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NVIDIA NCP-AIN Exam Overview:

Certification Vendor:NVIDIA
Exam Name:NVIDIA-Certified Professional: AI Networking (NCP-AIN)
Exam Number:NCP-AIN
Exam Duration:120 minutes
Exam Format:Multiple Choice
Certificate Validity Period:2 years
Available Languages:English
Exam Price:$400 USD
Related Certifications:NVIDIA-Certified Associate AI Infrastructure and Operations
NVIDIA-Certified Professional AI Operations
NVIDIA-Certified Professional AI Infrastructure
Passing Score:70%
Real Exam Qty:70-75
Recommended Training:NVIDIA Learning & Certification Hub
Exam Registration:NVIDIA Certification Portal
Sample Questions:NVIDIA NCP-AIN Sample Questions
Exam Way:Online, remote-proctored exam
Pre Condition:Recommended 2–3 years of hands-on experience in data center or networking environments using NVIDIA AI infrastructure and networking technologies.
Official Syllabus URL:https://www.nvidia.com/en-us/learn/certification/

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NVIDIA NCP-AIN Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 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.

NVIDIA-Certified Professional AI Networking Sample Questions (Q66-Q71):

NEW QUESTION # 66
Your organization is planning to utilize Ethernet for an upcoming AI project. Spectrum-X is the selected platform for this deployment, and Adaptive Routing is a key feature.
What are the requirements included in the Spectrum-X RA for adaptive routing?

Answer: B

Explanation:
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.


NEW QUESTION # 67
A leading AI research center is upgrading its infrastructure to support large language model projects.
The team is debating whether to implement a dedicated storage fabric for their AI workloads.
Which of the following best explains why a dedicated storage fabric is crucial for this AI network architecture?
Pick the 2 correct responses below

Answer: A,B

Explanation:
Modern AI training (especially with LLMs) requires extremely high-speed, parallel access to large datasets. A dedicated storage fabricseparates data I/O traffic from the training compute path and avoids contention.
FromNVIDIA DGX Infrastructure Reference Architectures:
"Dedicated storage networks eliminate I/O bottlenecks by providing low-latency, high-bandwidth access to distributed storage for large-scale training jobs."
"Parallel access to datasets is key for performance, especially in multi-node, multi-GPU AI clusters." Security (B)is important, but not the core reason for a storage fabric.
Cost (D)is typicallyincreased, not reduced, with dedicated fabrics.
Reference: NVIDIA BasePOD/AI Infrastructure Deployment Guidelines - Storage Section


NEW QUESTION # 68
A fabric administrator added new servers to a 40-port edge switch. The administrator now needs to gather and map the newly added ports' LIDs and LINK SPEED. Which of the following commands can be used for that purpose?

Answer: D

Explanation:
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.
Reference: NVIDIA InfiniBand Tools - ibnetdiscover Utility


NEW QUESTION # 69
Which of the following options correctly describes the difference between UFM Telemetry, UFM Enterprise, and UFM Cyber AI?

Answer: D

Explanation:
UFM Telemetry: Provides real-time monitoring and analysis of network performance, collecting data such as port counters and cable information to assess the health and efficiency of the network. UFM Enterprise: Focuses on comprehensive network management and optimization, enabling administrators to monitor, operate, and optimize InfiniBand scale-out computing environments effectively. UFM Cyber AI: Detects and mitigates network security threats by analyzing telemetry data to identify anomalies and potential security issues within the network infrastructure.


NEW QUESTION # 70
In an AI cluster using NVIDIA GPUs, which configuration parameter in the NicClusterPolicy custom resource is crucial for enabling high-speed GPU-to-GPU communication across nodes?

Answer: C

Explanation:
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.


NEW QUESTION # 71
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