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HP HPE2-B08 Exam Syllabus Topics:

HPE Private Cloud AI Solutions Sample Questions:

1. A customer is expanding their HPE Private Cloud AI "Medium" configuration to support a new generative AI inferencing workload. They are concerned about network congestion and latency, as the AI workload is known to generate large, sudden bursts of traffic between the compute nodes and the storage system.
The solution uses NVIDIA Spectrum SN4700M switches for the AI interconnect.
Which feature of these switches is specifically designed to handle bursty traffic and prevent packet loss in a lossless Ethernet fabric?

A) Integrated Silicon Root of Trust to validate the switch firmware integrity.
B) The ability to route traffic based on application-layer metadata.
C) A fully shared buffer architecture that can dynamically absorb traffic bursts from any port.
D) Support for Fibre Channel over Ethernet (FCoE) encapsulation.

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

3. A large enterprise is adopting HPE Private Cloud AI and needs to accelerate the development of several generative AI applications. Their data science team wants to leverage pre-trained foundation models from NVIDIA but needs to customize them for specific business tasks like contract summarization and internal policy Q&A.
Which NVIDIA AI Enterprise software framework provides a comprehensive, end-to-end toolkit for curating data, customizing models using techniques like PEFT, and implementing guardrails for safe deployment?
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Customer Goal:
- Accelerate development of custom generative AI apps
- Utilize pre-trained foundation models
- Require tools for data prep, model customization, and safety
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A) NVIDIA Triton Inference Server
B) NVIDIA NIM (NVIDIA Inference Microservices)
C) NVIDIA NeMo
D) NVIDIA RAPIDS

4. An AI development team is training a large language model that exceeds the memory capacity of a single GPU. To continue training, they need to distribute the workload across multiple GPUs within the same server.
Which combination of HPE server and NVIDIA technology is specifically designed to provide a high- bandwidth, direct communication path between GPUs, bypassing the PCIe bus for improved performance in multi-GPU training?

A) HPE ProLiant DL325 Gen11 server with NVIDIA L4 GPUs
B) HPE Alletra Storage MP with RoCE-capable network adapters
C) HPE ProLiant DL380a Gen11 server with GPUDirect Storage (GDS)
D) HPE ProLiant DL380a Gen12 server with an NVIDIA NVLink Bridge

5. A customer in the public sector wants to use AI to analyze live video feeds from city-wide cameras to automate public safety tasks like detecting traffic accidents or identifying security threats in real-time.
This is their first major AI initiative.
Which AI use case does this scenario represent?

A) Recommender Systems
B) Drug Discovery
C) Computer Vision / Intelligent Video Analytics
D) Natural Language Processing (NLP)

Solutions: