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HP HPE2-B08 Exam Syllabus Topics:

HPE Private Cloud AI Solutions Sample Questions:

1. 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) The option to choose a Large configuration with powerful NVIDIA H100 GPUs and a high-speed RoCE fabric for demanding fine-tuning workloads.
B) Its turnkey nature, which simplifies deployment and allows their expert team to focus on building models rather than integrating infrastructure.
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.

2. An architect is designing a high-performance computing environment for a customer with two distinct, demanding workloads:
1. A large-scale, multi-node deep learning model that requires the fastest possible server-to-server communication.
2. A data-intensive analytics workload that requires the fastest possible data ingestion from an HPE GreenLake for File Storage array.
Which combination of technologies from the HPE Private Cloud AI solution should the architect select to optimize both workloads? (Select all that apply.)

A) A flat TCP/IP network for simplicity, relying on the speed of the 200GbE adapters.
B) InfiniBand for the server-to-server fabric and Fibre Channel for the storage fabric.
C) Multi-Instance GPU (MIG) to partition GPUs for each workload.
D) NVLink for intra-server GPU communication and RoCE for the server-to-server and server-to-storage fabric.
E) GPUDirect Storage (GDS) to enable a direct data path between storage and GPUs for the analytics workload.

3. 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 ProLiant DL380a server with NVIDIA H100 NVL GPUs
B) HPE Cray system with NVIDIA Grace Hopper Superchips
C) HPE ProLiant DL320 Gen11 server with NVIDIA L4 GPUs
D) HPE ProLiant DL384 Gen12 server with NVIDIA H200 NVL GPUs

4. A customer states they need an AI solution for a "summarization" use case that will be accessed by approximately 75 concurrent users. The underlying data is updated frequently, so RAG will be required.
When using the HPE Intelligent Configurator, which three inputs are mandatory to get an initial sizing recommendation?

A) RAG requirement, Power and cooling capacity, Desired software license term
B) Number of users, Preferred GPU model, Data center location
C) Use case, Number of users, RAG requirement
D) Use case, Model choice, Network switch preference

5. A customer's distributed AI training job is experiencing poor performance. An analysis reveals high network latency. The architect suspects a misconfiguration in the NVIDIA Spectrum switches that form the RoCE-based AI fabric.
They review the following configuration snippet from one of the switch ports connected to a compute node:
```
interface ethernet 1/1
description "Connection to PCAI-Node-1"
speed 200G
mtu 9216
switchport mode trunk
## Priority Flow Control (PFC) is disabled on this port
```
What is the most likely cause of the performance issue?

A) The port is incorrectly configured in trunk mode instead of access mode.
B) The port speed is not sufficient for the connected H100 GPU.
C) Priority Flow Control (PFC) is disabled, which is mandatory for a lossless RoCE fabric.
D) The MTU size is too small for AI workloads.

Solutions: