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| Topic | Details |
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| Topic 1 | - 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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| 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.
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| Topic 3 | - 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.
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NVIDIA-Certified Professional AI Networking test dumps & exam questions for NVIDIA NCP-AIN
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NVIDIA-Certified Professional AI Networking Sample Questions (Q46-Q51):
NEW QUESTION # 46
In Cumulus Linux, which technology enables the ability to provide active-active redundancy to servers, without the need for direct inter-switch links?
- A. EVPN Multi-homing
- B. VSS
- C. MLAG
Answer: A
Explanation:
EVPN Multi-homingenablesactive-active redundancy without inter-switch links by using overlay routing over VXLAN and distributed control plane using BGP EVPN.
NEW QUESTION # 47
In order to configure RoCE on a Cumulus switch, which command should be used?
- A. nv set qos roce enable on
- B. nv roce qos enable on
- C. nv set roce qos enable on
- D. nv qos roce enable on
Answer: A
Explanation:
To enable RDMA over Converged Ethernet (RoCE) on a Cumulus switch, the correct command is:
nv set qos roce enable on
This command configures the Quality of Service (QoS) settings to support RoCE, ensuring that the necessary parameters for lossless Ethernet are applied.
NEW QUESTION # 48
You are tasked with configuring multi-tenancy using partition key (PKey) for a high-performance storage fabric running on InfiniBand. Each tenant's GPU server is allowed to access the shared storage system but cannot communicate with another tenant's GPU server.
Which of the following partition key membership configurations would you implement to set up multi- tenancy in this environment?
- A. Assign full membership to both GPU servers and storage system.
- B. Assign limited membership to both GPU servers and storage system.
- C. Assign limited membership PKey to the shared storage system and full membership PKey to each tenant's GPU servers.
- D. Assign full membership PKey to the shared storage system and limited membership PKey to each tenant's GPU servers.
Answer: D
Explanation:
To enforce strictmulti-tenancy, where:
* Tenant A's GPUcannot talk toTenant B's GPU
* But both can accessshared storage
The correct solution is:
* Storage system # Full PKey membership
* Each tenant's GPU # Limited PKey membership
From theNVIDIA InfiniBand P_Key Partitioning Guide:
"A port with limited membership can only communicate with full members of the same PKey. It cannot communicate with other limited members, even within the same partition." This isolates tenantsfrom each other, while allowingshared access to storage.
Incorrect Options:
* Apermits tenant-to-tenant communication.
* Bisolates everything, including access to storage.
* Cprevents GPU access to storage.
Reference: NVIDIA InfiniBand - Multi-Tenant PKey Partitioning Design
NEW QUESTION # 49
What does NVIDIA's GPU-accelerated networking primarily enable in AI/ML environments?
- A. Efficient data movement and communication between GPUs for faster AI model training and inference
- B. Enhanced data security for AI applications
- C. Reduced computational power for AI models
- D. Faster model creation
Answer: A
Explanation:
GPU-accelerated networking optimizes data movement across GPUs and other devices, ensuring that AI models are trained and deployed with minimal latency and maximum throughput.
NEW QUESTION # 50
Which NVIDIA technology is specifically designed to provide high-performance networking for AI workloads?
- A. Mellanox ConnectX
- B. CUDA
- C. TensorFlow
- D. CUDA-X AI
Answer: A
Explanation:
Mellanox ConnectX is a high-performance network interface card (NIC) that is optimized for data centers, providing low-latency and high-throughput networking, which is crucial for AI workloads.
NEW QUESTION # 51
......
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