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HP HPE2-B08 Exam Syllabus Topics:

HPE Private Cloud AI Solutions Sample Questions:

Question 1

An enterprise wants to deploy pre-trained foundation models from various sources for multiple business units. A key requirement is to simplify and standardize the deployment process, regardless of the model's origin. They want a solution that packages models into scalable, optimized, and easy-to-use microservices with a standard API.
Which component of the NVIDIA AI Enterprise software suite directly addresses this need?

A. NVIDIA TAO Toolkit
B. NVIDIA Triton Inference Server
C. NVIDIA NeMo
D. NVIDIA NIM (NVIDIA Inference Microservices)

Question 2

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

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

Question 4

A customer needs a solution for two primary workloads: large-scale model training and real-time inference. They have a team of data scientists who are constantly developing new models and a separate operations team that deploys and manages these models in production.
Which statement best describes how the different stakeholders would interact with the HPE Private Cloud AI solution?

A. Both the data scientists and the operations team would use the HPE Intelligent Configurator to manage the models.
B. The entire process for all stakeholders is managed through the server's iLO interface.
C. The data scientists would primarily use tools within HPE AI Essentials (like JupyterLab and MLFlow) for model development, while the operations team would use NVIDIA NIMs to deploy the finished models.
D. The data scientists would use NVIDIA NIMs to train the models, and the operations team would use HPE Data Fabric to serve them.

Question 5

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

Solutions: