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HP HPE7-S01 Exam Syllabus Topics:

SectionWeightObjectives
Explain HPE Compute AI and HPC Solution Components and Architecture38%- Management and automation
  • 1. HPE GreenLake
  • 2. Lifecycle management
  • 3. HPE OneView
- HPE Compute portfolio
  • 1. HPE Synergy
  • 2. HPE ProLiant servers
  • 3. HPE Cray systems
- AI and HPC architectures
  • 1. High-performance workload platforms
  • 2. NVIDIA integration
  • 3. GPU-accelerated computing
Manage Implementation and Startup of HPE AI and HPC Solutions2%- Deployment and validation
  • 1. Implementation planning
  • 2. Operational readiness
  • 3. Configuration verification
Design HPE Solutions for AI and HPC Workloads50%- Solution architecture and design
  • 1. Workload analysis
  • 2. Performance optimization
  • 3. Capacity planning
- Infrastructure integration
  • 1. Scalability and resiliency design
  • 2. Compute, storage, and networking integration
  • 3. Hybrid cloud architectures
Demonstrate AI Solutions10%- AI solution demonstration
  • 1. Customer use cases
  • 2. Solution positioning
  • 3. Business value presentation

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HP Advanced HPE Compute Architect Solutions Written Exam Sample Questions (Q69-Q74):

NEW QUESTION # 69
A customer must encrypt OS volumes using BitLocker with hardware-backed key protection on new ProLiant Gen11 servers.
What must be present?

Answer: A

Explanation:
BitLocker uses TPM 2.0 to seal the volume encryption key to platform measurements. Controller- based Secure Encryption and SEDs protect data at rest at the drive level but do not provide the TPM key protector BitLocker requires.


NEW QUESTION # 70
You are configuring a proposal for HPE ProLiant servers to act as vSAN nodes in a new ESA cluster.
What is one piece of information needed to determine the nodes' drive capacity requirements?

Answer: C

Explanation:
vSAN ESA capacity sizing depends on the storage policy, especially Failures to Tolerate (FTT), because FTT determines the RAID/data placement overhead and therefore the required usable drive capacity.
Reference: https://blogs.vmware.com/cloud-foundation/2022/11/02/capacity-overheads-for-the- esa-in-vsan-8/


NEW QUESTION # 71
Which component, included in HPE Private Cloud AI, can customers use to automate a data pipeline, based on a series of Spark Applications?

Answer: B

Explanation:
Airflow is used to orchestrate and automate data pipelines as DAGs, including workflows that run a series of Spark Applications. MLIS is for inference, Ray is for distributed compute, and MLflow is for experiment/model tracking.


NEW QUESTION # 72
A customer plans to implement machine learning models but has limited visibility into where business data is generated and how it is managed across departments.
During the readiness assessment, which step will best support an accurate evaluation of their AI deployment potential?

Answer: D

Explanation:
AI readiness depends on understanding where data comes from, who owns it, how it is formatted, and how it moves between systems. This establishes whether the organization can support accurate, secure, and scalable AI deployment.


NEW QUESTION # 73
Which factors should you consider when determining the GPU memory requirements for inferencing an AI model?

Answer: D

Explanation:
GPU memory for inferencing is primarily driven by the model size, which depends on the number of parameters and the precision used to store them, such as FP32, FP16, BF16, or INT8.


NEW QUESTION # 74
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