Download the NVIDIA AI Infrastructure NCP-AII Dumps (V8.02) and Start Preparation Today: Continue to Read NCP-AII Free Dumps (Part 2, Q41-Q80)

1. In an InfiniBand fabric, what is the primary role of the Subnet Manager (SM) with respect to routing?

2. You’re debugging performance issues in a distributed training job. ‘nvidia-smi’ shows consistently high GPU utilization across all nodes, but the training speed isn’t increasing linearly with the number of GPUs. Network bandwidth is sufficient.

What is the most likely bottleneck?

3. You are tasked with designing a high-performance network for a large-scale recommendation system. The system requires low latency and high throughput for both training and inference.

Which interconnect technology is MOST suitable for connecting the nodes within the cluster?

4. An A1 inferencing server, using NVIDIA Triton Inference Server, experiences intermittent crashes under peak load. The logs reveal CUDA out-of-memory errors (00M) despite sufficient system RAM. You suspect a GPU memory leak within one of the models.

Which strategy BEST addresses this issue?

5. When setting up a multi-server, multi-GPU environment using NVLink switches, what is the primary consideration when planning the network topology for optimal performance?

6. Consider a scenario where you are using NCCL (NVIDIA Collective Communications Library) for multi-GPU training across multiple servers connected via NVLink switches.

Which NCCL environment variable would you use to specify the network interface to be used for communication?

7. You are tasked with setting up network fabric ports to connect several servers, each with multiple NVIDIA GPUs, to an InfiniBand switch. Each server has two ConnectX-6 adapters.

What is the best strategy to maximize bandwidth and redundancy between the servers and the InfiniBand fabric?

8. Given the following ‘nvswitch-cli’ output, what does the ‘Link Speed’ indicate, and what potential bottleneck might a low ‘Link Speed’ suggest?

9. You’re optimizing an Intel Xeon server with 4 NVIDIA GPUs for inference serving using Triton Inference Server. You’ve deployed multiple models concurrently. You observe that the overall throughput is lower than expected, and the GPU utilization is not consistently high.

What are potential bottlenecks and optimization strategies? (Select all that apply)

10. A distributed training job using multiple nodes, each with eight NVIDIA GPUs, experiences significant performance degradation. You notice that the network bandwidth between nodes is consistently near its maximum capacity. However, ‘nvidia-smi’ shows low GPU utilization on some nodes.

What is the MOST likely cause?

11. You are tasked with optimizing storage performance for a deep learning training job on an NVIDIA DGX server. The training data consists of millions of small image files.

Which of the following storage optimization techniques would be MOST effective in reducing I/O bottlenecks?

12. Which of the following statements regarding VXLAN (Virtual Extensible LAN) is MOST accurate in the context of data center networking for AI/ML workloads?

13. 1.A GPU in your AI server consistently overheats during inference workloads. You’ve ruled out inadequate cooling and software bugs.

Running ‘nvidia-smi’ shows high power draw even when idle.

Which of the following hardware issues are the most likely causes?

14. You are configuring a Mellanox InfiniBand network for a DGXAIOO cluster.

What is the RECOMMENDED subnet manager for a large, high-performance A1 training environment, and why?

15. You are troubleshooting a performance issue on an Intel Xeon server with NVIDIAAI 00 GPUs. Your application involves frequent data transfers between CPU memory and GPU memory. You suspect that the PCle bus is a bottleneck.

How can you verify and mitigate this bottleneck?

16. You are managing a cluster of GPU servers for deep learning. You observe that one server consistently exhibits high GPU temperature during training, causing thermal throttling and reduced performance. You’ve already ensured adequate airflow.

Which of the following actions would be MOST effective in addressing this issue?

17. After upgrading the network card drivers on your A1 inference server, you experience intermittent network connectivity issues, including packet loss and high latency. You’ve verified that the physical connections are secure.

Which of the following steps would be most effective in troubleshooting this issue?

18. You are deploying a multi-tenant A1 infrastructure with strict isolation requirements.

Which network technology would be most suitable for creating isolated virtual networks for each tenant?

19. You’re profiling the performance of a PyTorch model running on an AMD server with multiple NVIDIA GPUs. You notice significant overhead in the data loading pipeline.

Which of the following strategies can help optimize data loading and improve GPU utilization? Select all that apply.

20. You are setting up network fabric ports for hosts in an NVIDIA-Certified Professional A1 Infrastructure (NCP-AII) environment. You need to configure Jumbo Frames to improve network throughput.

What is the typical MTU (Maximum Transmission Unit) size you would set on the network interfaces and switches, and why?

21. You are implementing a distributed deep learning training setup using multiple servers connected via NVLink switches. You want to ensure optimal utilization of the NVLink interconnect.

Which of the following strategies would be MOST effective in achieving this goal?

22. You are managing a server farm of GPU servers used for A1 model training. You observe frequent GPU failures across different servers.

Analysis reveals that the failures often occur during periods of peak ambient temperature in the data center. You can’t immediately improve the data center cooling.

What are TWO proactive measures you can implement to mitigate these failures without significantly impacting training performance?

23. You notice that one of the fans in your GPU server is running at a significantly higher RPM than the others, even under minimal load. ipmitool sensor’ output shows a normal temperature for that GPU.

What could be the potential causes?

24. You suspect a power supply issue is causing intermittent GPU failures in a server with four NVIDIAAIOO GPUs. The server is rated for a peak power consumption of 3000W. You have a power meter available.

Which of the following methods provides the most accurate assessment of the server’s power consumption under full GPU load?

25. You are configuring a server with multiple GPUs for CUDA-aware MPI.

Which environment variable is critical for ensuring proper GPU affinity, so that each MPI process uses the correct GPU?

26. Consider an AMD EPYC-based server with 8 NVIDIAAIOO GPUs connected via PCle Gen4. You’re running a distributed training job using Horovod. You’ve noticed that communication between GPUs is a bottleneck.

Which of the following NCCL configuration options would be MOST beneficial in this scenario? (Assume all options are syntactically correct for NCCL).

27. You’re optimizing an Intel Xeon server with 4 NVIDIAAIOO GPUs for a computer vision application that uses CODA. You notice that the GPU utilization is fluctuating significantly, and performance is inconsistent. Using ‘nvprof, you identify that there are frequent stalls in the CUDA kernels due to thread divergence.

What are possible causes and solutions?

28. Your AI training pipeline involves a pre-processing step that reads data from a large HDF5 file. You notice significant delays during this step. You suspect the HDF5 file structure might be contributing to the slow read times.

What optimization technique is MOST likely to improve read performance from this HDF5 file?

29. You have an Intel Xeon Gold server with 2 NVIDIA Tesla VI 00 GPUs. After deploying your A1 application, you observe that one GPU is consistently running at a significantly higher temperature than the other

What could be a plausible reason for this behavior?

30. Which of the following are valid methods for verifying the health and connectivity of InfiniBand links in an NCP-AII environment? (Select TWO)

31. An A1 server exhibits frequent kernel panics under heavy GPU load. ‘dmesg’ reveals the following error: ‘NVRM: Xid (PCl:0000:3B:00): 79, pid=..., name=..., GPU has fallen off the bus.’

Which of the following is the least likely cause of this issue?

32. You suspect a faulty NVIDIA ConnectX-6 network adapter in a server used for RDMA-based distributed training.

Which commands or tools can you use to diagnose potential issues with the adapter’s hardware and connectivity?

33. You are deploying a multi-GPU server for deep learning training. After installing the GPUs, the system boots, but ‘nvidia-smi’ only detects one GPU. The motherboard has multiple PCle slots, all of which are physically capable of supporting GPUs.

What is the most probable cause?

34. You’re designing a new InfiniBand network for a distributed deep learning workload. The workload consists of a mix of large-message all- to-all communication and small-message parameter synchronization.

Considering the different traffic patterns, what routing strategy would MOST effectively minimize latency and maximize bandwidth utilization across the fabric?

35. You’re monitoring the storage I/O for an AI training workload and observe high disk utilization but relatively low CPU utilization.

Which of the following actions is LEAST likely to improve the performance of the training job?

36. You’re optimizing an AMD EPYC server with 4 NVIDIAAIOO GPUs for a large language model training workload. You observe that the GPUs are consistently underutilized (50-60% utilization) while the CPUs are nearly maxed out.

Which of the following is the MOST likely bottleneck?

37. You observe high latency and low bandwidth between two GPUs connected via an NVLink switch. You suspect a problem with the NVLink link itself.

Which of the following methods would be the most effective in diagnosing the physical NVLink link health?

38. You are installing a GPU server in a data center with limited cooling capacity.

Which of the following server configuration choices would BEST help minimize the server’s thermal output, without significantly compromising performance? Assume all options are compatible.

39. You are experiencing link flapping (frequent up/down transitions) on several InfiniBand links in your AI infrastructure. This is causing intermittent connectivity issues and performance degradation.

What are the MOST likely causes of this issue, and what steps should you take to troubleshoot and resolve it? (Select TWO)

40. You’re deploying a new cluster with multiple NVIDIAAIOO GPUs per node. You want to ensure optimal inter-GPU communication performance using NVLink.

Which of the following configurations are critical for achieving maximum NVLink bandwidth?