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| Section | Objectives |
|---|
| Topic 1: AI Infrastructure Design | - Networking for AI workloads - Compute and GPU considerations - Storage and data pipeline design
|
| Topic 2: HPE Private Cloud AI Fundamentals | - Overview of private cloud AI concepts - Core AI workload characteristics
|
| Topic 3: HPE GreenLake for AI Solutions | - GreenLake architecture and services - Consumption-based IT model for AI
|
| Topic 4: Security in Private Cloud AI | - Identity and access management - Workload and data protection
|
| Topic 5: Data Management and Governance | - Data lifecycle management - Data governance and compliance
|
| Topic 6: Deployment and Operations | - Deployment models for AI solutions - Monitoring and optimization - Lifecycle management of AI infrastructure
|
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HPE Private Cloud AI Solutions Sample Questions (Q66-Q71):
NEW QUESTION # 66
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?
- A. NVIDIA NVLink Bridge
- B. RDMA over Converged Ethernet (RoCE)
- C. PCI Express (PCIe) Gen5
- D. GPUDirect Storage (GDS)
Answer: A
NEW QUESTION # 67
A customer needs a solution for AI inferencing at the edge for a computer vision application. They have determined a Small configuration of HPE Private Cloud AI is sufficient. The solution also requires several value-added services, including an AI transformation workshop and a data design service.
How should an architect attach these services in One Config Advanced (OCA)?
- A. The architect must open a support ticket with HPE to have the services added to the quote.
- B. The services can be selected and added to the configuration as optional line items within OCA.
- C. The services must be quoted separately from the hardware and software configuration.
- D. The services are automatically included in the Smart Template and require no action.
Answer: B
NEW QUESTION # 68
A customer wants a single platform to handle the following workloads:
* Real-time fraud detection using a trained model (Inference).
* A chatbot for internal support that uses a corporate knowledge base (RAG).
* Quarterly updates to their custom logistics model (Fine-tuning).
The customer is an 'AI Pro' looking for a turnkey, on-premises cloud experience.
Which HPE solution is designed to handle this mix of inference, RAG, and fine-tuning workloads?
- A. A standalone cluster of AI-optimized HPE ProLiant servers
- B. HPE GreenLake for File Storage
- C. A dedicated HPE Cray system
- D. HPE Private Cloud AI with NVIDIA
Answer: D
NEW QUESTION # 69
An architect uses the HPE Intelligent Configurator for a customer with 120 concurrent users for a text generation task with RAG. The tool recommends a "Medium - Expanded (4-node)" configuration. The customer then reveals they want to use a smaller, more efficient 7B parameter model instead of the 13B model the tool defaulted to.
How will this change in model size likely affect the sizing tool's recommendation?
- A. It will have no effect, as the number of users is the primary factor.
- B. It will upgrade the recommendation to a "Large - Standard (4-node)" configuration.
- C. It will downgrade the recommendation to a "Medium - Standard (2-node)" configuration.
- D. It will require the architect to switch to the "application capacity" sizing method.
Answer: C
NEW QUESTION # 70
A customer's distributed AI training job is experiencing poor performance. An analysis reveals high network latency. The architect suspects a misconfiguration in the NVIDIA Spectrum switches that form the RoCE-based AI fabric.
They review the following configuration snippet from one of the switch ports connected to a compute node:
```
interface ethernet 1/1
description "Connection to PCAI-Node-1"
speed 200G
mtu 9216
switchport mode trunk
## Priority Flow Control (PFC) is disabled on this port
```
What is the most likely cause of the performance issue?
- A. Priority Flow Control (PFC) is disabled, which is mandatory for a lossless RoCE fabric.
- B. The MTU size is too small for AI workloads.
- C. The port is incorrectly configured in trunk mode instead of access mode.
- D. The port speed is not sufficient for the connected H100 GPU.
Answer: A
NEW QUESTION # 71
......
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