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| Section | Objectives |
|---|---|
| Topic 1: HPE Private Cloud AI Fundamentals | - Core AI workload characteristics - Overview of private cloud AI concepts |
| Topic 2: Security in Private Cloud AI | - Identity and access management - Workload and data protection |
| Topic 3: Data Management and Governance | - Data lifecycle management - Data governance and compliance |
| Topic 4: AI Infrastructure Design | - Networking for AI workloads - Storage and data pipeline design - Compute and GPU considerations |
| Topic 5: Deployment and Operations | - Deployment models for AI solutions - Lifecycle management of AI infrastructure - Monitoring and optimization |
| Topic 6: HPE GreenLake for AI Solutions | - GreenLake architecture and services - Consumption-based IT model for AI |
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NEW QUESTION # 29
An architect is positioning an HPE Private Cloud AI solution to a customer who is an "AI Pro." The customer's CIO is the key decision maker.
Which benefits of the solution would be most compelling to this stakeholder? (Choose 2.)
Answer: A,E
NEW QUESTION # 30
A customer in the media and entertainment industry wants a solution to accelerate the creation of 3D animations and renderings. Their artists need to be able to generate complex visual AI content quickly.
The company has a mature AI practice and requires a powerful, data center-based solution.
Which HPE ProLiant server and NVIDIA GPU combination is purpose-built for these generative visual AI workloads?
Answer: C
NEW QUESTION # 31
An architect is designing an infrastructure solution for an AI workload that involves processing massive datasets for training. The goal is to minimize data transfer latency between the storage system and the GPUs in the compute nodes. The architect wants to enable the NVIDIA GPUs to fetch data directly from the NVMe storage array, bypassing the server's CPU and main memory.
Review the proposed architectural components:
```
- Compute Nodes: HPE ProLiant DL380a Gen11 with NVIDIA H100 GPUs
- Storage: HPE GreenLake for File Storage
- Interconnect: Ethernet with RoCE support
```
Which technology must be enabled and properly configured across these components to achieve this direct GPU-to-storage data path? (Choose 2.)
Answer: A,E
NEW QUESTION # 32
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?
Answer: B
NEW QUESTION # 33
A customer who is an "AI Beginner" wants to start an AI inferencing project at their edge locations.
Their goal is to analyze security camera feeds to help prevent theft. They have a limited budget and IT staff at the edge sites.
Which HPE AI solution is the most appropriate to position for this specific scenario?
Answer: C
NEW QUESTION # 34
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