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HP HPE7-S01 Exam Syllabus Topics:

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

HP Advanced HPE Compute Architect Solutions Written Sample Questions:

You are proposing 32 HPE Cray XD670 systems with HPE Performance Cluster Manager (HPCM) to a customer.
What is one benefit of HPCM that you should emphasize?

  • A. HPCM provides GPU-compatible scheduling software for HPC jobs.
  • B. HPCM enables the systems to support secure boot and hardware root of trust.
  • C. HPCM integrates with HPE Compute Ops Management to provide a single interface for monitoring a system's health.
  • D. HPCM makes it much easier to deploy and patch the systems' operating systems.
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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

  • A. The memory available on the host and the number of convolutional layers in the model
  • B. The memory available on the host and the number of parameters in the model
  • C. The floating point precision and the number of layers in the model
  • D. The number of parameters in the model and the floating point precision
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Correct Answer: D  🗳️

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Which HPE Private Cloud AI configuration is designed for early development and prototyping use cases?

  • A. Large
  • B. Medium
  • C. Developer System
  • D. Small
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Correct Answer: C  🗳️

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What is a benefit of the storage component of HPE Private Cloud AI (small, medium, and large configurations)?

  • A. It is built from the all-flash local drives on the AI-optimized nodes to provide the lowest latency.
  • B. It is built on GreenLake for File Storage, which supports low latency communications.
  • C. It is built from hybrid local drives on the AI-optimized nodes to balance performance and cost- effectiveness.
  • D. It is built on GreenLake for File Storage, which supports both NFS and Lustre for mixed AI workloads.
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Correct Answer: B  🗳️

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A customer is evaluating whether to run their AI proof of concept (PoC) in the cloud or on-prem.
They store sensitive data and require low-latency performance.
Which factor supports running the PoC in the data center?

  • A. Need to procure the resources as quickly as possible
  • B. Preference for short-term licensing agreements
  • C. Latency considerations for sensitive data stored locally
  • D. Desire to minimize staff training on container platforms
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Correct Answer: C  🗳️

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