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HP HPE2-B08 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| HPE GreenLake for AI Solutions | - Consumption-based IT model for AI - GreenLake architecture and services |
| Deployment and Operations | - Monitoring and optimization - Deployment models for AI solutions - Lifecycle management of AI infrastructure |
| HPE Private Cloud AI Fundamentals | - Core AI workload characteristics - Overview of private cloud AI concepts |
| Security in Private Cloud AI | - Workload and data protection - Identity and access management |
| Data Management and Governance | - Data governance and compliance - Data lifecycle management |
| AI Infrastructure Design | - Compute and GPU considerations - Networking for AI workloads - Storage and data pipeline design |
HPE Private Cloud AI Solutions Sample Questions:
What is the primary advantage of using a Smart Template in OCA for HPE Private Cloud AI versus manually configuring a similar set of hardware?
- A. The Smart Template ensures all necessary and validated components, including specific cables, power cords, and software SKUs, are included correctly.
- B. The Smart Template guarantees the lowest possible price for the hardware.
- C. The Smart Template allows the use of components from other vendors.
- D. The Smart Template provides a 90-day free trial of the entire solution.
An architect is designing an AI solution for a financial services company that needs to build a chatbot.
The chatbot must answer customer queries using the company's latest internal policy documents, which are updated daily. The company has a limited budget and no data scientists available for a lengthy model retraining project.
Which approach should the architect recommend?
- A. Use a pre-trained computer vision model to extract text from the policy documents.
- B. Train a new LLM from scratch using only the company's policy documents to ensure data privacy.
- C. Fine-tune a pre-trained model daily by retraining it on the entire set of policy documents.
- D. Use a pre-trained model and implement a Retrieval-Augmented Generation (RAG) framework.
An architect is working with a customer who has been identified as an 'AI Pro'. They have a mature AI practice and are looking to scale their efforts in creating 'digital twin' simulations for automotive prototypes. This involves complex, graphics-intensive AI workloads. The customer wants a full-stack, turnkey private cloud solution to accelerate this initiative.
What is the most appropriate HPE solution to position for this customer?
- A. HPE Private Cloud AI with NVIDIA.
- B. An HPE AI Services - Transformation Workshop to redefine their goals.
- C. A set of AI-optimized HPE ProLiant DL servers for edge deployment.
- D. A custom solution built on individual HPE ProLiant servers.
A customer has used the HPE Intelligent Configurator and determined that the HPE Private Cloud AI
"Small - Expanded" configuration meets their needs. They now need to generate a final, quotable Bill of Materials (BOM).
What is the most direct and efficient method for the sales team to create this BOM?
- A. Use the standard HPE ProLiant DL380a Gen11 server template in OCA and add the GPUs and networking manually.
- B. Manually add each component (servers, GPUs, switches, cables, etc.) one by one into HPE One Config Advanced (OCA).
- C. Send the output from the HPE Intelligent Configurator directly to the distribution partner for a quote.
- D. Select the "HPE Private Cloud AI - Small - Expanded" Smart Template within HPE One Config Advanced (OCA).
A customer needs to run a generative AI workload at multiple, dispersed edge locations. Each location has significant space and power constraints. The workload is inference-only and does not require the absolute highest performance, but rather a balance of good performance and energy efficiency.
Which HPE ProLiant server and NVIDIA GPU combination is specifically positioned for this type of edge AI use case?
- A. HPE Cray system with NVIDIA Grace Hopper Superchips
- B. HPE ProLiant DL384 Gen12 server with NVIDIA H200 NVL GPUs
- C. HPE ProLiant DL320 Gen11 server with NVIDIA L4 GPUs
- D. HPE ProLiant DL380a server with NVIDIA H100 NVL GPUs
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