NVIDIA -Certified Professional NCP-AII

시험준비시간 최소화

IT업계 엘리트한 강사들이 퍼펙트한 NCP-AII시험응시 NVIDIA AI Infrastructure덤프문제집을 제작하여 디테일한 NCP-AII문제와 답으로 여러분이 아주 간단히 NVIDIA AI Infrastructure시험응시를 패스할 수 있도록 최선을 다하고 있습니다.덤프구매후 2,3일 정도만 공부하시면 바로 시험보셔도 되기에 가장 짧은 시간을 투자하여 시험에서 패스할수 있습니다.

NCP-AII시험은 최근 제일 인기있는 인증시험입니다. IT업계에 종사하시는 분들은 자격증취득으로 자신의 가치를 업그레이드할수 있습니다. NVIDIA AI Infrastructure 시험은 유용한 IT자격증을 취득할수 있는 시험중의 한과목입니다. NVIDIA NVIDIA-Certified Professional 최신버전 덤프는 여러분들이 한방에 시험에서 통과하도록 도와드립니다. NCP-AII덤프를 공부하는 과정은 IT지식을 더 많이 배워가는 과정입니다. NCP-AII시험대비뿐만아니라 많은 지식을 배워드릴수 있는 덤프를 공부하고 시험패스하세요.

퍼펙트한 서비스 제공

승진이나 연봉인상을 꿈꾸면 승진과 연봉인상을 시켜주는 회사에 능력을 과시해야 합니다. IT인증시험은 국제적으로 승인해주는 자격증을 취득하는 시험입니다. 시험을 패스하여 자격증을 취득하면 회사에서 꽃길만 걷게 될것입니다. NCP-AII인증시험덤프 덤프구매전 한국어 온라인 상담서비스부터 구매후 덤프 무료 업데이트버전 제공, NCP-AII인증시험 덤프 불합격시 덤프비용 전액환불 혹은 다른 과목으로 교환 등 저희는 구매전부터 구매후까지 철저한 서비스를 제공해드립니다. NVIDIA AI Infrastructure인증시험 덤프는 인기덤프인데 지금까지 NCP-AII덤프를 구매한후 불합격으로 인해 환불신청하신 분은 아직 한분도 없었습니다.

최신 업데이트버전 NCP-AII덤프

저희는 2,3일에 한번씩 NCP-AII덤프자료가 업데이트 가능한지 체크하고 있습니다. NVIDIA AI Infrastructure덤프가 업데이트된다면 업데이트된 버전을 고객님 구매시 사용한 메일주소로 발송해드립니다. NCP-AII 덤프 업데이트서비스는 구매일로부터 1년내에 유효함으로 1년이 지나면 NCP-AII덤프 업데이트서비스가 자동으로 종료됩니다. NVIDIA AI Infrastructure덤프 무료 업데이트 서비스를 제공해드림으로 고객님께서 구매하신 NCP-AII덤프 유효기간을 최대한 연장해드립니다.

최신 NVIDIA-Certified Professional NCP-AII 무료샘플문제:

1. Which of the following is the MOST critical consideration when planning the cooling strategy for a server rack containing multiple NVIDIA A100 GPUs?

A) Ensuring the server room temperature is kept below 25 degrees Celsius.
B) Increasing the fan speed of the server chassis fans to maximum.
C) Optimizing airflow to ensure hot air is efficiently exhausted from the rack and cool air is drawn in.
D) Applying thermal paste to the GPU memory chips.
E) Using liquid cooling for the CPUs, but air cooling for the GPUs.

2. You are tasked with ensuring optimal power efficiency for a GPU server running machine learning workloads. You want to dynamically adjust the GPU's power consumption based on its utilization. Which of the following methods is the MOST suitable for achieving this, assuming the server's BIOS and the NVIDIA drivers support it?

A) Configure the server's BIOS/UEFI to use a power-saving profile, which will automatically reduce the GPU's power consumption when idle.
B) Manually set the GPU's power limit using 'nvidia-smi -pl and create a script to monitor utilization and adjust the power limit periodically.
C) Enable Dynamic Boost in the NVIDIA Control Panel (if available), which will automatically allocate power between the CPU and GPU based on their current needs.
D) Use NVIDIA's Data Center GPU Manager (DCGM) to monitor GPU utilization and dynamically adjust the power limit based on a predefined policy.
E) Disable ECC (Error Correcting Code) on the GPU to reduce power consumption.

3. 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?

A) Check the CPU utilization. If it's low, the PCle bus is likely the bottleneck. Mitigate by increasing the number of CPU cores assigned to the data transfer tasks.
B) Use 'nvprof to profile the application and identify the exact lines of code that are causing the high PCle traffic. Optimize those sections of code to reduce data transfers.
C) Monitor the GPU temperature. If it's high, the PCle bus is likely overheating. Mitigate by improving the server's cooling.
D) Use 'nvidia-smi' to monitor the PCle bandwidth utilization of the GPUs. If it's consistently high (near the theoretical limit), the PCle bus is likely a bottleneck. Mitigate by reducing the frequency of CPU-GPU data transfers, using pinned (page-locked) memory, and ensuring that the GPUs are connected to PCle slots with sufficient bandwidth.
E) Examine the system logs for PCle errors. If there are many errors, the PCle bus is likely unstable. Mitigate by reseating the GPUs and checking the power supply.

4. You've flashed the BlueField OS to your SmartNlC, but you need to customize the kernel command line arguments (bootargs) to enable a specific feature. Where is the MOST appropriate place to modify these arguments for persistent changes that survive reboots?

A) Directly in the kernel image file itself using a hex editor.
B) Passing it as an argument to bfboot during deployment.
C) In the '/proc/cmdline' file. This allows immediate changes.
D) In the bootloader configuration file (e.g., extlinux.conf or grub.cfg) on the BlueFieId's flash memory.
E) In the '/etc/default/grub' file on the BlueField OS, followed by updating the GRUB configuration.

5. You are designing a storage system using BeeGFS for an AI cluster. The cluster consists of 10 client nodes, each with 2 NVIDIAAIOO GPUs, and 4 storage servers. Each storage server has 10 NVMe SSDs. The training dataset is 100TB. You want to ensure high availability and performance. Which of the following BeeGFS configurations would be MOST appropriate?

A) Two MDS servers in a high-availability configuration and 40 OSTs (one per NVMe SSD).
B) 10 MDS server (one per client nodes) and a single OST.
C) One MDS server and 10 OSTs, splitting each NVMe SSD into smaller virtual OSTs.
D) Four MDS servers (one per storage server) and 40 OSTs (one per NVMe SSD).
E) A single metadata server (MDS) and four storage targets (OSTs), each spanning all 10 NVMe SSDs on a storage server.

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