HPE2-B08최신업데이트덤프, HPE2-B08 100％시험패스덤프자료

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HP HPE2-B08 Exam Syllabus Topics:

Section	Weight	Objectives
Architecting HPE Private Cloud AI Solutions	20%	- Explain common AI use cases and how they map to workloads - Explain the HPE Private Cloud AI sizing and configuration guidelines - Describe how HPE Private Cloud AI supports AI/ML workloads - Describe the AI/ML lifecycle and data pipeline requirements - Identify components of the HPE Private Cloud AI architecture
Supporting HPE Private Cloud AI Solutions	20%	- Describe capacity planning and optimization best practices - Explain how to work with HPE support services - Identify how to perform firmware and software updates - Describe support resources and documentation
Managing and Operating HPE Private Cloud AI Solutions	30%	- Identify troubleshooting procedures and common issues - Explain backup and recovery procedures - Identify how to manage storage and data resources - Describe how to manage users and access control - Describe the tools and methods for managing HPE Private Cloud AI - Explain how to monitor HPE Private Cloud AI performance and health
Installing and Configuring HPE Private Cloud AI Solutions	30%	- Describe the prerequisites for installing HPE Private Cloud AI - Explain how to deploy and configure HPE Private Cloud AI components - Identify the steps to configure the HPE Private Cloud AI environment - Identify how to access and use HPE Private Cloud AI management interfaces - Describe how to validate the HPE Private Cloud AI installation

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HPE2-B08최신 업데이트 덤프 덤프자료는 HPE Private Cloud AI Solutions 최고의 시험대비자료

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최신 Hybrid Cloud HPE2-B08 무료샘플문제 (Q41-Q46):

질문 # 41
A customer is building a large-scale AI training cluster using HPE Private Cloud AI.
They have two main requirements for the storage solution:
1. It must provide extremely high throughput and low latency to feed data to a large cluster of NVIDIA H100 GPUs.
2. It must be able to scale performance and capacity independently to accommodate future growth without costly overprovisioning.
The architect is proposing HPE GreenLake for File Storage.
Which architectural features of this solution directly address the customer's requirements? (Select all that apply.)
```
Customer Requirements:
1. High performance for AI training workloads.
2. Independent scaling of performance and capacity.
```

A. It uses a disaggregated architecture, allowing controller nodes (performance) and storage shelves (capacity) to be scaled separately.
B. It is managed exclusively through a command-line interface (CLI) for maximum control.
C. It relies on traditional hard disk drives (HDDs) for cost-effective capacity, with a small flash tier for caching.
D. It supports GPUDirect Storage (GDS) over a high-speed NVMe-oF (RoCE) network, enabling a direct, low-latency path between storage and GPUs.
E. It includes HPE Data Fabric, providing a global namespace across the worker nodes' local drives.

정답：A,D

질문 # 42
A financial services company, currently at the 'AI Pro' maturity level, wants to build a private cloud solution to support two primary initiatives:
1. Initiative 1: Fine-tune a proprietary 70B parameter LLM for fraud detection, requiring maximum training performance.
2. Initiative 2: Deploy a customer-facing RAG-based chatbot for 500 concurrent users.
The customer wants a single, integrated solution that can handle both workloads efficiently. They have a new data center with ample power and cooling.
Which HPE Private Cloud AI configuration should the architect recommend?

A. Two separate solutions: a Small - Expanded for the RAG workload and a Large - Standard for the fine-tuning workload.
B. A custom-built solution using HPE ProLiant DL325 servers and NVIDIA L4 GPUs.
C. Medium - Expanded, because it supports a high number of concurrent users for RAG.
D. Large - Expanded, because its NVIDIA H100 NVL GPUs and eight worker nodes are required for the intensive fine-tuning workload.

정답：D

질문 # 43
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 downgrade the recommendation to a "Medium - Standard (2-node)" configuration.
B. It will have no effect, as the number of users is the primary factor.
C. It will require the architect to switch to the "application capacity" sizing method.
D. It will upgrade the recommendation to a "Large - Standard (4-node)" configuration.

정답：A

질문 # 44
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. Select the "HPE Private Cloud AI - Small - Expanded" Smart Template within HPE One Config Advanced (OCA).
B. Use the standard HPE ProLiant DL380a Gen11 server template in OCA and add the GPUs and networking manually.
C. Send the output from the HPE Intelligent Configurator directly to the distribution partner for a quote.
D. Manually add each component (servers, GPUs, switches, cables, etc.) one by one into HPE One Config Advanced (OCA).

정답：A

질문 # 45
An architect is sizing an HPE Private Cloud AI solution. The customer plans to deploy a generative AI application for 150 concurrent users that requires Retrieval-Augmented Generation (RAG).
The architect enters the following into the HPE Intelligent Configurator:
```
- Use case: Text Generation
- Number of users: 100-250
- RAG: Yes
- Model: Llama 2 13B (tool default for this use case)
```
Based on the provided inputs, which HPE Private Cloud AI configuration will the HPE Intelligent Configurator most likely recommend?

A. Small - Expanded (2-node)
B. Small - Standard (1-node)
C. Large - Standard (4-node)
D. Medium - Expanded (4-node)

정답：D

질문 # 46
......

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