あなたのNCP-AII試験合格を100%保証

JPNTestテスト問題集を初めて使用したときにNVIDIA-Certified Professional NCP-AII試験（NVIDIA AI Infrastructure）に合格されなかった場合は、購入料金を全額ご返金いたします。

NCP-AII試験の品質と価値

JPNTestのNVIDIA-Certified Professional NCP-AII模擬試験問題集は、認定された対象分野の専門家と公開された作成者のみを使用して、最高の技術精度標準に沿って作成されています。

ダウンロード可能なインタラクティブNCP-AIIテストエンジン

NVIDIA-Certified Professionalの基礎準備資料問題集には、NVIDIA-Certified Professional NCP-AII試験を受けるために必要なすべての材料が含まれています。詳細は、正確で論理的なものを作成するために業界の経験を常に使用しているNVIDIA-Certified Professional によって研究と構成されています。

JPNTestでNVIDIA NCP-AII問題集をチョイスする理由

JPNTestは、1週間で完璧に認定試験を準備することができる、忙しい受験者に最適な問題集を提供しております。 NCP-AIIの問題集は、NVIDIAの専門家チームがベンダーの推奨する授業要綱を深く分析して作成されました。弊社のNCP-AII学習材料を一回のみ使用するだけで、NVIDIA認証試験に合格することができます。

NCP-AIIはNVIDIAの重要な認証であり、あなたの専門スキルを試す認定でもあります。受験者は、試験を通じて自分の能力を証明したいと考えています。 JPNTest NVIDIA AI Infrastructure は、NVIDIA-Certified Professionalの301の問題と回答を収集して作成しました。NVIDIA AI Infrastructureの知識ポイントをカバーし、候補者の能力を強化するように設計されています。 JPNTest NCP-AII受験問題集を使用すると、NVIDIA AI Infrastructureに簡単に合格し、NVIDIA認定を取得して、NVIDIAとしてのキャリアをさらに歩むことができます。

デモをダウンロードする

NCP-AIIの迅速なアップデート対応

NCP-AII試験に変更がございました場合は、現在の試験と一致するよう、瞬時に学習資料を更新することができます。弊社は、お客様に最高、最新のNVIDIA NCP-AII問題集を提供することに専念しています。なお、ご購入いただいた製品は365日間無料でアップデートされます。

NVIDIA AI Infrastructure 認定 NCP-AII 試験問題:

1. You are installing four NVIDIAAIOO GPUs in a server, and after installation, you observe that the PCle link speed for one of the GPUs is running at x8 instead of the expected x16. What could be the POSSIBLE causes for this reduced PCle link speed?

A) The CPU does not have enough PCle lanes to support all GPUs at x16.
B) The GPU is faulty.
C) The PCle slot is only wired for x8 speed.
D) The BIOS/UEFI is configured to limit the PCle link speed for that slot.
E) All of the above

2. An NVIDIA DGX server with 8 GPUs is experiencing performance issues during a distributed deep learning training run. You suspect a problem with the GPU interconnects. You have already confirmed that NVLink is active. What is the most thorough approach to diagnose potential bandwidth or latency bottlenecks in the GPU-to-GPlJ communication paths?

A) Run NCCL all-reduce benchmarks (e.g., using the NCCL tests) to measure the actual communication bandwidth between all pairs of GPUs. Compare the results to expected theoretical peak bandwidth.
B) Examine the output of 'dmesg' for any NVLink-related error messages or warnings.
C) Monitor GPU utilization with 'nvidia-smi' during the training run. Uneven utilization across GPUs indicates a potential communication bottleneck.
D) Use 'nvidia-smi topo -m' to visualize the GPU topology and check the reported link speeds. Any links with significantly lower speeds are suspect.
E) All of the above

3. You are observing that the memory bandwidth being achieved by your CUDA application on an NVIDIAAIOO GPU is significantly lower than the theoretical peak bandwidth. Which of the following could be potential causes for this, and what actions can you take to validate or mitigate them? (Select all that apply)

A) The application is using single precision floating-point operations. Switch to double precision to increase memory bandwidth utilization.
B) The system memory is fully occupied. Deallocate some memory.
C) The GPU is being limited by power capping. Increase the power limit using 'nvidia-smi -pl' (if permitted) to allow the GPU to operate at higher clock speeds.
D) The application is using uncoalesced memory access patterns. Refactor the code to ensure contiguous memory access by threads within a warp.
E) The application is using a small transfer size per kernel launch. Increase the amount of data processed per kernel launch to amortize the overhead of kernel launch and data transfer.

4. You are installing four NVIDIAAIOO GPUs into a server designed for AI training. The server motherboard has multiple PCIe Gen4 x16 slots. However, the server's power supply unit (PSU) only has three 8-pin PCIe power connectors available. What is the BEST course of action to ensure all GPUs receive adequate power?

A) Underclock the GPUs significantly to reduce their power consumption below the available PSU capacity.
B) Replace the existing PSU with a higher wattage PSU that has at least four 8-pin PCIe power connectors.
C) Use a PCIe power splitter cable on one of the 8-pin connectors to power two GPUs.
D) Connect the GPUs using the motherboard's internal SATA power connectors.
E) Install only three GPUs and leave the fourth unpowered.

5. Consider a scenario where you need to isolate GPU workloads in a multi-tenant Kubernetes cluster. Which of the following Kubernetes constructs would be MOST suitable for achieving strong isolation at both the resource and network level?

A) Using node affinity only.
B) Using taints and tolerations to dedicate GPU nodes to specific workloads.
C) Using labels and selectors to schedule workloads on specific GPU nodes.
D) Using pod affinity and anti-affinity rules to control pod placement.
E) Using namespaces with resource quotas and network policies.

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