enabling administrators to optimize performance, troubleshoot issues, and validate configurations. It collects detailed telemetry data such as link status, packet drops, latency, and congestion metrics, which are essential for Spectrum-X optimization.

Exact Extract from NVIDIA Documentation:

“NVIDIA NetQ is a highly scalable network operations tool that provides telemetry-based monitoring and analytics for Ethernet networks, including NVIDIA Spectrum-X platforms. NetQ collects real-time telemetry data from switches and hosts, offering insights into network performance, congestion, and connectivity. It supports Cumulus Linux and SONiC environments, making it ideal for optimizing Spectrum-X networks by providing visibility into key metrics like latency, throughput, and packet loss.”

—NVIDIA NetQ User Guide

This extract confirms that option C, NetQ, is the correct tool for gathering telemetry data in a Spectrum-X network. NetQ’s integration with Spectrum-X switches and its ability to collect and analyze telemetry data make it the go-to solution for network optimization tasks.

TheMINHOProuting protocol, while efficient in finding minimal paths, does not inherently prevent credit loops. This can lead to deadlocks in the network. In contrast, routing protocols like UPDOWN and FAT TREE are designed to avoid such loops, ensuring more reliable network operation.​

To enable RDMA over Converged Ethernet (RoCE) on a Cumulus switch, the correct command is:​

nv set qos roce enable on

This command configures the Quality of Service (QoS) settings to support RoCE, ensuring that the necessary parameters for lossless Ethernet are applied.​

The RDMA Shared Device Plugin is a critical component in the NicClusterPolicy custom resource for enabling Remote Direct Memory Access (RDMA) capabilities in Kubernetes clusters. RDMA allows for high-throughput, low-latency networking, which is essential for efficient GPU-to-GPU communication across nodes in AI workloads. By deploying the RDMA Shared Device Plugin, the cluster can leverage RDMA-enabled network interfaces, facilitating direct memory access between GPUs without involving the CPU, thus optimizing performance.​

Reference Extracts from NVIDIA Documentation:

"RDMA Shared Device Plugin: Deploy RDMA Shared device plugin. This plugin enables RDMA capabilities in the Kubernetes cluster, allowing high-speed GPU-to-GPU communication across nodes."​

"The RDMA Shared Device Plugin is responsible for advertising RDMA-capable network interfaces to Kubernetes, enabling pods to utilize RDMA for high-performance networking."​

The "What Just Happened" (WJH) service on Cumulus switches provides real-time visibility into network problems by monitoring various layers and components, including layer 1, layer 2, layer 3, tunnel, buffer, and Access Control List (ACL) related issues. WJH streams detailed and contextual telemetry data, enabling administrators to diagnose and troubleshoot network problems effectively.​

Reference Extracts from NVIDIA Documentation:

"WJH can monitor layer 1, layer 2, layer 3, tunnel, buffer and ACL related issues."​

"The WJH service enables you to diagnose network problems by looking at dropped packets."​

TheNVIDIA Network Operatoris designed to simplify and automate the deployment and management of networking components in Kubernetes clusters, particularly those utilizing NVIDIA Spectrum-X switches. It manages the installation and configuration of necessary drivers, plugins, and other networking resources to enable features like RDMA and GPUDirect RDMA, which are essential for high-performance AI workloads.​

By leveraging Kubernetes Custom Resource Definitions (CRDs) and the Operator Framework, the Network Operator ensures that networking components are consistently and correctly configured across the cluster, reducing manual intervention and potential configuration errors.​

The correct answer isPXN (Peer eXchange Network).

From theNVIDIA NCCL Documentation:

"PXN enables communication between GPUs connected via NVLink and NICs by treating the GPUs as a distributed switch. This architecture improves bandwidth utilization by enabling any GPU to communicate with the NIC via the shortest path available, even if it's not directly connected to the NIC."

This enhances GPU-to-NIC and NIC-to-GPU transfers, leveraging the NVLink topology. It significantly boosts performance in multi-GPU setups where not every GPU is directly connected to the NIC.

Other options:

Adaptive Routingis a fabric-level feature for dynamic path rerouting.

Graph Search Optimizationis used internally for topology modeling in NCCL.

SHARP v2is a switch-based collective acceleration method, unrelated to PXN.

NVIDIA BlueField Data Processing Units (DPUs)are integral to securing AI infrastructures, especially in environments requiring stringent data privacy and security measures. BlueField DPUs offload and accelerate critical infrastructure tasks such as encryption, firewall enforcement, and intrusion detection, thereby isolating sensitive data paths from potential threats.​

In the context of AI workloads, BlueField DPUs enable secure and efficient data movement between GPUs and storage systems, ensuring that sensitive information, like financial data, is protected during both training and inference processes. Their integration into NVIDIA's reference architectures provides a hardware root of trust, essential for maintaining data integrity and compliance with security standards.​

To upgrade the MLNX-OS on InfiniBand switches, the recommended procedure is as follows:​

Connect to the switch via SSH: Establish a secure shell connection to the switch using its management IP address.​

Fetch the MLNX-OS software image: Obtain the appropriate MLNX-OS software image from the official source or repository.​

Use the 'install' command to perform the upgrade: Execute the 'install' command on the switch to initiate the upgrade process with the fetched software image.​

This method ensures a smooth and efficient upgrade without the need for physical intervention or service disruption.​

Reference Extracts from NVIDIA Documentation:

"Click on Systems → MLNX-OS Upgrade. Select the desired upgrade method (e.g. 'Install from local file'). Select your image and click 'Install Image'."

Role-Based Access Control (RBAC)is implemented within NVIDIA's Unified Fabric Manager (UFM) to manage user permissions effectively. RBAC allows administrators toassign roles to users, each with specific permissions, ensuring that only authorized individuals can make changes to the fabric configuration. This structured approach to access control enhances security by limiting the potential for unauthorized modifications and streamlines the management of user privileges across the network.​