最新のNS0-901問題集で試験を準備する

Network Appliance NS0-901 試験概要:

Network Appliance NS0-901 試験シラバストピック:

Network Appliance NetApp Certified AI Expert 認定 NS0-901 試験問題：

1. The firm's CFO is concerned about the rising costs of the on-premises AI infrastructure. A storage utilization report shows that of the 200 TB of data on the high-performance AFF A-Series, 150 TB consists of inactive, older versions of product documents that are rarely accessed but must be kept online for regulatory reasons.
The current storage landscape is:
- Performance Tier: NetApp AFF A-Series (200 TB used)
- Capacity Tier: NetApp StorageGRID (1.5 PB used)
What is the most effective and automated solution to reduce the storage cost of the performance tier without impacting data accessibility?

A) Use NetApp SnapMirror to replicate the entire 200 TB volume to the StorageGRID system and then delete the source.
B) Manually identify and delete the 150 TB of inactive data from the AFF A-Series.
C) Purchase an additional, larger AFF A-Series system to gain better storage efficiency through deduplication.
D) Implement NetApp FabricPool to automatically tier the inactive data blocks from the AFF A-Series to the StorageGRID system.

2. Which of the following are typical requirements for inferencing in AI models? (Choose two)

A) Pre-trained models
B) Loading the model into memory
C) Extensive training data
D) Cloud-based inference only

3. A national research laboratory is investing in a turnkey AI infrastructure solution. Their primary goal is to eliminate the complexity and risk of designing and integrating the compute, network, and storage components themselves. The solution must be pre-validated by the vendors to deliver predictable, linear performance as they scale from one to multiple compute nodes. Which two options represent this type of pre-validated, converged infrastructure solution for AI? (Choose two)

A) NetApp AIPod, which integrates NVIDIA DGX servers with NetApp storage and networking.
B) A custom-built server rack with components sourced from various different vendors.
C) A single NetApp FAS system connected directly to a single server.
D) A Cisco and NetApp FlexPod for AI solution.
E) A public cloud provider's general-purpose virtual machine instances.

4. An AI architect is planning the resource allocation for a new project. The primary task is to process millions of unlabeled customer reviews to identify naturally occurring groups or themes without any prior guidance.
The project requirements are summarized below:
Task: Discover hidden patterns in text data
Input_Data: 10 million unlabeled text reviews
Output: Clustered groups of related reviews
Supervision: None
Which type of machine learning algorithm is required for this task?

A) Predictive learning
B) Reinforcement learning
C) Unsupervised learning
D) Supervised learning

5. The AI training jobs on the AIPod are performing below expectations. The NVIDIA DGX servers' GPUs show low utilization. A performance analysis reveals that the bottleneck is not the storage system itself, but the network path between the storage and the compute nodes.
The current network configuration is as follows:
Network_Fabric: 100GbE Standard Ethernet
Protocol: NFS over TCP/IP
Data_Path: Storage -> Host CPU -> GPU Memory
Which network architecture enhancement would provide the most significant performance improvement by reducing latency and CPU overhead?

A) Upgrade the network switches to a model with a larger packet buffer.
B) Isolate the storage traffic on a separate VLAN from the management traffic.
C) Implement RDMA over Converged Ethernet (RoCE) and configure GPUDirect Storage.
D) Add more 100GbE network ports to the storage controllers.

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