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HP HPE2-B08 Exam Syllabus Topics:

Section	Objectives
Topic 1: Data Management and Governance	- Data governance and compliance - Data lifecycle management
Topic 2: AI Infrastructure Design	- Networking for AI workloads - Storage and data pipeline design - Compute and GPU considerations
Topic 3: Deployment and Operations	- Deployment models for AI solutions - Monitoring and optimization - Lifecycle management of AI infrastructure
Topic 4: HPE Private Cloud AI Fundamentals	- Core AI workload characteristics - Overview of private cloud AI concepts
Topic 5: Security in Private Cloud AI	- Workload and data protection - Identity and access management
Topic 6: HPE GreenLake for AI Solutions	- Consumption-based IT model for AI - GreenLake architecture and services

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HPE Private Cloud AI Solutions Sample Questions (Q17-Q22):

NEW QUESTION # 17
An architect has generated a configuration for HPE Private Cloud AI in OCA. The customer wants to know if they can use their existing data center network switches for the high-performance AI interconnect instead of the NVIDIA Spectrum switches included in the BOM.
What is the correct response?

A. No, because the HPE Private Cloud AI solution is air-gapped and cannot connect to external switches.
B. Yes, any 200GbE switch can be substituted to lower the cost.
C. No, the NVIDIA Spectrum switches are part of the pre-validated, turnkey solution and are required for performance and support.
D. Yes, as long as the existing switches are also from NVIDIA, they are compatible.

Answer: C

NEW QUESTION # 18
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. Kyverno
B. JupyterLab
C. Prometheus
D. Apache Airflow

Answer: D

NEW QUESTION # 19
The three pre-defined sizes (Small, Medium, Large) of HPE Private Cloud AI are designed to address different primary workloads. Match the configuration size to its intended primary workload.
*Configuration Size:
1. Small
2. Medium
3. Large
*Primary Workload:
a. AI Inferencing with RAG and large-scale Fine-Tuning
b. AI Inferencing
c. AI Inferencing with RAG

A. 1-b, 2-c, 3-a
B. 1-a, 2-b, 3-c
C. 1-b, 2-a, 3-c
D. 1-c, 2-a, 3-b

Answer: A

NEW QUESTION # 20
An organization is deploying a multi-tenant AI environment using HPE Private Cloud AI. They need to run several smaller, independent AI inference workloads on a single, powerful NVIDIA H100 GPU to maximize resource utilization. Each workload must be securely isolated with its own dedicated portion of the GPU's compute and memory resources.
What key NVIDIA technology, supported on the Hopper architecture, allows for this secure partitioning of a single physical GPU? (Select all that apply.)

A. GPUDirect Storage (GDS)
B. NVLink Bridge
C. Multi-Instance GPU (MIG)
D. Remote Direct Memory Access (RDMA)
E. Confidential Computing

Answer: C,E

NEW QUESTION # 21
A data science team is struggling to manage their AI/ML projects. They use a variety of open-source tools for data preparation, training, and MLOps, but integrating them is complex and time-consuming.
They need a unified platform that provides self-service access to a curated and pre-integrated set of these tools.
Which HPE Private Cloud AI software component is specifically designed to solve this problem?

A. NVIDIA NIM
B. HPE GreenLake for File Storage
C. HPE AI Essentials
D. HPE Intelligent Configurator

Answer: C

NEW QUESTION # 22
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