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NVIDIA-Certified Professional AI Networking Sample Questions (Q27-Q32):

NEW QUESTION # 27
You are designing a new AI data center for a research institution that requires high-performance computing for large-scale deep learning models. The institution wants to leverage NVIDIA's reference architectures for optimal performance.
Which NVIDIA reference architecture would be most suitable for this high-performance AI research environment?

A. NVIDIA Base Command Platform
B. NVIDIA LaunchPad
C. NVIDIA DGX SuperPOD
D. NVIDIA DGX Cloud

Answer: C

Explanation:
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.
Reference:DGX SuperPOD Architecture - NVIDIA Docs

NEW QUESTION # 28
How does Spectrum-X achieve network isolation for multiple tenants?

A. By assigning unique IP address ranges to each tenant.
B. By implementing a Layer 3 Virtual Network Identifier (L3VNI) per VRR
C. By implementing physical network segmentation.
D. Using manual configuration of access control lists (ACLs).

Answer: B

Explanation:
Spectrum-X achieves network isolation in multi-tenant environments by implementing Layer 3 Virtual Network Identifiers (L3VNIs) per Virtual Routing and Forwarding (VRF) instance. This approach allows each tenant to have a separate routing table and network segment, ensuring that traffic is isolated and secure between tenants.
Reference Extracts from NVIDIA Documentation:
* "Spectrum-X enhances multi-tenancy with performance isolation to ensure tenants' AI workloads perform optimally and consistently."

NEW QUESTION # 29
You are concerned about potential security threats and unexpected downtime in your InfiniBand data center.
Which UFM platform uses analytics to detect security threats, operational issues, and predict network failures in InfiniBand data centers?

A. Telemetry Platform
B. Enterprise Platform
C. Host Agent
D. Cyber-AI Platform

Answer: D

Explanation:
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.
Reference:NVIDIA UFM Cyber-AI Documentation v2.9.1

NEW QUESTION # 30
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?

A. SN5600, BlueField-3 SuperNIC, DDR, TCP traffic
B. SN5600, BlueField-3 SuperNIC, DDR, RoCE traffic
C. SN4700, BlueField-3 SuperNIC, DDR, RoCE traffic

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 # 31
What is the purpose of WJH (What Just Happened)?

A. Provide contextual information regarding dropped packets in order to aid debugging.
B. Identify potential cyberattacks or unusual traffic patterns across the cluster.
C. Collate operating system logs and diagnose system crashes.
D. Send notifications of failed login attempts to a pre-defined Slack channel.

Answer: A

Explanation:
NVIDIA's What Just Happened (WJH) is a feature that provides real-time visibility into network problems by analyzing all packets passing through the switch and alerting on performance issues caused by packet drops, congestion, high latency, or misconfigurations.
WJH retains the last packets that were dropped from the switch with complete packet headers and the actual drop reason. This enhances the ability to debug network problems, identify affected flows, and decrease time- to-repair.

NEW QUESTION # 32
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New NCP-AIN Test Notes | Test NCP-AIN Cram Review

100% Pass 2025 High Pass-Rate NVIDIA NCP-AIN: New NVIDIA-Certified Professional AI Networking Test Notes

NVIDIA-Certified Professional AI Networking Sample Questions (Q27-Q32):

Pass Guaranteed Quiz NVIDIA - NCP-AIN - Updated New NVIDIA-Certified Professional AI Networking Test Notes

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