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HP HPE7-S01 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Manage Implementation and Startup of HPE AI and HPC Solutions | 2% | - Deployment and validation
|
| Topic 2: Demonstrate AI Solutions | 10% | - AI solution demonstration
|
| Topic 3: Design HPE Solutions for AI and HPC Workloads | 50% | - Solution architecture and design
|
| Topic 4: Explain HPE Compute AI and HPC Solution Components and Architecture | 38% | - Management and automation
|
HP Advanced HPE Compute Architect Solutions Written Sample Questions:
1. A customer is building a chatbot that incorporates an LLM. The customer wants to prevent the chatbot from responding to or generating toxic content.
What should you recommend to the customer?
A) Use NVIDIA NeMo Guardrails input and output rails.
B) Use NVIDIA Evaluator exact match checks.
C) Use NVIDIA Evaluator to check the LLM's F1 score.
D) Use NVIDIA NeMo Guardrails execution rails.
2. A customer reports lower-than-expected memory bandwidth on a two-socket ProLiant Gen11 server populated with 12 DIMMs per socket in an unbalanced pattern.
What should you recommend?
A) Set the memory operating speed manually to the maximum supported value
B) Replace RDIMMs with LRDIMMs of the same capacity
C) Enable Memory Interleaving in the UEFI workload profile
D) Populate DIMMs so that all memory channels per processor are equally populated
3. You are demonstrating HPE Private Cloud AI and HPE Machine Learning Inference Software to a customer. The customer says that the organization has a custom model, stored in an OpenLLM hub, which they would like to deploy with HPE Machine Learning Inference Software.
What should you explain?
A) While HPE Machine Learning Inference Software does not support deploying custom models, Ray Serve, also provided by HPE Private Cloud AI, does.
B) HPE Machine Learning Inference Software supports pulling this model from the hub and deploying it.
C) While HPE Machine Learning Inference Software does not support deploying custom models, KServe, also provided by HPE Private Cloud AI, does.
D) HPE Machine Learning Inference Software can deploy this model if the customer packages it with Bento Archive and saves it to a PVC in HPE Private Cloud AI.
4. A customer needs an upgrade for their ESXi hosts, and you are proposing HPE ProLiant DL servers. When you recommend using HPE custom ESXi images with these servers, the customer says that they have their own tools that they include on all images.
What should you explain?
A) The customer can create their own custom image with their tools and with the HPE bundles available in the vibsdepot.
B) The customer can rely on the tools and drivers included in the HPE custom image to replace the functions of the tools the customer is currently using.
C) The customer must use the custom image for ESXi to load successfully on the servers. However, the customer can add their tools to the OS manually after the server boots.
D) The customer should use an HPE OneView for vCenter OS Build Plan to combine their custom ESXi image with the HPE custom ESXi image.
5. An automotive engineering team is running inference workloads for traffic simulation and computer vision models using KServe on HPE Private Cloud AI.
The team also uses GPU-enabled notebooks running on HPE Private Cloud AI to experiment with new models. They want to automatically adjust GPU usage for the different models based on current demand, as well as ensure that the notebooks never prevent the inferencing workloads from receiving the GPUs they need.
Which two features support this functionality? (Choose two.)
A) Kyverno mutating admission policies
B) Canary roll outs for KServe
C) Autoscaling for KServe
D) HPE AI Essentials scheduler priorities
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: D | Question # 3 Answer: B | Question # 4 Answer: A | Question # 5 Answer: C,D |





