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Perfect NCP-AIN Free Sample & Passing NCP-AIN Exam is No More a Challenging

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Perfect NCP-AIN Free Sample & Passing NCP-AIN Exam is No More a Challenging

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NVIDIA-Certified Professional AI Networking Sample Questions (Q20-Q25):NEW QUESTION # 20
As the network administrator for a large-scale AI research cluster, you are responsible for ensuring seamless data flow across an InfiniBand east-west fabric that interconnects hundreds of compute nodes.
Which tool would you use to trace and discover the network paths between nodes on this InfiniBand east-west fabric?
  • A. NetQ
  • B. ibnetdiscover
  • C. tracert
  • D. ibpathverify
Answer: B
Explanation:
The ibnetdiscover utility is used to perform InfiniBand subnet discovery and outputs a human-readable topology file. GUIDs, node types, and port numbers are displayed, as well as port LIDs and node descriptions.
All nodes and links are displayed, providing a full topology. This utility can also be used to list the current connected nodes. The output is printed to the standard output unless a topology file is specified.
InfiniBand is a high-performance, low-latency interconnect technology used in AI and HPC data centers, particularly for east-west traffic between compute nodes in large-scale fabrics. Ensuring seamless data flow requires tools to troubleshoot and monitor the network, including the ability to trace and discover network paths between nodes. The question asks for the specific tool used to trace and discover paths in an InfiniBand fabric, which is a key task in InfiniBand troubleshooting.
According to NVIDIA's official InfiniBand documentation, the ibnetdiscover tool is designed to discover and map the topology of an InfiniBand fabric, including the paths between nodes. It scans the fabric, queries the subnet manager, and generates a topology map that details the connections between switches, Host Channel Adapters (HCAs), and other devices. This tool is essential for verifying connectivity, identifying routing paths, and troubleshooting issues like misconfigured routes or link failures in large-scale InfiniBand fabrics.
Exact Extract from NVIDIA Documentation:
"The ibnetdiscover tool is used to discover the InfiniBand fabric topology and generate a map of the network.
It queries the subnet manager to retrieve information about all nodes, switches, and links in the fabric, providing a detailed view of the paths between nodes. This tool is critical for troubleshooting connectivity issues and ensuring proper routing in InfiniBand networks."
-NVIDIA InfiniBand Networking Guide
This extract confirms that ibnetdiscover is the correct tool for discovering network paths in an InfiniBand east- west fabric. It provides a comprehensive view of the fabric's topology, enabling administrators to trace paths between compute nodes and ensure seamless data flow.
Reference:InfiniBand Fabric Utilities - NVIDIA Docs

NEW QUESTION # 21
When upgrading DOCA on a BlueField DPU, what command should first be run on the host?
  • A. sudo apt-get autoremove
  • B. sudo apt-get upgrade doca
  • C. /usr/sbin/ofed_uninstall.sh -force
  • D. sudo apt-get install doca
Answer: C
Explanation:
Before upgrading the DOCA SDK on aBlueField DPU, it ismandatory to uninstall the existing OFED driversto prevent compatibility conflicts.
From theNVIDIA DOCA Installation Guide:
"Before upgrading DOCA or BlueField-related software, you must remove existing OFED packages using: /usr/sbin/ofed_uninstall.sh -force." This ensures:
* Clean driver state
* No residual kernel modules or userspace libraries
* Proper registration of new DOCA/OFED versions
Incorrect Options:
* AandCmay not resolve conflicts.
* Dinstalls but doesn't remove conflicting packages.
Reference: DOCA SDK Installation - Uninstall OFED Requirement

NEW QUESTION # 22
Which of the following NCCL environment variables enable SHARP aggregation with NCCL when using the NCCL-SHARP plugin?
Pick the 2 correct responses below
  • A. NCCLSPECTRUM_ENABLE=1
  • B. NCCL_ALGO=CollNet
  • C. NCCL_COLLNET_ENABLE=1
  • D. NCCL_SHARP_AUTOINIT
Answer: C,D
Explanation:
To enable SHARP (Scalable Hierarchical Aggregation and Reduction Protocol) aggregation using theNCCL- SHARP plugin, the following two environment variables are required:
* NCCL_COLLNET_ENABLE=1
Enables NCCL's support for CollNet (Collective Network) operations, including SHARP.
* NCCL_SHARP_AUTOINIT=1
Automatically initializes the SHARP plugin when available, activating SHARP-based collectives.
From theNVIDIA NCCL User Guide - SHARP Plugin Section:
"NCCL_COLLNET_ENABLE must be set to enable collective network acceleration features."
"NCCL_SHARP_AUTOINIT enables automatic SHARP plugin integration at NCCL runtime." Incorrect Options:
* B. NCCL_ALGO=CollNet- This variable controls the algorithm used for collectives but does not enable SHARP.
* C. NCCLSPECTRUM_ENABLE- This is not a documented NCCL variable.
Reference: NCCL SHARP Plugin Guide & NCCL User Guide - Environment Variables Section

NEW QUESTION # 23
A major cloud provider is designing a new data center to support large-scale AI workloads, particularly for training large language models. They want to optimize their network architecture for maximum performance and efficiency.
Why is a rail-optimized topology considered a best practice for AI network architecture in this scenario?
  • A. It provides optimal GPU-to-GPU communication and reduces network interference between flows.
  • B. It simplifies network management by using a single large switch for all connections.
  • C. It prioritizes north-south traffic over east-west traffic for better internet connectivity.
  • D. It maximizes the number of network hops to increase data redundancy.
Answer: A
Explanation:
A rail-optimized topology is designed to enhance GPU-to-GPU communication by connecting each GPU's Network Interface Card (NIC) to a dedicated rail switch. This configuration ensures predictable traffic patterns and minimizes network interference between data flows, which is crucial for the performance of large-scale AI workloads, such as training large language models. By reducing contention and latency, this topology supports efficient and scalable AI training environments.
Reference Extracts from NVIDIA Documentation:
* "Rail-optimized network topology helps maximize all-reduce performance while minimizing network interference between flows."
* "A Rail Optimized Stripe Architecture provides efficient data transfer between GPUs, especially during computationally intensive tasks such as AI Large Language Models (LLM) training workloads, where seamless data transfer is necessary to complete the tasks within a reasonable timeframe."

NEW QUESTION # 24
What is the total throughput of the SN5600 Spectrum-X switch?
  • A. 25.6 terabits per second
  • B. 102.4 gigabits per second
  • C. 51.2 terabits per second
  • D. 12.8 petabits per second
Answer: C
Explanation:
The SN5600 smart-leaf/spine/super-spine switch offers 64 ports of 800GbE in a dense 2U form factor. The SN5600 offers diverse connectivity in combinations of 1 to 800GbE and boasts an industry-leading total throughput of 51.2Tb/s.
Reference:NVIDIA Spectrum SN5600 Ethernet Switch - Bluum

NEW QUESTION # 25
......
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