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| Certification Vendor: | NVIDIA |
|---|---|
| Exam Name: | NVIDIA-Certified Professional: AI Networking (NCP-AIN) |
| Exam Number: | NCP-AIN |
| Exam Duration: | 120 minutes |
| Real Exam Qty: | 70-75 |
| Available Languages: | English |
| Passing Score: | 70% |
| Exam Price: | $400 USD |
| Exam Format: | Multiple Choice |
| Related Certifications: | NVIDIA-Certified Professional AI Infrastructure NVIDIA-Certified Associate AI Infrastructure and Operations NVIDIA-Certified Professional AI Operations |
| Certificate Validity Period: | 2 years |
| 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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NEW QUESTION # 57
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: C
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 # 58
Why is the InfiniBand LRH called a local header?
Answer: D
Explanation:
TheLocal Route Header (LRH)in InfiniBand is termed "local" because it is used exclusively for routing packets within a single subnet. The LRH contains the destination and source Local Identifiers (LIDs), which are unique within a subnet, facilitating efficient routing without the need for global addressing. This design optimizes performance and simplifies routing within localized network segments.
InfiniBand is a high-performance, low-latency interconnect technology widely used in AI and HPC data centers, supported by NVIDIA's Quantum InfiniBand switches and adapters. The Local Routing Header (LRH) is a critical component of the InfiniBand packet structure, used to facilitate routing within an InfiniBand fabric. The question asks why the LRH is called a "local header," which relates to its role in the InfiniBand network architecture.
According to NVIDIA's official InfiniBand documentation, the LRH is termed "'local' because it contains the addressing information necessary for routing packets between nodes within the same InfiniBand subnet." The LRH includes fields such as the Source Local Identifier (SLID) and Destination Local Identifier (DLID), which are assigned by the subnet manager to identify the source and destination endpoints within the local subnet. These identifiers enable switches to forward packets efficiently within the subnet without requiring global routing information, distinguishing the LRH from the Global Routing Header (GRH), which is used for inter-subnet routing.
Exact Extract from NVIDIA Documentation:
"The Local Routing Header (LRH) is used for routing InfiniBand packets within a single subnet. It contains the Source LID (SLID) and Destination LID (DLID), which are assigned by the subnet manager to identify the source and destination nodes in the local subnet. The LRH is called a 'local header' because it facilitates intra-subnet routing, enabling switches to forward packets based on LID-based forwarding tables."
-NVIDIA InfiniBand Architecture Guide
This extract confirms that option A is the correct answer, as the LRH's primary function is to route traffic between nodes within the local subnet, leveraging LID-based addressing. The term "local" reflects its scope, which is limited to a single InfiniBand subnet managed by a subnet manager.
Reference:LRH and GRH InfiniBand Headers - NVIDIA Enterprise Support Portal
NEW QUESTION # 59
When utilizing the ib_write_bw tool for performance testing, what does the -S flag define?
Answer: A
Explanation:
From NVIDIA 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.
NEW QUESTION # 60
You are automating the deployment of a Spectrum-X network using Ansible. You need to ensure that the playbooks can handle different switch models and configurations efficiently.
Which feature of the NVIDIA NVUE Collection helps simplify the automation by providing pre-built roles for common network configurations?
Answer: A
Explanation:
The NVIDIA NVUE Collection for Ansible includes pre-built roles designed to streamline automation tasks across various switch models and configurations. These roles encapsulate common network configurations, allowing for efficient and consistent deployment.
By utilizing these roles, network administrators can:
* Apply standardized configurations across different devices.
* Reduce the complexity of playbooks by reusing modular components.
* Ensure consistency and compliance with organizational policies.
This approach aligns with Ansible best practices, promoting maintainability and scalability in network automation.
Reference: NVIDIA NVUE Collection Documentation - Ansible Roles
NEW QUESTION # 61
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: D
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 # 62
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