20:00

PDF|

Guide for NVIDIA-Certified Professional: AI Operations (NCP-AIO)

Quiz NVIDIA-Certified Professional: AI Operations (NCP-AIO)

Free Test
/ 10

Quiz

1/10
You are using Magnum IO NCCL (NVIDIA Collective Communications Library) for distributed deep
learning training across multiple GPUs. The training process is experiencing significant slowdowns
during inter-GPU communication. You notice that some GPUs report higher communication latency in
the NCCL logs. Upon closer inspection, the PCIe and NVLink usage metrics are within expected ranges,
but the IB fabric shows increased retransmissions. What is the most effective solution to improve
communication performance?
Select the answer
1 correct answer
A.
Adjust the InfiniBand MTU size to match the network's optimal configuration.
B.
Enable NCCL topology hints in the Magnum IO configuration.
C.
Increase the PCIe bandwidth allocation for each GPU.
D.
Reduce the batch size to decrease communication load.

Quiz

2/10
You are monitoring the performance of NVIDIA Base Command Manager (BCM) in your AI data center
and observe significant delays in job scheduling and execution. The logs reveal the following:
• High CPU utilization on the central BCM manager.
• Frequent disk I/O warnings on the central server.
• Normal network traffic between agents and the central manager.
Which of the following actions is the best approach to resolve this issue?
Select the answer
1 correct answer
A.
Add more GPUs to the compute nodes.
B.
Optimize disk I/O by migrating to NVMe-based storage for the central manager.
C.
Increase the timeout values in the agent configuration files.
D.
Upgrade the network switches to increase bandwidth.

Quiz

3/10
You are tasked with deploying an AI training workload on a Kubernetes cluster. The workload involves
GPU-intensive tasks, and the cluster contains both CPU and GPU nodes. How should you configure
Kubernetes to ensure the AI workload runs efficiently on GPU nodes?
Select the answer
1 correct answer
A.
Label the GPU nodes and use taints and tolerations to isolate them for AI workloads.
B.
Use node affinity to specify GPU nodes for the workload.
C.
Schedule the workload using default Kubernetes scheduling policies without modifications.
D.
Configure a Kubernetes Service to expose GPU nodes directly to the AI application.

Quiz

4/10
You are the administrator of a Slurm cluster used for high-performance computing workloads. The
cluster consists of nodes with varying configurations, and you need to update the slurm.conf file to
allocate nodes into specific partitions based on their memory and CPU configurations. Which of the
following steps should you take to ensure the changes are applied correctly?
Select the answer
1 correct answer
A.
Modify the slurm.conf file, then restart the Slurm daemons (slurmctld and slurmd) on all nodes.
B.
Update the slurm.conf file, then copy it manually to each compute node and restart slurmd on each node.
C.
Modify the slurm.conf file and wait for the Slurm daemons to automatically propagate the changes.
D.
Modify the slurm.conf file and run scontrol reconfigure on the primary Slurm controller.

Quiz

5/10
An AI workload involves training large models on terabytes of data stored in a shared file system. The
organization aims to minimize data access latency and maximize throughput during training. Which
storage solution is best aligned with this requirement?
Select the answer
1 correct answer
A.
Traditional storage architecture with CPU-based data transfer to GPUs.
B.
NVIDIA GPUDirect Storage integrated with a high-performance NVMe-based file system.
C.
In-memory caching of the entire dataset across multiple nodes.
D.
Direct GPU-to-GPU communication over RDMA without shared storage.

Quiz

6/10
You are administering an NVIDIA Fleet Command deployment for a multi-department organization. The
finance department requires access to specific dashboards for monitoring GPU utilization and cost
analytics, while the AI research team needs access to deploy and manage models across the
organization. As the administrator, how should you configure user access to meet these requirements
while maintaining security and least privilege principles? (Choose two)
Select the answer
2 correct answers
A.
Configure access policies at the GPU cluster level, giving the finance department read-only access and the research team full access.
B.
Assign the "Administrator" role to all users to simplify management.
C.
Create a single shared account for the finance and research teams to streamline access.
D.
Set up role-based access control (RBAC) to enforce permissions at the project level and assign users to the appropriate roles.
E.
Create two user roles: "Finance Viewer" and "Research Administrator," assigning appropriate permissions to each role.

Quiz

7/10
Your organization operates a data center running GPU-based systems for AI training. Energy costs are a
significant concern, and you aim to optimize power usage without sacrificing performance. Which of the
following strategies is most effective for managing GPU power consumption during training?
Select the answer
1 correct answer
A.
Reduce the GPU clock speeds permanently to minimize energy usage across all workloads.
B.
Use a software-based energy-saving mode that reduces the number of cores available on the GPU.
C.
Use NVIDIA's nvidia-smi tool to dynamically adjust the power limit based on the workload requirements.
D.
Set GPUs to their maximum power limit to ensure peak performance at all times.

Quiz

8/10
You are tasked with preprocessing a large dataset containing millions of rows and multiple categorical
and numerical features for training a machine learning model. Which of the following actions is the most
optimal approach using NVIDIA RAPIDS to handle the dataset effectively and prepare it for training?
Select the answer
1 correct answer
A.
Use cuDF to perform all preprocessing steps on the CPU to avoid GPU memory bottlenecks.
B.
Use cuDF to load the data into GPU memory and apply GPU-accelerated transformations such as filtering, encoding, and scaling.
C.
Use cuML for data preprocessing as it provides optimized methods for both numerical and categorical data transformations.
D.
Use pandas for initial data preprocessing steps, then transfer the data to cuDF for GPU-accelerated transformations.

Quiz

9/10
A company is developing autonomous drones for large-scale agricultural monitoring. As the AI
infrastructure architect, you must design a scalable system to handle the drone's real-time image
analysis and decision-making requirements. Which approach best ensures scalability, low latency, and
reliable real-time processing for this use case?
Select the answer
1 correct answer
A.
Offload all processing to third-party services for cost savings and simplified management.
B.
Use GPU clusters in the cloud exclusively for both training and inference, leveraging high network throughput.
C.
Deploy all image analysis tasks to a centralized cloud infrastructure using batch processing.
D.
Implement edge computing on each drone for image analysis, with periodic updates to the central cloud for training.

Quiz

10/10
You are an administrator managing an NVIDIA AI cluster that uses Slurm for workload scheduling. The
research team is experiencing delays in job execution due to inefficient scheduling policies. Your task is
to optimize the scheduling configuration to improve resource allocation while minimizing job wait times.
Which of the following configurations in Slurm is the most effective approach to prioritize job scheduling
and ensure fair resource allocation in a multi-user environment?
Select the answer
1 correct answer
A.
Enable the backfill scheduler and configure job priorities using the PriorityWeightFairShare parameter.
B.
Use PreemptionMode=kill to terminate low-priority jobs immediately when high-priority jobs are submitted.
C.
Set PriorityType=basic and allocate resources on a first-come, first-served basis.
D.
Disable backfill scheduling and rely solely on the default FIFO (first in, first out) scheduling policy.
Looking for more questions?Buy now

NVIDIA-Certified Professional: AI Operations (NCP-AIO) Practice test unlocks all online simulator questions

Thank you for choosing the free version of the NVIDIA-Certified Professional: AI Operations (NCP-AIO) practice test! Further deepen your knowledge on NVIDIA Simulator; by unlocking the full version of our NVIDIA-Certified Professional: AI Operations (NCP-AIO) Simulator you will be able to take tests with over 300 constantly updated questions and easily pass your exam. 98% of people pass the exam in the first attempt after preparing with our 300 questions.

BUY NOW

What to expect from our NVIDIA-Certified Professional: AI Operations (NCP-AIO) practice tests and how to prepare for any exam?

The NVIDIA-Certified Professional: AI Operations (NCP-AIO) Simulator Practice Tests are part of the NVIDIA Database and are the best way to prepare for any NVIDIA-Certified Professional: AI Operations (NCP-AIO) exam. The NVIDIA-Certified Professional: AI Operations (NCP-AIO) practice tests consist of 300 questions and are written by experts to help you and prepare you to pass the exam on the first attempt. The NVIDIA-Certified Professional: AI Operations (NCP-AIO) database includes questions from previous and other exams, which means you will be able to practice simulating past and future questions. Preparation with NVIDIA-Certified Professional: AI Operations (NCP-AIO) Simulator will also give you an idea of the time it will take to complete each section of the NVIDIA-Certified Professional: AI Operations (NCP-AIO) practice test . It is important to note that the NVIDIA-Certified Professional: AI Operations (NCP-AIO) Simulator does not replace the classic NVIDIA-Certified Professional: AI Operations (NCP-AIO) study guides; however, the Simulator provides valuable insights into what to expect and how much work needs to be done to prepare for the NVIDIA-Certified Professional: AI Operations (NCP-AIO) exam.

BUY NOW

NVIDIA-Certified Professional: AI Operations (NCP-AIO) Practice test therefore represents an excellent tool to prepare for the actual exam together with our NVIDIA practice test . Our NVIDIA-Certified Professional: AI Operations (NCP-AIO) Simulator will help you assess your level of preparation and understand your strengths and weaknesses. Below you can read all the quizzes you will find in our NVIDIA-Certified Professional: AI Operations (NCP-AIO) Simulator and how our unique NVIDIA-Certified Professional: AI Operations (NCP-AIO) Database made up of real questions:

Info quiz:

  • Quiz name:NVIDIA-Certified Professional: AI Operations (NCP-AIO)
  • Total number of questions:300
  • Number of questions for the test:50
  • Pass score:80%

You can prepare for the NVIDIA-Certified Professional: AI Operations (NCP-AIO) exams with our mobile app. It is very easy to use and even works offline in case of network failure, with all the functions you need to study and practice with our NVIDIA-Certified Professional: AI Operations (NCP-AIO) Simulator.

Use our Mobile App, available for both Android and iOS devices, with our NVIDIA-Certified Professional: AI Operations (NCP-AIO) Simulator . You can use it anywhere and always remember that our mobile app is free and available on all stores.

Our Mobile App contains all NVIDIA-Certified Professional: AI Operations (NCP-AIO) practice tests which consist of 300 questions and also provide study material to pass the final NVIDIA-Certified Professional: AI Operations (NCP-AIO) exam with guaranteed success. Our NVIDIA-Certified Professional: AI Operations (NCP-AIO) database contain hundreds of questions and NVIDIA Tests related to NVIDIA-Certified Professional: AI Operations (NCP-AIO) Exam. This way you can practice anywhere you want, even offline without the internet.

BUY NOW