NVIDIA AI Infrastructure: NCP-AII Exam


"NVIDIA AI Infrastructure", also known as NCP-AII exam, is a NVIDIA Certification. With the complete collection of questions and answers, PrepAwayPDF has assembled to take you through 197 Q&As to your NCP-AII Exam preparation. In the NCP-AII exam resources, you will cover every field and category in NVIDIA-Certified Professional Certification helping to ready you for your successful NVIDIA Certification.

  • Exam Code: NCP-AII
  • Exam Name: NVIDIA AI Infrastructure
  • Total Questions: 197

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NVIDIA NCP-AII Exam Overview:

Certification Vendor:NVIDIA
Exam Name:NVIDIA-Certified Professional AI Infrastructure Exam
Exam Number:NCP-AII
Certificate Validity Period:2 years
Exam Format:Scenario-based items, Multiple-choice questions
Real Exam Qty:60-70
Related Certifications:NVIDIA-Certified Associate AI Infrastructure and Operations (NCA-AIIO)
NVIDIA-Certified Professional AI Networking (NCP-AIN)
NVIDIA-Certified Professional AI Operations (NCP-AIO)
Available Languages:English
Passing Score:Pass/Fail only, no numerical score
Exam Duration:120 minutes
Exam Price:$400 USD
Recommended Training:NVIDIA AI Infrastructure Training
Exam Registration:NVIDIA Certification Portal
Sample Questions: DOWNLOAD DEMO
Exam Way:Online remote proctored or onsite at authorized test centers
Pre Condition:No mandatory prerequisites; recommended 2–3 years of experience in data center infrastructure, Linux administration, and NVIDIA hardware/software environments
Official Syllabus URL:https://www.nvidia.com/en-us/learn/certification/ai-infrastructure-professional/

NVIDIA NCP-AII Exam Syllabus Topics:

SectionWeightObjectives
System and Server Bring-up20%- Firmware and system configuration
  • 1. BMC, BIOS, TPM and firmware updates
    • 2. OS installation and base configuration
      - Hardware installation and validation
      • 1. Server, GPU, network and storage components setup
        • 2. Power, cooling and physical connectivity verification
          Software Stack Deployment25%- NVIDIA software components
          • 1. Base Command Manager and cluster management tools
            • 2. GPU drivers, container toolkit and runtime
              - Orchestration and workload management
              • 1. Slurm, Kubernetes and container orchestration
                • 2. NGC catalog and software deployment
                  Validation, Troubleshooting and Optimization20%- Troubleshooting and maintenance
                  • 1. Performance optimization and best practices
                    • 2. Hardware and software fault isolation
                      - Cluster validation and benchmarking
                      • 1. HPL, NCCL and performance testing
                        • 2. Health checks and error detection
                          GPU Resource Management15%- Multi-Instance GPU (MIG) configuration
                          • 1. Partitioning and resource allocation
                            • 2. Isolation and performance tuning
                              - GPU scheduling and optimization
                              • 1. NVLink and fabric management
                                • 2. Workload placement and sharing
                                  Networking and Storage Configuration20%- Storage integration
                                  • 1. Parallel file systems and object storage
                                    • 2. Storage performance for AI workloads
                                      - NVIDIA networking solutions
                                      • 1. InfiniBand and Ethernet fabric setup
                                        • 2. BlueField DPU configuration

                                          NVIDIA AI Infrastructure Exam: Answers Before You Commit

                                          NVIDIA AI Infrastructure is an official NVIDIA exam, identified by exam code NCP-AII. Passing it earns the NVIDIA-Certified Professional AI Infrastructure certification at the Professional level. It also relates to NVIDIA-Certified Associate AI Infrastructure and Operations (NCA-AIIO), NVIDIA-Certified Professional AI Operations (NCP-AIO), NVIDIA-Certified Professional AI Networking (NCP-AIN). Certifications like this one remain a reliable route to standing out: they prove ability in a way resumes alone cannot.

                                          The NVIDIA AI Infrastructure exam contains 60-70 questions to complete within 120 minutes. The candidates who run out of time are usually the ones who never practiced against a clock. The PrepAwayPDF software engine lets you limit your test time exactly like the real exam, exposing pacing weaknesses while they are still free to fix.

                                          You need Pass/Fail only, no numerical score to pass NVIDIA AI Infrastructure, and the official registration fee is $400 USD. Retakes charge the full $400 USD again, which makes failing a genuinely expensive outcome. Reduce that risk the rational way: practice with the PrepAwayPDF questions until your scores sit consistently above the requirement, then book.

                                          No mandatory prerequisites; recommended 2–3 years of experience in data center infrastructure, Linux administration, and NVIDIA hardware/software environments

                                          Vendor requirements change from time to time, so verify the current conditions before registering via the official exam page.

                                          Registration for NVIDIA AI Infrastructure runs through the official channels below.

                                          One practical note: the exam is delivered Online remote proctored or onsite at authorized test centers.

                                          NVIDIA recommends the following training for NVIDIA AI Infrastructure candidates.

                                          Whatever training you take, anchor it with the 197 practice questions in the PrepAwayPDF NCP-AII package, each with a detailed explanation that turns every mistake into a lesson.

                                          Yes. You can download the free demo of the NVIDIA AI Infrastructure questions before you buy, and after purchase you have the right to one year of free updates. When your product expires, extending the update service costs 50% of the regular price. Three versions, PDF, software, and online APP, let you study the way that suits you.

                                          A 100% money-back guarantee protects you under clear conditions. Take the NVIDIA AI Infrastructure exam within 60 days of purchase; if you fail, you can claim a full refund, provided the exam matches your product. Attempts within 3 days of purchase are ineligible, as are downloaded-but-unused products, free materials, and expired orders; the candidate name must match the payer name. Submit a scanned enrollment slip and the official Score Report PDF within 2 days of the exam, and claims are processed within 7 days. Alternatively, exchange for two other exam products of equal value, free, while keeping the update service on your original purchase.

                                          Delivery is instant: files unlock for download at payment and are automatically emailed within one minute. If nothing arrives within 2 hours, check spam and contact customer service, available 24/7. Installation is unlimited across your computers.

                                          The NVIDIA AI Infrastructure syllabus divides into 5 domains. The leading areas are GPU Resource Management (15%), Software Stack Deployment (25%), and Networking and Storage Configuration (20%). The complete outline is published above; knowing your shortcomings starts with knowing the syllabus.

                                          NVIDIA AI Infrastructure Sample Questions:

                                          A data scientist wants to run a PyTorch container on docker using a Multi-Instance GPU (MIG) slice. Based on the requirements, the system administrate suggests using a MIG slice with 2g compute profile and 10GB of GPU memory. What command should the administrator tell the data scientist to run?

                                          • A. docker run --gpus '"device0"' --mig "2" nvcr.io/nvidia/pytorch:20.11-py3 nvidia-smi -L
                                          • B. docker run --mig '"device=0:2g.10gb" nvcr.io/nvidia/pytorch:20.11-py nvidia-smi -L
                                          • C. docker run --mig '"device=0:2"' nvcr.io/nvidia/pytorch:20.11-py3 nvidia-smi -L
                                          • D. docker run --gpus '"device=0:2"' nvcr.io/nvidia/pytorch:20.11-py3 nvidia-smi -L
                                          Reveal Solution  Discussion  0

                                          Correct Answer: D  🗳️

                                          Explanation: Only visible for PrepAwayPDF members. You can sign-up / login (it's free).

                                          A company has a registered NGC account and their server has NCG CLI installed. What step should be taken first to gain access to NGC?

                                          • A. ngc config set
                                          • B. ngc config update
                                          • C. ngc config get
                                          • D. ngc init
                                          Reveal Solution  Discussion  0

                                          Correct Answer: A  🗳️

                                          Explanation: Only visible for PrepAwayPDF members. You can sign-up / login (it's free).

                                          A user wants to restrict a Docker container to use only GPUs 0 and 2. Which command achieves this?

                                          • A. docker run -e NVIDIA_VISIBLE_DEVICES=0.2 nvidia/cuda:12.1-base nvidia-smi
                                          • B. docker run -device /dev/nvidia0./dev/nvidia2 nvidia/cuda:12.1-base nvidia-smi
                                          • C. docker run -gpus "device=0.2" nvidia/cuda:12.1-base nvidia-smi
                                          • D. docker run -gpus all nvidia/cuda:12.1-base nvidia-smi -id=0,2
                                          Reveal Solution  Discussion  0

                                          Correct Answer: C  🗳️

                                          Explanation: Only visible for PrepAwayPDF members. You can sign-up / login (it's free).

                                          An infrastructure engineer is preparing a new AI cluster for production use, which relies on NVIDIA switches and high-speed optical transceivers for node connectivity. The team is finalizing network validation before launching large-scale training jobs. Why is it critical to confirm and align the firmware version on all switch transceivers prior to production?

                                          • A. To guarantee that hardware inventory tools can report serial numbers and manufacturer codes for asset management critical for future support and troubleshooting.
                                          • B. To allow the network operating system to automatically discover all connected transceivers with heterogeneous firmware.
                                          • C. To ensure stability, bandwidth, and compatibility across the cluster, avoiding link issues and performance loss.
                                          Reveal Solution  Discussion  0

                                          Correct Answer: C  🗳️

                                          Explanation: Only visible for PrepAwayPDF members. You can sign-up / login (it's free).

                                          A cluster administrator is preparing to update the firmware on a DGX H100 system, including the GPU tray (baseboard). What is the correct sequence of steps to perform a safe and successful firmware upgrade?

                                          • A. Update the BMC and skip the GPU tray and motherboard tray updates if the system appears healthy.
                                          • B. Stop all GPU activity, update and reboot the BMC, update motherboard and tray components, perform a cold reset, and verify completion.
                                          • C. Update the GPU tray first, then the motherboard tray, and reboot the BMC after all updates are complete.
                                          • D. Perform a cold reset, stop all GPU activity, update and reboot the BMC, update motherboard and tray components, and verify completion.
                                          Reveal Solution  Discussion  0

                                          Correct Answer: B  🗳️

                                          Explanation: Only visible for PrepAwayPDF members. You can sign-up / login (it's free).

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