HP HPE2-B08 Exam : HPE Private Cloud AI Solutions

An architect is explaining the HPE Private Cloud AI configurations to a customer.
What is the key differentiator between the "Large" configuration and the "Small" and "Medium" configurations in terms of hardware?

• A. The Large configuration uses NVIDIA H100 NVL GPUs, while the Small and Medium configurations use NVIDIA L40S GPUs.
• B. The Large configuration is the only one that includes HPE GreenLake for File Storage.
• C. The Large configuration uses AMD processors, while the Small and Medium configurations use Intel processors.
• D. The Large configuration is deployed in a single rack, while the Small and Medium require two racks.

An AI development team is training a large language model that exceeds the memory capacity of a single GPU. To continue training, they need to distribute the workload across multiple GPUs within the same server.
Which combination of HPE server and NVIDIA technology is specifically designed to provide a high- bandwidth, direct communication path between GPUs, bypassing the PCIe bus for improved performance in multi-GPU training?

• A. HPE Alletra Storage MP with RoCE-capable network adapters
• B. HPE ProLiant DL325 Gen11 server with NVIDIA L4 GPUs
• C. HPE ProLiant DL380a Gen12 server with an NVIDIA NVLink Bridge
• D. HPE ProLiant DL380a Gen11 server with GPUDirect Storage (GDS)

A global logistics company is designing an enterprise-grade AI solution. The project has two main goals:
1. Goal 1: Develop a highly accurate, proprietary logistics optimization model by fine-tuning a foundation model on the company's massive, confidential shipping dataset (20TB). This requires a secure, high- performance, multi-node training environment.
2. Goal 2: Deploy a generative AI-powered chatbot for the customer service department. The chatbot must provide real-time shipment status and answer policy questions based on a knowledge base that is updated hourly.
The company is classified as an 'AI Pro,' with a formal AI strategy and a Center of Excellence, but they want a turnkey solution to accelerate time-to-market.
Which components and strategies should the architect propose to meet all the customer's requirements?
(Select all that apply.)
```
Customer Profile:
- Industry: Global Logistics
- AI Maturity: AI Pro
- Key Workloads: Large-scale Fine-Tuning, Real-time RAG
- Desired Solution: Turnkey, enterprise-grade private cloud
```

• A. Use HPE AI Essentials to manage the training cluster, providing features like experiment tracking and optimized resource scheduling for the fine-tuning job.
• B. Implement a Retrieval-Augmented Generation (RAG) architecture for the customer service chatbot to ensure it uses the latest, hourly-updated information.
• C. Recommend that the customer build their own solution from individual components to have maximum control.
• D. Position Al-optimized HPE ProLiant DL servers at the edge for the fine-tuning workload to reduce data transfer costs.
• E. Rely solely on public cloud services for the fine-tuning job to avoid capital expenditure on high- performance GPUs.
• F. Use the HPE Private Cloud AI Large configuration with NVIDIA H100 GPUs to provide the necessary performance for the large-scale fine-tuning task.

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. The port is incorrectly configured in trunk mode instead of access mode.
• B. The port speed is not sufficient for the connected H100 GPU.
• C. The MTU size is too small for AI workloads.
• D. Priority Flow Control (PFC) is disabled, which is mandatory for a lossless RoCE fabric.

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 dense (fully connected) layer
• B. An output layer with a softmax function
• C. A recurrent layer
• D. A convolutional layer