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HP HPE2-B08 Exam Syllabus Topics:

HPE Private Cloud AI Solutions Sample Questions:

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

2. An architect is positioning an HPE Private Cloud AI solution to a customer who is an "AI Pro." The customer's CIO is the key decision maker.
Which benefits of the solution would be most compelling to this stakeholder? (Choose 2.)

A) The ability to write Python code in a Jupyter Notebook.
B) Access to a command-line interface for the network switches.
C) The ability to use NVIDIA NIMs to drastically simplify and standardize model deployment, reducing operational complexity and cost.
D) A predictable, cloud-like operational expense model and a clear return on investment (ROI) by accelerating time-to-value for AI projects.
E) The specific version of the CUDA driver used by the NVIDIA GPUs.

3. An architect uses the HPE Intelligent Configurator for a customer with 120 concurrent users for a text generation task with RAG. The tool recommends a "Medium - Expanded (4-node)" configuration. The customer then reveals they want to use a smaller, more efficient 7B parameter model instead of the 13B model the tool defaulted to.
How will this change in model size likely affect the sizing tool's recommendation?

A) It will upgrade the recommendation to a "Large - Standard (4-node)" configuration.
B) It will require the architect to switch to the "application capacity" sizing method.
C) It will downgrade the recommendation to a "Medium - Standard (2-node)" configuration.
D) It will have no effect, as the number of users is the primary factor.

4. A sales professional is preparing a quote for an HPE Private Cloud AI solution in OCA and needs to ensure the correct support services are attached.
What is the default level of support included with all components when using the "Flexible services" option in the Smart Template?

A) HPE Tech Care, Essential
B) HPE Complete Care Service
C) HPE Tech Care, Critical
D) HPE Tech Care, Basic

5. An architect is designing an infrastructure solution for an AI workload that involves processing massive datasets for training. The goal is to minimize data transfer latency between the storage system and the GPUs in the compute nodes. The architect wants to enable the NVIDIA GPUs to fetch data directly from the NVMe storage array, bypassing the server's CPU and main memory.
Review the proposed architectural components:
```
- Compute Nodes: HPE ProLiant DL380a Gen11 with NVIDIA H100 GPUs
- Storage: HPE GreenLake for File Storage
- Interconnect: Ethernet with RoCE support
```
Which technology must be enabled and properly configured across these components to achieve this direct GPU-to-storage data path? (Choose 2.)

A) Multi-Instance GPU (MIG)
B) RDMA over Converged Ethernet (RoCE)
C) GPUDirect Storage (GDS)
D) NVLink
E) Confidential Computing

Solutions: