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| Certification Vendor: | NVIDIA |
|---|---|
| Exam Name: | NVIDIA-Certified Professional AI Infrastructure Exam |
| Exam Number: | NCP-AII |
| Available Languages: | English |
| 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) |
| Certificate Validity Period: | 2 years |
| Real Exam Qty: | 60-70 |
| Passing Score: | Pass/Fail only, no numerical score |
| Exam Format: | Scenario-based items, Multiple-choice questions |
| Exam Duration: | 120 minutes |
| Exam Price: | $400 USD |
| Recommended Training: | NVIDIA AI Infrastructure Training |
| Exam Registration: | NVIDIA Certification Portal |
| Sample Questions: | NVIDIA NCP-AII Sample Questions |
| 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/ |
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質問 # 186
Which of the following methods are considered the most reliable ways to install NVIDIA drivers on a production server running a stable Linux distribution (e.g., RHEL, CentOS, or Ubuntu LTS) to minimize downtime and ensure system stability?
正解：C、D、E
解説：
Using the distribution's package manager is generally the safest and most reliable method for installing NVIDIA drivers. This approach ensures that dependencies are managed correctly and updates are handled through the system's standard update mechanisms. Containerization isolates the driver and application dependencies. Nvidia's data center driver program provides enterprise-grade support and reliability. Running the .run installer directly can sometimes lead to dependency issues and conflicts. Building from source is complex and not generally recommended for production environments.
質問 # 187
Which protocol is commonly used in Spine-Leaf architectures for dynamic routing and load balancing across multiple paths?
正解：D
解説：
ECMP (Equal-Cost Multi-Path) is crucial for efficiently utilizing the multiple paths available in a Spine-Leaf architecture. It allows traffic to be distributed across these paths, improving throughput and reducing congestion. OSPF and BGP can be used for routing but do not inherently provide per-packet load balancing. STP is used to prevent loops, and VRRP provides router redundancy, neither of which directly address load balancing across multiple equal-cost paths.
質問 # 188
You are designing a storage solution for a multi-tenant AI cluster. Different teams will be running training jobs concurrently. Which of the following considerations are MOST important for ensuring fair resource allocation and preventing performance bottlenecks?
正解：C、E
解説：
Storage quotas prevent individual tenants from consuming excessive storage resources, while QOS policies ensure that each tenant receives a fair share of I/O bandwidth. Isolating tenants using separate storage namespaces or volumes prevents noisy neighbor effects, where one tenant's I/O -intensive workload impacts the performance of other tenants. A single large volume doesn't provide isolation. Prioritizing I/O based on privileges is generally not a fair approach in a multi-tenant environment.
質問 # 189
Which of the following statements accurately describe the benefits of using MIG (Multi-lnstance GPU) in an AI/HPC environment?
(Select all that apply)
正解：B、E
解説：
MIG allows partitioning a single GPU into multiple isolated instances, thus optimizing resource utilization (A). It provides hardware- level isolation, ensuring performance consistency and preventing interference between workloads (B). While MIG simplifies GPU sharing, it doesn't eliminate the need for all virtualization software, especially in more complex environments. MIG doesn't increase FLOPS (D); it divides the existing compute power. While different containers running on different MIG instances could have different CUDA versions, MIG itself doesn't directly handle this (E); this is handled via containers or environments.
質問 # 190
You are tasked with upgrading the NVIDIA driver on a Kubernetes node hosting GPU-accelerated A1 workloads. To minimize downtime and ensure a smooth transition, which sequence of steps should you follow?
正解：E
解説：
Cordoning the node prevents new pods from being scheduled on it. After upgrading the driver and rebooting, uncordoning the node allows Kubernetes to resume scheduling workloads. Draining the node before upgrading can cause unnecessary downtime if pods are migrated before the upgrade process starts. The NVIDIA container toolkit must be compatible to the NVIDIA driver, but the upgrade sequence follows Option C steps.
質問 # 191
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