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NEW QUESTION # 26
After an architect selects the "HPE Private Cloud AI - Large - Expanded" Smart Template in OCA, they see it includes a significant number of "HPE Factory Express Complex Unit of SVC" services.
What is the purpose of these bundled services?
- A. To allow the customer to exchange the hardware for the next generation at no cost.
- B. To provide a credit for future software purchases on the HPE GreenLake cloud.
- C. To cover the pre-integration and configuration of the entire solution at an HPE factory before shipment.
- D. To provide on-site training for the customer's data science team.
Answer: C
NEW QUESTION # 27
A customer's distributed AI training job is experiencing poor performance. An analysis reveals high network latency. The architect suspects a misconfiguration in the NVIDIA Spectrum switches that form the RoCE-based AI fabric.
They review the following configuration snippet from one of the switch ports connected to a compute node:
```
interface ethernet 1/1
description "Connection to PCAI-Node-1"
speed 200G
mtu 9216
switchport mode trunk
## Priority Flow Control (PFC) is disabled on this port
```
What is the most likely cause of the performance issue?
- A. Priority Flow Control (PFC) is disabled, which is mandatory for a lossless RoCE fabric.
- B. The MTU size is too small for AI workloads.
- C. The port speed is not sufficient for the connected H100 GPU.
- D. The port is incorrectly configured in trunk mode instead of access mode.
Answer: A
NEW QUESTION # 28
A data science team has trained a deep learning model for image classification. While the model achieves 99.8% accuracy on the training dataset, its accuracy drops to only 75% on a new, unseen validation dataset.
The team provides the following training metrics:
```
- Training Epochs: 500
- Training Dataset Size: 1,000 images
- Model Parameters: 15 million
- Training Accuracy: 99.8%
- Validation Accuracy: 75.3%
```
What is the most likely cause of this performance discrepancy?
- A. The learning rate used for training was set too low.
- B. The model is overfitting to the training data and cannot generalize to new data.
- C. The model has too few parameters to learn the features effectively.
- D. The model is underfitting due to an insufficient number of training epochs.
Answer: B
NEW QUESTION # 29
A customer is planning to deploy an HPE Private Cloud AI solution. Their IT department has provided a worksheet detailing the workload requirements. The solution architect needs to select the appropriate configuration size.
Review the customer's requirements:
```
- Primary Workload: Fine-tuning a 70-billion parameter foundation model
- Secondary Workload: AI Inferencing with RAG
- User Base: 50 developers during tuning; 300 concurrent users for inference
- Data Sensitivity: High (must remain on-premises)
- Power/Cooling: Standard data center air cooling available
```
Which HPE Private Cloud AI configuration is required to meet these demands, and what is the key component that justifies this choice? (Choose 2.)
- A. The key component is the NVIDIA H100 NVL GPU, designed for large-scale training and fine-tuning.
- B. The key component is the NVIDIA L40S GPU, which is optimized for RAG workloads.
- C. The key component is the HPE ProLiant DL325 server in the management plane.
- D. The solution requires a Large configuration.
- E. The solution requires a Medium configuration.
Answer: A,D
NEW QUESTION # 30
A customer is using the HPE Intelligent Configurator to determine the correct size for an HPE Private Cloud AI solution. Their primary use case is a text generation chatbot for internal HR support.
What is the MOST critical piece of information the customer must provide to the sizing tool to get an accurate recommendation for the number and type of GPUs required?
- A. The estimated number of concurrent users who will be querying the chatbot.
- B. The brand of networking switches used in their existing data center fabric.
- C. The number of ML engineers who will maintain the model.
- D. The physical location of the data center where the solution will be deployed.
Answer: A
NEW QUESTION # 31
An architect is evaluating the high operational costs associated with their company's internal AI platform. The primary workload involves fine-tuning a 70-billion parameter LLM for various departmental tasks. The team reports that the GPU cluster utilization is low, and jobs often fail, requiring manual restarts.
They are reviewing the platform's configuration:
```
- Model: Llama 2 70B
- Task: Supervised Fine-Tuning
- Cluster Size: 16x nodes, each with 4x NVIDIA A100 GPUs
- Scheduling: Manual job submission via SSH scripts
- Data Management: Datasets manually copied to local storage on each node
- Collaboration: Code and models shared via a central Git repository
```
Which NVIDIA AI Enterprise component is specifically designed to address the challenges of low GPU utilization and manual job management in a multi-node training environment like this?
- A. NVIDIA Triton Inference Server
- B. HPE Machine Learning Development Environment
- C. NVIDIA RAPIDS
- D. NVIDIA NIM (NVIDIA Inference Microservices)
Answer: B
NEW QUESTION # 32
An enterprise is designing a solution for training a large, custom Convolutional Neural Network (CNN) for a new computer vision application. Their data science team has determined that the training process will need to be distributed across multiple GPUs to be completed in a reasonable timeframe. The training process involves intensive matrix multiplication operations.
The architect is specifying components from the HPE Private Cloud AI solution.
Which infrastructure components are critical for accelerating this specific distributed training workload?
(Select all that apply.)
```
Workload Analysis:
- AI Model: Large Convolutional Neural Network (CNN)
- Task: Distributed Training
- Key Operation: Intensive matrix multiplication
```
- A. NVIDIA GPUs featuring multiple Tensor Cores.
- B. HPE GreenLake for File Storage with standard NFS over TCP/IP.
- C. The HPE Data Fabric software component.
- D. An NVIDIA NVLink Bridge to connect the GPUs.
- E. HPE ProLiant DL325 servers for the worker nodes.
Answer: A,D
NEW QUESTION # 33
A financial services firm is building a fraud detection application on HPE Private Cloud AI. The application needs to process a continuous stream of transaction data from multiple sources in real time.
The data science team requires a robust platform to build, manage, and execute the complex data pipelines needed to feed the AI model.
Which pre-integrated open-source tool within HPE AI Essentials is the industry standard for orchestrating and managing these complex data workflows and pipelines?
- A. JupyterLab
- B. Kyverno
- C. Apache Airflow
- D. Prometheus
Answer: C
NEW QUESTION # 34
A customer's ML Engineer states, "We need to deploy our trained models, and our top priority is simplifying the process. We want to treat our models like cattle, not pets-packaging them into standardized, optimized containers that we can deploy and scale easily via an API." This statement describes the primary benefit of which software component in the HPE Private Cloud AI stack?
- A. JupyterLab
- B. NVIDIA NIM (NVIDIA Inference Microservices)
- C. HPE Data Fabric
- D. Apache Airflow
Answer: B
NEW QUESTION # 35
A customer is building an application to classify images of defective products on a manufacturing line.
Which type of neural network layer is essential for this model to automatically learn and identify visual features like edges, corners, and textures in the images?
- A. A convolutional layer
- B. A recurrent layer
- C. A dense (fully connected) layer
- D. An output layer with a softmax function
Answer: A
NEW QUESTION # 36
An AI application is being developed to analyze financial time-series data to predict stock market trends. The model needs to understand long-term dependencies and the sequence in which data points occur.
Which neural network architecture is specifically designed to handle sequential data like text or time- series?
- A. Convolutional Neural Network (CNN)
- B. K-Means Clustering Algorithm
- C. A fully connected, feedforward neural network
- D. Transformer model
Answer: D
NEW QUESTION # 37
An architect is designing a distributed training solution using HPE Private Cloud AI. The solution involves multiple HPE ProLiant DL380a servers, each with four NVIDIA H100 GPUs.
Review the logical network topology:
```
[HPE ProLiant Server 1] \
- GPU 0 <--> GPU 1 (Internal)
- GPU 2 <--> GPU 3 (Internal)
\
[NVIDIA Spectrum Switch (RoCE)] <--> [HPE GreenLake for File Storage]
/
[HPE ProLiant Server 2] /
- GPU 0 <--> GPU 1 (Internal)
- GPU 2 <--> GPU 3 (Internal)
```
Which interconnect technology facilitates the highest-bandwidth communication path labeled "(Internal)" for scaling the training job across the GPUs within a single server?
- A. NVIDIA NVLink Bridge
- B. RDMA over Converged Ethernet (RoCE)
- C. GPUDirect Storage (GDS)
- D. PCI Express (PCIe) Gen5
Answer: A
NEW QUESTION # 38
An 'AI Pro' customer wants to deploy a solution to create 'digital twins' of their manufacturing equipment for predictive maintenance simulations. This workload requires significant GPU power for both the simulation and the underlying AI model.
Which HPE solution should be positioned as the primary platform for this advanced, data-center based workload?
- A. A standard data warehouse solution without GPU acceleration.
- B. HPE Private Cloud AI with NVIDIA.
- C. The customer's existing VDI environment.
- D. Individual HPE ProLiant DL320 Gen11 servers at the edge.
Answer: B
NEW QUESTION # 39
A retail customer wants to implement an AI-powered recommender system to personalize product suggestions on their e-commerce website. They are an 'Early AI user' and need a full-stack solution that simplifies deployment and management.
Which HPE AI solution is most appropriate for this use case?
- A. HPE Cray systems
- B. HPE AI Services - Transformation Workshop
- C. HPE Private Cloud AI with NVIDIA
- D. AI-optimized HPE ProLiant DL servers deployed individually
Answer: C
NEW QUESTION # 40
A customer wants to build a configuration in One Config Advanced (OCA) for the HPE Private Cloud AI "Large - Standard" solution.
Which key components should the architect expect the Smart Template to include in the Bill of Materials (BOM)? (Choose 2.)
- A. 4 worker nodes.
- B. 8 worker nodes.
- C. HPE ProLiant DL380a Gen11 servers with NVIDIA L40S GPUs.
- D. HPE ProLiant DL380a Gen11 servers with NVIDIA H100 NVL GPUs.
- E. HPE Cray compute nodes.
Answer: A,D
NEW QUESTION # 41
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