Latest NCP-AII Dumps (V9.03) for Smooth and Efficient Exam Preparation: Read NVIDIA NCP-AII Free Dumps (Part 1, Q1-Q40)

1. You are designing a network for a distributed training job utilizing multiple GPUs across multiple nodes.

Which network characteristic is MOST critical for minimizing training time?

2. 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?

3. 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?

4. 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?

5. You’re designing a data center network for inference workloads. The primary requirement is high availability.

Which of the following considerations are MOST important for your topology design?

6. 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?

7. You need to remotely monitor the GPU temperature and utilization of a server without installing any additional software on the server itself.

Assuming you have network access to the server’s BMC (Baseboard Management Controller), which protocol and standard data format would BEST facilitate this?

8. Consider the following ‘ibroute’ command used on an InfiniBand host: ‘ibroute add dest Oxla dev ib0’.

What is the MOST likely purpose of this command?

9. You’re optimizing a deep learning model for deployment on NVIDIA Tensor Cores. The model uses a mix of FP32 and FP16 precision. During profiling with NVIDIA Nsight Systems, you observe that the Tensor Cores are underutilized.

Which of the following strategies would MOST effectively improve Tensor Core utilization?

10. Consider a scenario where you are setting up a high-performance computing cluster with several GPU-accelerated nodes using Slurm as the resource manager. You want to ensure that jobs requesting GPUs are only scheduled on nodes with the appropriate NVIDIA drivers and CUDA toolkit installed.

How can you achieve this within Slurm?

11. Which of the following is a primary benefit of using a CLOS network topology (e.g., Spine-Leaf) in a data center?

12. 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?

13. 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?

14. You are planning the network infrastructure for a DGX SuperPOD. You need to ensure that the network fabric can handle the high bandwidth and low latency requirements of A1 training workloads.

Which network technology is the RECOMMENDED choice for interconnecting the DGX nodes within the SuperPOD, and why?

15. 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?

16. Which of the following are key considerations when choosing between CPU pinning and NUMA (Non-Uniform Memory Access) awareness for a distributed training job on a multi-socket AMD EPYC server with multiple GPUs?

17. In a distributed training environment with NVLink switches, you need to optimize the data transfer between GPUs on different servers.

Which strategy is most likely to minimize the impact of inter-server latency on the overall training time?

18. You’ve replaced a faulty NVIDIA Quadro RTX 8000 GPU with an identical model in a workstation. The system boots, and ‘nvidia-smi’ recognizes the new GPU. However, when rendering complex 3D scenes in Maya, you observe significantly lower performance compared to before the replacement. Profiling with the NVIDIA Nsight Graphics debugger shows that the GPU is only utilizing a small fraction of its available memory bandwidth.

What are the TWO most likely contributing factors?

19. Consider the following *iptables’ rule used in an A1 inference server.

What is its primary function?

iptables -A INPUT -p tcp --dport 8080 -j ACCEPT

20. Consider a scenario where you are running a CUDA application on an NVIDIA GPU. The application compiles successfully but crashes during runtime with a *CUDA ERROR ILLEGAL ADDRESS* error. You’ve carefully reviewed your code and can’t find any obvious out- of-bounds memory accesses.

What advanced debugging techniques could help you pinpoint the source of this error?

21. You are troubleshooting a network performance issue in your NCP-AII environment.

After running ‘ibstat’ on a host, you see the following output for one of the InfiniBand ports:

What does the ‘LMC: 0’ indicate, and what are the implications for network performance?

22. 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?

23. 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?

24. You are configuring a network for a distributed training job using multiple DGX servers connected via InfiniBand. After launching the training job, you observe that the inter-GPU communication is significantly slower than expected, even though ‘ibstat’ shows all links are up and active.

What is the MOST likely cause of this performance bottleneck?

25. Your AI infrastructure includes several NVIDIAAI 00 GPUs. You notice that the GPU memory bandwidth reported by ‘nvidia-smi’ is significantly lower than the theoretical maximum for all GPUs. System RAM is plentiful and not being heavily utilized.

What are TWO potential bottlenecks that could be causing this performance issue?

26. 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?

27. You have a large dataset stored on a BeeGFS file system. The training job is single node and uses data augmentation to generate more data on the fly. The data augmentation process is CPU-bound, but you notice that the GPU is underutilized due to the training data not being fed to the GPU fast enough.

How can you reduce the load on the CPU and improve the overall training throughput?

28. Which of the following techniques are effective for improving inter-GPU communication performance in a multi-GPU Intel Xeon server used for distributed deep learning training with NCCL?

29. You are using GPU Direct RDMA to enable fast data transfer between GPUs across multiple servers. You are experiencing performance degradation and suspect RDMA is not working correctly.

How can you verify that GPU Direct RDMA is properly enabled and functioning?

30. In a data center utilizing NVIDIA GPUs and NVLink, what is the primary advantage of using a direct-attached NVLink network topology compared to routing traffic over the network?

31. You’re troubleshooting a DGX-I server exhibiting performance degradation during a large-scale distributed training job. ‘nvidia-smü shows all GPUs are detected, but one GPU consistently reports significantly lower utilization than the others. Attempts to reschedule orkloads to that GPU frequently result in CUDA errors.

Which of the following is the MOST likely cause and the BEST initial roubleshooting step?

32. You’re working with a large dataset of microscopy images stored as individual TIFF files. The images are accessed randomly during a training job. The current storage solution is a single HDD. You’re tasked with improving data loading performance.

Which of the following storage optimizations would provide the GREATEST performance improvement in this specific scenario?

33. Which of the following is the MOST important reason for using a dedicated storage network (e.g., InfiniBand or RoCE) for AI/ML workloads compared to using the existing Ethernet network?

34. 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?

35. What is the role of GPUDirect RDMA in an NVLink Switch-based system, and how does it improve performance?

36. 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.

37. You are deploying a multi-tenant AI infrastructure where different users or groups have isolated network environments using VXLAN.

Which of the following is the MOST important consideration when configuring the VTEPs (VXLAN Tunnel Endpoints) on the hosts to ensure proper network isolation and performance?

38. You are running a large-scale distributed training job on a cluster of AMD EPYC servers, each equipped with multiple NVIDIAA100 GPUs. You are using Slurm for job scheduling. The training process often fails with NCCL errors related to network connectivity.

What steps can you take to improve the reliability of the network communication for NCCL in this environment? Choose the MOST appropriate answers.

39. 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?

40. After replacing a faulty NVIDIA GPU, the system boots, and ‘nvidia-smi’ detects the new card. However, when you run a CUDA program, it fails with the error "‘no CUDA-capable device is detected’". You’ve confirmed the correct drivers are installed and the GPU is properly seated.

What’s the most probable cause of this issue?