NCP-AIN Exam Dumps - NVIDIA-Certified Professional Questions and Answers

The correct utility isibnetdiscover.

From the official NVIDIA InfiniBand Utilities Guide:

"ibnetdiscover scans the fabric and returns a topology of all switches and end nodes, including their GUIDs, LIDs, port numbers, and link speeds."

It generates a fabric map with node-to-port relationships and shows:

GUIDs

LIDs (Local IDs)

Link speeds and widths

Switch-to-host connections

This is essential for network topology validation and mapping physical port additions.

Incorrect Options:

ib_check_routes– for routing table diagnostics.

ibhosts– shows host information but not switch-level port mapping.

ibswitches– shows switch info, but lacks port-level LID/link speed mapping.

Virtual Routing and Forwarding (VRF)is the most effective method to achievenetwork segmentation and isolationin a multi-tenant environment.

From theNVIDIA Cumulus Linux Documentation – VRF Section:

"VRF allows multiple instances of routing tables to coexist within the same switch, effectively isolating traffic between tenants or departments."

Each department can:

Operate in its own VRF domain

Have independent routing tables

Maintain strict separation of Layer 3 paths

Incorrect Options:

A (Port Mirroring)– Used for traffic monitoring, not isolation.

C (ACLs)– Useful for fine-grained filtering, but not scalable tenant isolation.

D (LLDP)– Used for neighbor discovery, not security or isolation.

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.

For optimal performance in multi-node, multi-GPU AI workloads:

NVLinkprovides high-speed, low-latency communication between GPUs within the same node.

InfiniBandoffers efficient, scalable communication between nodes in a data center.Combining these technologies ensures both intra-node and inter-node communication needs are effectively met.​

A rail-optimized topology is designed to enhance GPU-to-GPU communication by connecting each GPU's Network Interface Card (NIC) to a dedicated rail switch. This configuration ensures predictable traffic patterns and minimizes network interference between data flows, which is crucial for the performance of large-scale AI workloads, such as training large language models. By reducing contention and latency, this topology supports efficient and scalable AI training environments.​

Reference Extracts from NVIDIA Documentation:

"Rail-optimized network topology helps maximize all-reduce performance while minimizing network interference between flows."​

"A Rail Optimized Stripe Architecture provides efficient data transfer between GPUs, especially during computationally intensive tasks such as AI Large Language Models (LLM) training workloads, where seamless data transfer is necessary to complete the tasks within a reasonable timeframe."​

AI workloads, particularly in large-scale training scenarios, are characterized by a small number of high-bandwidth, long-lived flows known as "elephant flows." These flows can dominate network traffic and are prone to causing congestion if not managed effectively.​

Traditional flow-based load balancing mechanisms, such as Equal-Cost Multipath (ECMP), distribute traffic based on flow hashes. However, in AI workloads with lowentropy (i.e., limited variability in flow characteristics), ECMP can lead to uneven traffic distribution and congestion on certain paths.​

Adaptive routing techniques, which dynamically adjust paths based on real-time network conditions, are more effective in managing AI traffic patterns and mitigating congestion risks.​

NVIDIA NetQ is a network operations tool that provides real-time visibility and automated validation of the network fabric. It helps in identifying misconfigurations, monitoring network health, and ensuring that the fabric meets the required specifications for AI workloads.​

NVIDIA AIR (AI-Ready Infrastructure) is a cloud-based simulation platform designed to model and validate data center network deployments, including Spectrum-X Ethernet networks, using realistic topologies and configurations. When creating a custom topology in NVIDIA AIR, users can define network links between devices (e.g., spine and leaf switches) using a DOT file format, which is based on the Graphviz graph visualization software. The question asks for the correct syntax to define a link between port 1 on a spine switch (spine-01) and port 41 on a leaf switch (gpu-leaf-01) in a NVIDIA AIR simulation.

According to NVIDIA’s official NVIDIA AIR documentation, the DOT file format is used to specify network topologies, including nodes (devices) and links (connections between ports). The syntax for defining a link in a DOT file uses a double dash (--) to indicate a connection between two ports, with each port specified in the format "":"". For Spectrum-X networks, which typically use Cumulus Linux or SONiC on NVIDIA Spectrum switches, ports are commonly labeled as swpX (switch port X) rather than ethX (Ethernet interface), especially for switch-to-switch connections in a leaf-spine topology. The correct syntax for the link between port 1 on spine-01 and port 41 on gpu-leaf-01 is:

"spine-01":"swp01" -- "gpu-leaf-01":"swp41"

This syntax uses swp01 and swp41 to denote switch ports, consistent with Cumulus Linux conventions, and the double dash (--) to indicate the link, as required by the DOT file format.

Exact Extract from NVIDIA Documentation:

“You can create custom topologies in Air using a DOT file, which is the file type used with the open-source graph visualization software, Graphviz. DOT files define nodes, attributes, and connections for generating a topology for a network. The following is an example of a link definition in a DOT file:

"leaf01":"swp31" -- "spine01":"swp1"

This specifies a connection between port swp31 on leaf01 and port swp1 on spine01. Port names typically follow the switch port naming convention (e.g., swpX) for Cumulus Linux-based switches.”

—NVIDIA Air Custom Topology Guide

This extract confirms that option A is the correct answer, as it uses the proper DOT file syntax with swp01 and swp41 for port names and the double dash (--) for the link, aligning with NVIDIA AIR’s topology definition process for Spectrum-X simulations.

Analysis of Other Options:

B. "spine-01":"swp1" to "gpu-leaf-01":"swp41": This option uses the correct port naming convention (swp1 and swp41) but incorrectly uses the word to as the connector instead of the double dash (--). The DOT file format requires -- to define links, making this syntax invalid for NVIDIA AIR.

C. "spine-01":"eth1" to "gpu-leaf-01":"eth41": This option uses ethX port names, which are typically used for host interfaces (e.g., servers) rather than switch ports in Cumulus Linux or SONiC environments. Switch ports in Spectrum-X topologies are labeled swpX. Additionally, the use of to instead of -- is incorrect for DOT file syntax, making this option invalid.

D. "spine-01":"eth1" - "gpu-leaf-01":"eth41": This option uses a single dash (-) instead of the required double dash (--) and incorrectly uses ethX port names instead of swpX. The ethX naming is not standard for switch ports in Spectrum-X, and the single dash is not valid DOT file syntax, making this option incorrect.

Why "spine-01":"swp01" -- "gpu-leaf-01":"swp41" is the Correct Answer:

Option A correctly adheres to the DOT file syntax used in NVIDIA AIR for defining network links:

Node and Port Naming: The nodes spine-01 and gpu-leaf-01 are specified with their respective ports swp01 and swp41, following the swpX convention for switch ports in Cumulus Linux-based Spectrum-X switches.

Link Syntax: The double dash (--) is the standard connector in DOT files to indicate a link between two ports, as required by Graphviz and NVIDIA AIR.

Spectrum-X Context: In a Spectrum-X leaf-spine topology, connections between spine and leaf switches (e.g., Spectrum-4 switches) use switch ports labeled swpX, making swp01 and swp41 appropriate for this simulation.

This syntax ensures that the NVIDIA AIR simulation accurately models the physical connection between spine-01 port 1 and gpu-leaf-01 port 41, enabling validation of the Spectrum-X network topology. The DOT file can be uploaded to NVIDIA AIR to generate the topology, as described in the documentation.

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.

To perform Flow Analysis with NetQ, the following prerequisites must be met:​

Cumulus Linux Version: NetQ Flow Analysis requires Cumulus Linux 5.x or later.​

Switch Hardware: The feature is supported on Spectrum-2 and later switch models.​

Lifecycle Management (LCM): LCM must be enabled to utilize Flow Analysis capabilities.​

These requirements ensure compatibility and proper functioning of the Flow Analysis feature within NetQ.​