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| Certification Vendor: | NVIDIA |
|---|---|
| Exam Name: | NVIDIA-Certified Professional AI Networking (NCP-AIN) Exam |
| Exam Number: | NCP-AIN |
| Exam Format: | Multiple choice questions, Single/multiple select items |
| Available Languages: | Chinese, English |
| Passing Score: | Pass/Fail only, no exact score published |
| Related Certifications: | NVIDIA-Certified Professional AI Operations (NCP-AIO) NVIDIA-Certified Professional AI Infrastructure (NCP-AII) |
| Certificate Validity Period: | 2 years |
| Exam Price: | $400 USD |
| Real Exam Qty: | 70-75 |
| Exam Duration: | 120 minutes |
| Recommended Training: | NVIDIA Spectrum Networking Training NVIDIA InfiniBand Essentials |
| Exam Registration: | NVIDIA Certification Portal |
| Sample Questions: | NVIDIA NCP-AIN Sample Questions |
| Exam Way: | Online remote proctored exam |
| Pre Condition: | 2โ3 years of data center operation experience with NVIDIA hardware; ability to deploy and manage AI networking infrastructure supporting AI workloads |
| Official Syllabus URL: | https://www.nvidia.com/en-us/learn/certification/ai-networking-professional/ |
>> Test NVIDIA NCP-AIN Quiz <<
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NEW QUESTION # 30
Which NVIDIA technology is specifically designed to provide high-performance networking for AI workloads?
Answer: C
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 # 31
When utilizing the ib_write_bw tool for performance testing, what does the -S flag define?
Answer: D
Explanation:
FromNVIDIA Performance Tuning Guide (ib_write_bw Tool Usage):
"-S <SL>: Specifies the Service Level (SL) to use for the InfiniBand traffic. SL is used for setting priority and mapping to virtual lanes (VLs) on the IB fabric." This flag is useful when testing QoS-aware setups or validating SL/VL mappings.
Incorrect Options:
* A- No such flag for burst size.
* B- -q defines number of QPs.
* C- --rate or -R is used for rate-limiting.
Reference: NVIDIA InfiniBand Performance Guide - ib_write_bw Options Section
NEW QUESTION # 32
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?
Answer: A
Explanation:
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 # 33
How does Spectrum-X achieve network isolation for multiple tenants?
Answer: C
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.
NEW QUESTION # 34
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.
Reference Extracts from NVIDIA Documentation:
* "RDMA Shared Device Plugin: Deploy RDMA Shared device plugin. This plugin enables RDMA capabilities in the Kubernetes cluster, allowing high-speed GPU-to-GPU communication across nodes."
* "The RDMA Shared Device Plugin is responsible for advertising RDMA-capable network interfaces to Kubernetes, enabling pods to utilize RDMA for high-performance networking."
NEW QUESTION # 35
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