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NVIDIA-Certified Professional AI Networking Sample Questions (Q64-Q69):

NEW QUESTION # 64
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?

A. NV IPAM
B. RDMA Shared Device Plugin
C. Secondary Network
D. OFED Driver

Answer: B

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 # 65
You are optimizing an InfiniBand network for AI workloads that require low-latency and high-throughput data transfers. Which feature of InfiniBand networks minimizes CPU overhead during data transfers?

A. SHARP
B. PKey
C. TCP/IP Offloading
D. Direct Memory Access (DMA)

Answer: D

Explanation:
Direct Memory Access (DMA) in InfiniBand networks allows data to be transferred directly between the memory of two devices without involving the CPU. This capability significantly reduces CPU overhead, lowers latency, and increases throughput, making it ideal for AI workloads that demand efficient data transfers.

NEW QUESTION # 66
You are configuring an InfiniBand network for an AI cluster and need to install the appropriate software stack. Which NVIDIA software package provides the necessary drivers and tools for InfiniBand configuration in Linux environments?

A. CUDA Toolkit
B. MLNX_OFED
C. NVIDIA GPU Cloud
D. NVIDIA Container Runtime

Answer: B

Explanation:
MLNX_OFED (Mellanox OpenFabrics Enterprise Distribution) is an NVIDIA-tested and packaged version of the OpenFabrics Enterprise Distribution (OFED) for Linux. It provides the necessary drivers and tools to support InfiniBand and Ethernet interconnects using the same RDMA (Remote Direct Memory Access) and kernel bypass APIs. MLNX_OFED enables high-performance networking capabilities essential for AI clusters, including support for up to 400Gb/s InfiniBand and RoCE (RDMA over Converged Ethernet).
Reference Extracts from NVIDIA Documentation:
* "MLNX_OFED is an NVIDIA tested and packaged version of OFED that supports two interconnect types using the same RDMA (remote DMA) and kernel bypass APIs called OFED verbs - InfiniBand and Ethernet."
* "Up to 400Gb/s InfiniBand and RoCE (based on the RDMA over Converged Ethernet standard) over 10
/25/40/50/100/200/400GbE are supported."

NEW QUESTION # 67
When upgrading DOCA on a BlueField DPU, what command should first be run on the host?

A. sudo apt-get install doca
B. sudo apt-get upgrade doca
C. /usr/sbin/ofed_uninstall.sh -force
D. sudo apt-get autoremove

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 # 68
In order to configure RoCE on a Cumulus switch, which command should be used?

A. nv roce qos enable on
B. nv set qos roce enable on
C. nv set roce qos enable on
D. nv qos roce enable on

Answer: B

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.
Reference: NVIDIA Cumulus Linux Documentation - RDMA over Converged Ethernet (RoCE)

NEW QUESTION # 69
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NCP-AIN Latest Questions | Reliable NCP-AIN Dumps Sheet

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NVIDIA-Certified Professional AI Networking Sample Questions (Q64-Q69):

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