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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Infrastructure Fundamentals | 15-20% | - Data center infrastructure requirements - NVIDIA software stack overview - GPU architecture basics - AI and Deep Learning concepts |
| Topic 2: Monitoring and Management | 15-20% | - Performance monitoring - Troubleshooting basics - Resource utilization - NVIDIA management tools |
| Topic 3: NVIDIA AI Infrastructure Components | 25-30% | - NVIDIA DGX systems - NVIDIA networking solutions (Mellanox) - Storage solutions for AI workloads - NVIDIA AI Enterprise software |
| Topic 4: Security and Best Practices | 10-15% | - Operational best practices - Compliance considerations - Security fundamentals |
| Topic 5: Deployment and Configuration | 25-30% | - Cluster configuration - Network configuration - Software deployment - System installation and setup |
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NEW QUESTION # 92
What is the purpose of using NCCL in verifying East-West fabric in an NVIDIA AI Factory?
Pick the 2 correct responses below.
Answer: A,D
Explanation:
NCCL is used to validate GPU communication behavior across the East-West fabric, so the correct answers are measuring latency between GPUs and measuring bandwidth between GPUs. NVIDIA describes NCCL as a topology-aware library of multi-GPU collective communication primitives, and NVIDIA GPU debug guidance specifically identifies NCCL performance tests, such as all_reduce_perf, as useful for establishing network performance between groups of nodes. In an AI Factory, East-West traffic is the server-to-server traffic used during distributed training. When models scale across many GPUs and nodes, operations such as all-reduce, broadcast, all-gather, and reduce-scatter depend on low latency and high bandwidth. NCCL testing helps confirm that GPU-to-GPU paths, GPUDirect RDMA, InfiniBand or Spectrum-X fabric behavior, routing, and collective communication performance are healthy before production workloads start. NCCL is not intended to measure storage performance; that requires storage benchmarks or GPUDirect Storage validation. It also does not measure GPU power consumption; that is handled by tools such as nvidia-smi, DCGM, or platform telemetry.
NEW QUESTION # 93
An A1 server is exhibiting unusually high CPU utilization during a GPU-accelerated workload. How can you determine if the CPU is becoming a bottleneck, preventing the GPUs from achieving their full potential?
Answer: E
Explanation:
All the options provide valid methods for identifying a CPU bottleneck. Monitoring CPU and GPU utilization, profiling the application, and running parallel benchmarks all help to determine if the CPU is limiting GPU performance.
NEW QUESTION # 94
A cluster administrator needs to validate transceiver firmware versions across 200 ports using UFM. Which GUI-based method provides a consolidated view?
Answer: C
Explanation:
Managing a large-scale AI fabric requires centralized visibility into the physical layer. The NVIDIAUnified Fabric Manager (UFM)provides a comprehensive Dashboard for InfiniBand networks. To check transceiver firmware-which is critical for ensuring feature parity and stability across the fabric-the administrator can use the UFM Enterprise GUI. By navigating to the "Devices" section and selecting a specific switch, the
"Cables" tab will aggregate telemetry for every occupied port. This view displays the manufacturer, part number, and the specific firmware version of the transceivers (LinkX) or Active Optical Cables (AOC). This consolidated view is far more efficient than manual CLI queries (Option C) for 200+ ports. Maintaining uniform firmware across transceivers ensures that optimizations like Adaptive Routing and Congestion Control perform consistently across the entire 400G or 200G fabric.
NEW QUESTION # 95
You are troubleshooting a network performance issue in your NVIDIA Spectrum-X based A1 cluster. You suspect that the Equal-Cost Multi-Path (ECMP) hashing algorithm is not distributing traffic evenly across available paths, leading to congestion on some links. Which of the following methods would be MOST effective for verifying and addressing this issue?
Answer: D
Explanation:
Switch telemetry tools provide the most direct and comprehensive way to monitor link utilization and identify imbalances in traffic distribution caused by ECMP. While 'ping' and 'traceroute' can provide path information, they don't give insight into traffic volume. Restarting the switches might temporarily alleviate the issue but doesn't address the underlying problem with the ECMP hashing. Disabling ECMP is a last resort and can reduce overall bandwidth.
NEW QUESTION # 96
An enterprise builds a Kubernetes-based AI platform using NVIDIA GPU Operator. After adding several new GPU nodes, administrators notice that NVIDIA drivers, container runtime components, and monitoring agents are installed automatically without manual intervention.
Which capability of GPU Operator enables this behavior?
Answer: A
Explanation:
GPU Operator simplifies Kubernetes deployments by managing GPU drivers, the NVIDIA Container Toolkit, device plugins, DCGM exporters, and related software as Kubernetes resources. This automates installation, upgrades, and lifecycle management across the cluster. It does not configure BIOS settings or perform virtual machine migration.
NEW QUESTION # 97
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