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NVIDIA NCP-AIN Exam Syllabus Topics:

TopicDetails
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.

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NVIDIA-Certified Professional AI Networking Sample Questions (Q88-Q93):

NEW QUESTION # 88
How does NVIDIA's AI networking solution contribute to the success of deep learning models?

Answer: A

Explanation:
NVIDIA's AI networking solutions ensure that deep learning models are trained quickly and efficiently by providing high-bandwidth, low-latency networking for the large data sets required in training.


NEW QUESTION # 89
Which of the following scenarios would the Network Traffic Map in UFM be least useful for troubleshooting?

Answer: A

Explanation:
The Network Traffic Map in NVIDIA's Unified Fabric Manager (UFM) provides a visual representation of the network topology and traffic flows, which is particularly useful for identifying congestion points, verifying network configurations, and optimizing workload distribution.
However, when troubleshooting a single node's hardware failure, the Network Traffic Map is less effective, as it focuses on network-level issues rather than individual hardware components.


NEW QUESTION # 90
When upgrading DOCA on a BlueField DPU, what command should first be run on the host?

Answer: A

Explanation:
Before upgrading the DOCA SDK on a BlueField DPU, it is mandatory to uninstall the existing OFED drivers to prevent compatibility conflicts.


NEW QUESTION # 91
What is the purpose of WJH (What Just Happened)?

Answer: C

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 # 92
You are troubleshooting a Spectrum-X network and need to ensure that the network remains operational in case of a link failure. Which feature of Spectrum-X ensures that the fabric continues to deliver high performance even if there is a link failure?

Answer: B

Explanation:
RoCE Adaptive Routing is a key feature of NVIDIA Spectrum-X that ensures high performance and resiliency in the network, even in the event of a link failure. This technology dynamically reroutes traffic to the least congested and operational paths, effectively mitigating the impact of link failures. By continuously evaluating the network's egress queue loads and receiving status notifications from neighboring switches, Spectrum-X can adaptively select optimal paths for data transmission. This ensures that the network maintains high throughput and low latency, crucial for AI workloads, even when certain links are down.


NEW QUESTION # 93
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