RELIABLE NVIDIA NCP-AIO TEST SIMULATOR, FREE NCP-AIO EXAM

Reliable NVIDIA NCP-AIO Test Simulator, Free NCP-AIO Exam

Reliable NVIDIA NCP-AIO Test Simulator, Free NCP-AIO Exam

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NVIDIA AI Operations Sample Questions (Q39-Q44):

NEW QUESTION # 39
You are deploying a DOCA application for network monitoring on a DPU. You need to capture and analyze specific network packets based on certain criteri a. Which DOCA service would be most suitable for this task, and how would you configure it?

  • A. DOCA DPI: Use deep packet inspection to analyze packet content and extract relevant information for monitoring purposes.
  • B. DOCA Flow: Define flow rules to match specific packets and trigger actions such as mirroring or redirection for further analysis.
  • C. DOCA Comm Channel: Use Comm Channel for streaming packets from DPU to external monitoring entities.
  • D. DOCA Telemetry: Configure telemetry collectors to capture packet statistics and flow information, then analyze the collected data.
  • E. DOCA Memory Domain (MD): Use shared memory between the host and the DPU to transfer captured packets for analysis on the host.

Answer: B,D

Explanation:
DOCA Telemetry is designed for collecting and analyzing network statistics, making it suitable for network monitoring. DOCA Flow can also be used to selectively capture and redirect packets based on defined flow rules. DOCA DPI is for deep packet inspection. Comm Channel not for packet streaming. MD is for sharing memory.


NEW QUESTION # 40
Which command line utility can be used to verify the proper functioning of GPUDirect RDMA between two GPUs on different nodes?

  • A. nvidia-smi'
  • B. 'cuda-memcheck'
  • C. Ispci'
  • D. 'ibv devinfo'
  • E. rocminfo'

Answer: D

Explanation:
'ibv_devinfo' is a command-line utility (part of the InfiniBand Verbs library) that provides information about RDMA devices and their capabilities. This includes verifying that RDMA is enabled and configured correctly, which is essential for GPUDirect RDMA. 'nvidia-smi' monitors GPU status. 'rocminfo' is for AMD GPUs. 'cuda-memcheck' is for CUDA memory errors. 'Ispci' lists PCI devices, but it doesn't specifically verify RDMA functionality.


NEW QUESTION # 41
You are using BCM to manage a large cluster of GPU servers. You want to implement a mechanism to automatically scale the number of BCM instances based on the load. What Kubernetes feature would be MOST suitable for this purpose?

  • A. Cluster Autoscaler
  • B. Node Auto-Provisioning
  • C. Vertical Pod Autoscaler (VPA)
  • D. Horizontal Pod Autoscaler (HPA)
  • E. kube-scheduler

Answer: D

Explanation:
The Horizontal Pod Autoscaler (HPA) is the most suitable Kubernetes feature for automatically scaling the number of BCM instances (pods) based on resource utilization (e.g., CPU, memory). HPA monitors the resource usage of the BCM pods and automatically adjusts the number of replicas to maintain the desired resource levels. VPA adjusts the resource requests and limits of individual pods. Cluster Autoscaler adds or removes nodes from the cluster. Node Auto-Provisioning is related to node management. Kube-scheduler schedules pods onto nodes.


NEW QUESTION # 42
How can you ensure that all newly provisioned nodes in your BCM cluster automatically have the necessary NVIDIA drivers and container runtime installed?

  • A. Configure BCM to run a post-provisioning script that installs the drivers and runtime.
  • B. Manually install the drivers and runtime on each node after provisioning.
  • C. Create a custom OS image with the drivers and runtime pre-installed and use that image for provisioning.
  • D. Use a Kubernetes DaemonSet to install the drivers and runtime on each node after it joins the cluster.
  • E. Rely on the NVIDIA automatic driver installation tool after the OS is booted.

Answer: C,D

Explanation:
A custom OS image ensures drivers and runtime are present from the start. A post-provisioning script allows automated installation. Manual installation is not scalable. A DaemonSet installs software after the node joins the cluster, but BCM configuration happens at provisioning. The NVIDIA automatic driver installation tool might not be compatible with all BCM configurations.


NEW QUESTION # 43
You are using 'nvsm' to manage NVLink across multiple nodes. You need to ensure that the 'nvsm' service is automatically started on all nodes after a system reboot. Which of the following methods is the MOST reliable way to achieve this?

  • A. Use a systemd service unit file to manage the 'nvsm' service.
  • B. Create a cron job that runs at reboot to start the 'nvsm' service.
  • C. Manually start 'nvsm' after each reboot.
  • D. Add the 'nvsm' command to the '/etc/rc.locar file.
  • E. Place the 'nvsm' executable in the 'letc/init.dP directory.

Answer: A

Explanation:
Using a systemd service unit file is the most modern and reliable way to manage services on Linux systems. Systemd provides features like dependency management, automatic restarts, and logging, making it the preferred method for ensuring that 'nvsm' is started automatically after a reboot. "rc.local', '/etc/init.d' , and cron jobs are older methods that are less reliable or less well-integrated with modern systems.


NEW QUESTION # 44
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