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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) The inclusion of a full-stack, enterprise-supported software suite including NVIDIA AI Enterprise and HPE AI Essentials.
C) Its ability to run on a single, low-power server for maximum efficiency.
D) Its turnkey nature, which simplifies deployment and allows their expert team to focus on building models rather than integrating infrastructure.
E) A simple, web-based interface for beginners to learn about AI concepts.

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

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

4. An IT director for a regional retail chain tells you they are "doing AI." Upon further questioning, you learn they have one data scientist who has built a single, experimental sales forecasting model as a proof-of-concept (PoC). The project lacks clear KPIs for success and there is no formal strategy for how to productionize it or what to do next.
How would you classify this customer's AI maturity level?

A) AI Curious
B) AI Beginner
C) Deployer of AI at scale
D) AI Pro

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

Solutions: