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NVIDIA NCP-AII Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: System and Server Bring-up20%- Firmware and system configuration
  • 1. OS installation and base configuration
    • 2. BMC, BIOS, TPM and firmware updates
      - Hardware installation and validation
      • 1. Power, cooling and physical connectivity verification
        • 2. Server, GPU, network and storage components setup
          Topic 2: Networking and Storage Configuration20%- NVIDIA networking solutions
          • 1. InfiniBand and Ethernet fabric setup
            • 2. BlueField DPU configuration
              - Storage integration
              • 1. Storage performance for AI workloads
                • 2. Parallel file systems and object storage
                  Topic 3: GPU Resource Management15%- GPU scheduling and optimization
                  • 1. NVLink and fabric management
                    • 2. Workload placement and sharing
                      - Multi-Instance GPU (MIG) configuration
                      • 1. Partitioning and resource allocation
                        • 2. Isolation and performance tuning
                          Topic 4: 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
                                  Topic 5: Software Stack Deployment25%- Orchestration and workload management
                                  • 1. Slurm, Kubernetes and container orchestration
                                    • 2. NGC catalog and software deployment
                                      - NVIDIA software components
                                      • 1. GPU drivers, container toolkit and runtime
                                        • 2. Base Command Manager and cluster management tools

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                                          NVIDIA AI Infrastructure Sample Questions (Q188-Q193):

                                          NEW QUESTION # 188
                                          A system engineer needs to set the vGPU scheduling behavior for all GPUs to share the scheduling equally with the default time slice length. What command should be used?

                                          Answer: B

                                          Explanation:
                                          The RmPVMRL=0x00 setting configures the NVIDIA vGPU scheduler to use equal-share scheduling with the default time slice length. The esxcli system module parameters set -m nvidia command is the correct ESXi command format for setting NVIDIA kernel module parameters globally for the GPUs.


                                          NEW QUESTION # 189
                                          Which of the following steps are essential components of a recommended DGX cluster installation procedure? (Choose two.)

                                          Answer: A,B

                                          Explanation:
                                          A recommended DGX cluster installation requires validating network interfaces and fabric connectivity before deploying cluster software so node provisioning and workload communication are reliable. Grouping nodes by function and assigning them to the proper cluster management categories ensures consistent configuration, management, and role-based deployment across the cluster.


                                          NEW QUESTION # 190
                                          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: E

                                          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 # 191
                                          You need to verify the NVLink connectivity between GPUs in a DGX server. Which command-line utility is the MOST reliable and provides detailed NVLink status?

                                          Answer: D

                                          Explanation:
                                          'dcgmi diag -t 1004' is the correct command. 'nvidia-smi' provides basic GPIJ information, but 'dcgmi diag -t 1004' (part of the Data Center GPU Manager) provides specific diagnostic tests for NVLink connectivity. 'Ispci' lists PCle devices, not specifically NVLink. 'gpustat' is a monitoring tool. 'nvlink_info' is hypothetical.


                                          NEW QUESTION # 192
                                          Your company is planning to expand its AI capabilities significantly over the next five years. To future-proof your storage infrastructure, you need a solution that can scale in both capacity and performance. Which of the following strategies best ensures that your storage infrastructure remains adaptable to future AI demands?

                                          Answer: D

                                          Explanation:
                                          A hybrid cloud model provides the flexibility to scale capacity and performance over time by combining on-premises infrastructure for predictable, high-performance workloads with cloud resources for elastic growth. This approach keeps the storage architecture adaptable as AI data volumes, training workloads, and performance requirements increase.


                                          NEW QUESTION # 193
                                          ......

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