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HP HPE2-B08 Exam Syllabus Topics:

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

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HPE Private Cloud AI Solutions Sample Questions (Q22-Q27):

NEW QUESTION # 22
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 AMD processors, while the Small and Medium configurations use Intel processors.
B. The Large configuration is the only one that includes HPE GreenLake for File Storage.
C. The Large configuration uses NVIDIA H100 NVL GPUs, while the Small and Medium configurations use NVIDIA L40S GPUs.
D. The Large configuration is deployed in a single rack, while the Small and Medium require two racks.

Answer: C

NEW QUESTION # 23
An architect has used the HPE Intelligent Configurator and determined that a "Medium - Standard" configuration is required.
When creating the final quote in One Config Advanced (OCA), what is the mandatory prerequisite that the customer is responsible for providing for the solution to be valid?

A. A list of all end-users who will access the system.
B. A subscription to the NVIDIA NGC catalog for downloading AI models.
C. A rack elevation diagram for the data center.
D. A valid, bring-your-own-license (BYOL) for VMware vSphere Foundation (VVF) or VMware Cloud Foundation (VCF).

Answer: D

NEW QUESTION # 24
A customer has selected the "HPE Private Cloud AI - Medium - Expanded" configuration.
Which of the following resource counts correctly describes this specific configuration?

A. 4 worker nodes, 16 total L40S GPUs, single rack
B. 4 worker nodes, 16 total H100 NVL GPUs, dual rack
C. 2 worker nodes, 8 total L40S GPUs, single rack
D. 8 worker nodes, 32 total H100 NVL GPUs, dual rack

Answer: A

NEW QUESTION # 25
You are positioning HPE Private Cloud AI to a customer who is an "AI Pro" and wants to scale their generative AI efforts.
Which key capabilities of the solution would you emphasize to this customer? (Select all that apply.)

A. Its turnkey nature, which simplifies deployment and allows their expert team to focus on building models rather than integrating infrastructure.
B. The option to choose a Large configuration with powerful NVIDIA H100 GPUs and a high-speed RoCE fabric for demanding fine-tuning workloads.
C. Its ability to run on a single, low-power server for maximum efficiency.
D. A simple, web-based interface for beginners to learn about AI concepts.
E. The inclusion of a full-stack, enterprise-supported software suite including NVIDIA AI Enterprise and HPE AI Essentials.

Answer: A,B,E

NEW QUESTION # 26
A data analytics team is running workloads on an HPE Private Cloud AI solution. They observe that a data ingestion job is not meeting performance expectations, suspecting a CPU bottleneck. They believe the application is not correctly leveraging GPUDirect Storage (GDS), forcing data to be copied through the server's main memory before reaching the GPU.
Which are valid reasons why GDS might not be functioning correctly? (Choose 3.)

A. The HPE GreenLake for File Storage array is using SATA SSDs instead of NVMe SSDs.
B. The network switches are not configured for lossless operation (e.g., PFC is disabled).
C. The NVIDIA GPUs have been configured with Multi-Instance GPU (MIG), which enhances GDS performance.
D. The application is using a standard TCP/IP socket for data transfer instead of an RDMA-based library.
E. The NVIDIA peer memory driver has not been installed on the guest VM.

Answer: B,D,E

NEW QUESTION # 27
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