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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Fundamental AI Concepts | 28% | - Impact of AI on industries and infrastructure requirements - General AI concepts, applications and workloads |
| Topic 2: Software Components of HPE Private Cloud AI with NVIDIA | 20% | - Benefits of HPE and NVIDIA software stack - Software functions supporting AI operations |
| Topic 3: Solution Sizing and Configuration | 17% | - Using HPE Intelligent Configurator for sizing - Differences between configuration sizes and options - Building configurations via One Config Advanced (OCA) |
| Topic 4: Infrastructure Components of HPE Private Cloud AI with NVIDIA | 20% | - Infrastructure capabilities for AI workload requirements - Benefits of HPE and NVIDIA integrated infrastructure |
| Topic 5: Customer Assessment and Solution Positioning | 15% | - Position appropriate HPE AI solutions - Assess AI maturity, workload characteristics and use cases |
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NEW QUESTION # 47
An architect is designing a distributed training solution using HPE Private Cloud AI. The solution involves multiple HPE ProLiant DL380a servers, each with four NVIDIA H100 GPUs.
Review the logical network topology:
```
[HPE ProLiant Server 1] \
- GPU 0 <--> GPU 1 (Internal)
- GPU 2 <--> GPU 3 (Internal)
\
[NVIDIA Spectrum Switch (RoCE)] <--> [HPE GreenLake for File Storage]
/
[HPE ProLiant Server 2] /
- GPU 0 <--> GPU 1 (Internal)
- GPU 2 <--> GPU 3 (Internal)
```
Which interconnect technology facilitates the highest-bandwidth communication path labeled "(Internal)" for scaling the training job across the GPUs within a single server?
Answer: A
NEW QUESTION # 48
A customer is building an application to classify images of defective products on a manufacturing line.
Which type of neural network layer is essential for this model to automatically learn and identify visual features like edges, corners, and textures in the images?
Answer: D
NEW QUESTION # 49
A customer wants to deploy a turnkey private cloud for a variety of generative AI workloads, including RAG-based chatbots and some model fine-tuning. One of their key IT stakeholders is the data engineer.
Which specific challenge for a data engineer is directly addressed by the HPE Data Fabric component within HPE Private Cloud AI?
Answer: A
NEW QUESTION # 50
Match the stakeholder in an AI project to their most likely primary concern.
Stakeholders:
1. Data Scientist
2. AI Decision Maker (CIO)
3. Data Engineer
Concerns:
a. "How can I easily build, manage, and automate data pipelines to feed our models?" b. "What is the total cost of ownership (TCO) and return on investment (ROI) for this AI initiative?" c. "Which hyperparameter tuning method will give my model the highest accuracy?"
Answer: A
NEW QUESTION # 51
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.)
Answer: A,C,D
NEW QUESTION # 52
......
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