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HP HPE2-B08 Exam Syllabus Topics:

HPE Private Cloud AI Solutions Sample Questions:

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

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

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

3. An architect is assessing a customer's workloads to position the correct HPE Private Cloud AI configuration. The customer has a single, massive task: training a foundational vision model from scratch using a petabyte-scale image dataset. The project is expected to take months and requires the absolute maximum compute performance available.
Which AI workload type does this represent, and which HPE solution is most appropriate?

A) Workload: AI Inferencing; Solution: AI-optimized HPE ProLiant DL servers
B) Workload: RAG; Solution: HPE Private Cloud AI - Medium configuration
C) Workload: Edge Computing; Solution: HPE ProLiant DL320 server
D) Workload: AI Model Training; Solution: HPE Cray Systems

4. An architect is working with a customer who has been identified as an 'AI Pro'. They have a mature AI practice and are looking to scale their efforts in creating 'digital twin' simulations for automotive prototypes. This involves complex, graphics-intensive AI workloads. The customer wants a full-stack, turnkey private cloud solution to accelerate this initiative.
What is the most appropriate HPE solution to position for this customer?

A) A custom solution built on individual HPE ProLiant servers.
B) A set of AI-optimized HPE ProLiant DL servers for edge deployment.
C) HPE Private Cloud AI with NVIDIA.
D) An HPE AI Services - Transformation Workshop to redefine their goals.

5. In a Natural Language Processing (NLP) task, what is the role of a tokenizer?

A) To apply a final activation function to determine the output class.
B) To convert a sentence of raw text into a sequence of numerical tokens that a model can process.
C) To encrypt the input text to ensure data privacy during model training.
D) To train the neural network using backpropagation.

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