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  • [Aug-2026] Verified NVIDIA NCP-AIN Bundle Real Exam Dumps PDF [Q23-Q37]

[Aug-2026] Verified NVIDIA NCP-AIN Bundle Real Exam Dumps PDF [Q23-Q37]

Posted on August 31, 2026 By freedumps No Comments on [Aug-2026] Verified NVIDIA NCP-AIN Bundle Real Exam Dumps PDF [Q23-Q37]
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[Aug-2026] Verified NVIDIA NCP-AIN Bundle Real Exam Dumps PDF

NCP-AIN Dumps PDF New [2026] Ultimate Study Guide

NVIDIA NCP-AIN Exam Syllabus Topics:

Topic Details
Topic 1
  • Spectrum-X Configuration, Optimization, Security, and Troubleshooting: This section of the exam measures the skills of Network Performance Engineers and covers configuring, managing, and securing NVIDIA Spectrum-X switches. It includes setting performance baselines, resolving performance issues, and using diagnostic tools such as CloudAI benchmark, NCCL, and NetQ. It also emphasizes leveraging DPUs for network acceleration and using monitoring tools like Grafana and SNMP for telemetry analysis.
Topic 2
  • AI Network Architecture: This section of the exam measures the skills of AI Infrastructure Architects and covers the ability to distinguish between AI factory and AI data center architectures. It includes understanding how Ethernet and InfiniBand differ in performance and application, and identifying the right storage options based on speed, scalability, and cost to fit AI networking needs.
Topic 3
  • InfiniBand Configuration, Optimization, Security, and Troubleshooting: This section of the exam measures the skills of Data Center Network Administrators and covers the configuration and operational maintenance of NVIDIA InfiniBand switches. It includes setting up InfiniBand fabrics for multi-tenant environments, managing subnet configurations, testing connectivity, and using UFM to troubleshoot and analyze issues. It also focuses on validating rail-optimized topologies for optimal network performance.

 

NEW QUESTION 23
You are optimizing an InfiniBand network for AI workloads that require low-latency and high-throughput data transfers. Which feature of InfiniBand networks minimizes CPU overhead during data transfers?

 
 
 
 
Direct Memory Access (DMA) in InfiniBand networks allows data to be transferred directly between the memory of two devices without involving the CPU. This capability significantly reduces CPU overhead, lowers latency, and increases throughput, making it ideal for AI workloads that demand efficient data transfers.

NEW QUESTION 24
You are implementing a multi-tenant environment on your Spectrum-X switches for different departments in your organization. You need to ensure that eachdepartment’s network traffic is isolated and secure.
Which Spectrum-X security feature would be most effective in creating isolated network environments for each department?

 
 
 
 
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.
Reference: Cumulus Linux – VRF Support on Spectrum Switches

NEW QUESTION 25
As the network administrator for a large-scale AI research cluster, you are responsible for ensuring seamless data flow across an InfiniBand east-west fabric that interconnects hundreds of compute nodes.
Which tool would you use to trace and discover the network paths between nodes on this InfiniBand east-west fabric?

 
 
 
 
The ibnetdiscover utility is used to perform InfiniBand subnet discovery and outputs a human-readable topology file. GUIDs, node types, and port numbers are displayed, as well as port LIDs and node descriptions.
All nodes and links are displayed, providing a full topology. This utility can also be used to list the current connected nodes. The output is printed to the standard output unless a topology file is specified.
InfiniBand is a high-performance, low-latency interconnect technology used in AI and HPC data centers, particularly for east-west traffic between compute nodes in large-scale fabrics. Ensuring seamless data flow requires tools to troubleshoot and monitor the network, including the ability to trace and discover network paths between nodes. The question asks for the specific tool used to trace and discover paths in an InfiniBand fabric, which is a key task in InfiniBand troubleshooting.
According to NVIDIA’s official InfiniBand documentation, the ibnetdiscover tool is designed to discover and map the topology of an InfiniBand fabric, including the paths between nodes. It scans the fabric, queries the subnet manager, and generates a topology map that details the connections between switches, Host Channel Adapters (HCAs), and other devices. This tool is essential for verifying connectivity, identifying routing paths, and troubleshooting issues like misconfigured routes or link failures in large-scale InfiniBand fabrics.
Exact Extract from NVIDIA Documentation:
“The ibnetdiscover tool is used to discover the InfiniBand fabric topology and generate a map of the network.
It queries the subnet manager to retrieve information about all nodes, switches, and links in the fabric, providing a detailed view of the paths between nodes. This tool is critical for troubleshooting connectivity issues and ensuring proper routing in InfiniBand networks.”
-NVIDIA InfiniBand Networking Guide
This extract confirms that ibnetdiscover is the correct tool for discovering network paths in an InfiniBand east- west fabric. It provides a comprehensive view of the fabric’s topology, enabling administrators to trace paths between compute nodes and ensure seamless data flow.
Reference:InfiniBand Fabric Utilities – NVIDIA Docs

NEW QUESTION 26
You’re troubleshooting a Spectrum-X network and notice that the System Status LED on a switch is blinking for more than 5 minutes. What is the most likely cause of this issue?

 
 
 
According to theNVIDIA Spectrum-X Switch Operating System (SX_OS) Troubleshooting Guide, the System 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 a blinking 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.”

NEW QUESTION 27
You are troubleshooting connectivity issues in your InfiniBand network and need to test basic connectivity between nodes. Which command should you use to test basic connectivity between InfiniBand nodes?

 
 
 
 
The tool specifically designed for testingInfiniBand connectivityis **ibping**. It functions similarly to the traditional ping utility but is optimized forInfiniBand fabrics.
From theNVIDIA InfiniBand Diagnostic Utilities Documentation:
“ibping tests the connectivity of InfiniBand nodes by sending management datagrams (MADs) and verifying the response from the destination LID or GUID.”
* Tests basicnode-to-nodereachability
* Supports testing viaLID, GUID, orport number
* Helps verify subnet manager routing and fabric health
Incorrect Options:
* pingandtracerouteare IP-based, not fabric-aware.
* ibnetdiscovermaps topology but doesn’t test live connectivity.
Reference: InfiniBand Diagnostic Tools – ibping

NEW QUESTION 28
You are managing a large InfiniBand fabric for an AI research cluster. You need to implement a solution that can proactively detect potential network issues and optimize performance.
Which feature of NVIDIA’s Unified Fabric Manager (UFM) is specifically designed to use AI-powered analytics for detecting security threats and predicting network failures in InfiniBand data centers?

 
 
 
 
Comprehensive and Detailed 150 to 250 words of Explanation From NVIDIA AI Networking Topics:
The correct answer is A. Cyber-AI platform . NVIDIA’s official UFM Cyber-AI documentation states that the UFM Cyber-AI platform determines a data center’s unique “vital signs” and uses them to identify performance degradation, component failures, and abnormal usage patterns . This directly matches the requirement for proactive detection of issues in a large InfiniBand fabric. NVIDIA also documents that Cyber- AI provides Link Anomaly detection and Link Failure Prediction , where machine learning models analyze monitoring information and predict future link failures 1 to 24 hours in advance . In addition, NVIDIA’s Cyber-AI materials describe integration with AI cybersecurity capabilities to help detect and mitigate security threats , which makes Cyber-AI the only option in this list that combines predictive analytics with security- oriented intelligence. By contrast, UFM Telemetry focuses on collecting and presenting real-time network data such as bandwidth, congestion, latency, and errors, while UFM Enterprise is the broader management platform and Host Agent is not the AI analytics engine for predictive failure and threat detection. Therefore, for AI-driven analytics, predictive maintenance, anomaly detection, and security-focused analysis in InfiniBand environments, Cyber-AI platform is the verified NVIDIA answer.

NEW QUESTION 29
Which service on Cumulus switches can monitor layer 1, layer 2, layer 3, tunnel, buffer, and ACL related issues?

 
 
 
 
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.”

NEW QUESTION 30
A financial services company is planning to implement an AI infrastructure to support real-time fraud detection and risk assessment. They need a solution that can handle both training and inference workloads while maintaining data privacy and security. Which NVIDIA reference architecture component would be most appropriate to address the data privacy and security concerns in this AI networking setup?

 
 
 
 
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.

NEW QUESTION 31
A cloud service provider is deploying the NVIDIA Spectrum-X Ethernet platform in a multi-tenant environment. To ensure the security and isolation of each tenant’s AI workload, the provider wants to implement a feature that prevents unauthorized access to the network. Which of the following features of the Spectrum-X platform should the provider implement?

 
 
 
 
In multi-tenant AI cloud environments, ensuring that each tenant’s workloads are isolated and secure is paramount. The NVIDIA Spectrum-X platform addresses this need through its Traffic Isolation capabilities. This feature ensures that network resources are partitioned effectively, preventing unauthorized access and interference between tenants. By implementing Traffic Isolation, the provider can maintain strict boundaries between different tenant environments, ensuring both security and performance consistency.

NEW QUESTION 32
Which of the following tools in Cumulus Linux is specifically useful for detecting and differentiating microbursts from regular network congestion? Pick the 2 correct responses below

 
 
 
 
In Cumulus Linux, microbursts are short-lived, high-volume traffic bursts that often go undetected by coarse-grained monitoring like SNMP.
The two tools specifically used for this purpose are:
What Just Happened (WJH)
“WJH provides real-time packet drop visibility and classifies drops by reason (e.g., congestion, ACLs, etc.), enabling microburst detection.” ASIC monitoring at millisecond granularity
“Deep telemetry is enabled via the switch ASIC, which provides sub-second counters that capture microburst patterns otherwise missed by SNMP.”

NEW QUESTION 33
Which of the following commands would you use to assign the IP address 20.11.12.13 to the management interface in SONiC?

 
 
 
 
In SONiC, to assign a static IP address to the management interface, the correct command is:
sudo config interface ip add eth0 20.11.12.13/24 20.11.12.254
This command sets the IP address and the default gateway for the management interface.
SONiC (Software for Open Networking in the Cloud) is an open-source network operating system used on NVIDIA Spectrum-X platforms, including Spectrum-4 switches, to provide a flexible and scalable networking solution for AI and HPC data centers. Configuring the management interface in SONiC is a critical task for enabling remote access and network management. The question asks for the correct command to assign the IP address 20.11.12.13 to the management interface, typically identified as eth0 in SONiC, as it is the default management interface for out-of-band management. Based on NVIDIA’s official SONiC documentation, the correct command to assign an IP address to the management interface involves using the config command-line utility, which is part of SONiC’s configuration framework. The command sudo config interface ip add eth0
20.11.12.13/24 20.11.12.254 is the standard method to configure the IP address and gateway for the eth0 management interface. This command specifies the interface (eth0), the IP address with its subnet mask (20.11.12.13/24), and the default gateway (20.11.12.254), ensuring proper network connectivity.

NEW QUESTION 34
You are deploying a Kubernetes cluster for AI workloads using NVIDIA Spectrum-X switches.
You need to automate the deployment and management of networking components in this environment. Which NVIDIA tool is specifically designed to automate the deployment and management of networking components in a Kubernetes cluster with Spectrum-X switches?

 
 
 
 
The NVIDIA Network Operator is 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 GPU Direct 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.

NEW QUESTION 35
You are configuring an InfiniBand network for an AI cluster and need to install the appropriate software stack. Which NVIDIA software package provides the necessary drivers and tools for InfiniBand configuration in Linux environments?

 
 
 
 
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.”

NEW QUESTION 36
A user has requested confirmation that the InfiniBand network is performing optimally and is not limiting the speed of a training run. To verify this, you would like to measure the RDMA throughput rate between two endpoints.
Which tool should be used?

 
 
 
 
The ib_write_bw tool is part of the Perftest package and is specifically designed to measure the bandwidth of RDMA write operations between two InfiniBand endpoints. It provides accurate assessments of RDMA throughput, which is crucial for verifying the performance of InfiniBand networks in high-performance computing and AI training environments.
Reference:ib_write_bw – NVIDIA Enterprise Support Portal

NEW QUESTION 37
Which command should be used to configure RoCE on a Cumulus switch?

 
 
 
 
Comprehensive and Detailed 150 to 250 words of Explanation From NVIDIA AI Networking Topics:
The correct answer is B. nv set qos roce enable on . In NVIDIA Cumulus Linux, RoCE configuration is managed under the QoS hierarchy in NVUE because RoCE depends on lossless Ethernet behavior, priority flow control, congestion management, and related quality-of-service mechanisms. NVIDIA’s official Cumulus Linux documentation shows that the RoCE feature is configured through nv set qos roce , and in newer command references this appears explicitly as nv set qos roce enable on|off . This confirms both the command structure and the ordering of the keywords: nv set # qos # roce # enable on .
The other options are incorrect because they do not follow valid NVUE syntax. NVIDIA documents NVUE commands in a strict object-based order, where the top-level feature group comes immediately after nv set .
Since RoCE is implemented as part of the QoS framework, qos must appear before roce . Commands such as nv set roce qos enable on , nv qos roce enable on , and nv roce qos enable on do not match the official NVIDIA command model. Therefore, for enabling RoCE on a Cumulus switch in an NVIDIA AI networking environment, the verified command is nv set qos roce enable on .

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