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HP HPE7-S01 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Explain HPE Compute AI and HPC Solution Components and Architecture38%- HPE Compute portfolio
  • 1. HPE Cray systems
  • 2. HPE Synergy
  • 3. HPE ProLiant servers
- AI and HPC architectures
  • 1. High-performance workload platforms
  • 2. NVIDIA integration
  • 3. GPU-accelerated computing
- Management and automation
  • 1. HPE OneView
  • 2. HPE GreenLake
  • 3. Lifecycle management
Topic 2: Demonstrate AI Solutions10%- AI solution demonstration
  • 1. Customer use cases
  • 2. Solution positioning
  • 3. Business value presentation
Topic 3: Design HPE Solutions for AI and HPC Workloads50%- Solution architecture and design
  • 1. Performance optimization
  • 2. Capacity planning
  • 3. Workload analysis
- Infrastructure integration
  • 1. Scalability and resiliency design
  • 2. Compute, storage, and networking integration
  • 3. Hybrid cloud architectures
Topic 4: Manage Implementation and Startup of HPE AI and HPC Solutions2%- Deployment and validation
  • 1. Operational readiness
  • 2. Implementation planning
  • 3. Configuration verification

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HP Advanced HPE Compute Architect Solutions Written Exam Sample Questions (Q55-Q60):

NEW QUESTION # 55
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.)

Answer: A,D

Explanation:
KServe autoscaling adjusts inference deployment capacity based on demand. HPE AI Essentials scheduler priorities ensure higher-priority inference workloads can get GPUs ahead of lower- priority notebook workloads.
Reference: https://kserve.github.io/website/docs/model-serving/predictive- inference/autoscaling/hpa-autoscaler
https://support.hpe.com/hpesc/public/docDisplay?docId=a00aie17hen_us&docLocale=en_US&pa ge=pcai%2FGenAI%2Fdeploying-knowledge-base.html


NEW QUESTION # 56
An HPE Private Cloud AI administrator is running multiple AI workloads and needs insight into which workloads are using resources.
Which HPE Private Cloud AI feature helps to deliver this visibility?

Answer: B

Explanation:
The GPU Control Panel shows workload/framework resource visibility, including assigned vGPUs, pod details, workload status, priority, and GPU utilization charts. This directly helps administrators see which AI workloads are consuming resources.
Reference:
https://support.hpe.com/hpesc/public/docDisplay?docId=a00aie111dhen_us&docLocale=en_US& page=ManageClusters%2Fconfigure-idle-reclaim.html


NEW QUESTION # 57
What is one benefit of the HPE curated images for Spark provided in HPE AI Essentials?

Answer: D

Explanation:
HPE-curated Spark images are designed to work with HPE AI Essentials data sources; for these images, users can access configured sources without manually distributing secrets, unlike generic Spark OSS images.
Reference:
https://support.hpe.com/hpesc/public/docDisplay?docId=a00aie111dhen_us&docLocale=en_US& page=Spark%2Fcreating_spark_application.html


NEW QUESTION # 58
What is one benefit of the NVIDIA AI Enterprise license provided in HPE Private Cloud AI?

Answer: C

Explanation:
The NVIDIA AI Enterprise license in HPE Private Cloud AI provides entitlement to NVIDIA enterprise AI software components used in AI workflows/blueprints, helping customers build and deploy AI applications faster.
Reference: https://docs.nvidia.com/ai-enterprise/software/latest/index.html
https://www.nvidia.com/en-us/data-center/products/ai-enterprise/


NEW QUESTION # 59
You are recommending HPE ProLiant DL servers and HPE Alletra Storage MP B10000 for a customer's Red Hat OpenShift platform.
What should you recommend to simplify storage provisioning for workloads running on the platform?

Answer: C

Explanation:
The HPE CSI Driver/Operator for Kubernetes enables dynamic provisioning and management of persistent storage for Kubernetes/OpenShift workloads on HPE Alletra Storage MP B10000.
vVols are for VMware environments, not OpenShift workload storage provisioning.


NEW QUESTION # 60
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