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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: High Performance Computing (HPC) Design and Management | 10% | - Architecture and scaling - Management and monitoring |
| Topic 2: NVIDIA AI Enterprise and Model Serving | 10% | - Model serving architecture and optimization - Software deployment and management |
| Topic 3: Troubleshooting HPE Private Cloud AI | 10% | - Issue diagnosis and resolution - Performance tuning and optimization |
| Topic 4: HPE AI Essentials: Data Analytics and Data Science | 15% | - Analytics and machine learning tools - Data pipelines and processing |
| Topic 5: Solution Optimization and Security | 5% | - Efficiency and resilience - Security best practices |
| Topic 6: HPE ProLiant Gen12 for AI | 20% | - GPU integration and configuration - AI-optimized compute design - Server architecture and components |
| Topic 7: Integration with Third-Party Platforms | 15% | - Red Hat OpenShift and Kubernetes integration - VMware integration |
| Topic 8: AI Workshops and HPE AI Essentials Platform | 15% | - Customer engagement and assessment - Platform capabilities and deployment |
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NEW QUESTION # 59
Which benefit does HPE Rear Door Heat Exchanger (RDHX) provide?
Answer: A
Explanation:
A is correct. An HPE Rear Door Heat Exchanger is a liquid-to-air heat-removal solution mounted at the rear of the rack. Server exhaust air passes through the heat exchanger, where heat is transferred into the facility liquid loop before the air returns to the room. By removing a substantial portion of the rack's heat load locally, an RDHX can reduce the burden on room-level air-conditioning infrastructure and therefore lower cooling energy consumption.
Option B is incorrect because an RDHX does not change the thermal operating limits of the servers; hardware still must remain within its specified inlet-temperature and environmental ranges. Option C is contradictory:
liquid heat exchange requires an appropriate facility water or coolant connection at or near the rack. Option D is also false. Servers still require their designed heat sinks, fans, airflow paths, and component-level thermal controls; the rear-door exchanger handles exhaust heat rather than replacing internal cooling components.
For high-density AI and HPC systems, cooling architecture is part of workload design because accelerator power density can become a rack and facility constraint.
References/topics: Advanced HPE Compute Solutions, Rev. 26.21, Module 1 "Liquid cooling options with HPE ProLiant Compute Gen12"; HPE rear-door heat-exchanger and data-center cooling documentation.
NEW QUESTION # 60
You are planning to demonstrate how you can use KServe to run NIMs on HPE Private Cloud AI.
You have downloaded the CodeLlama-70B-Instruct model to a volume in your namespace named demo-model. The objects that you are planning to deploy are shown below:
What change should you make to the objects?
Answer: A
Explanation:
The model is already downloaded to a PVC, so the InferenceService must reference that PVC with storageUri. KServe then mounts the model storage for the predictor; you do not change the model format or ServingRuntime. More precisely, this belongs under the predictor's model spec as storageUri.
NEW QUESTION # 61
A customer wants to manage the full lifecycle of their HPE ProLiant Gen11 servers - including firmware updates, monitoring, and remote console access - from a single cloud-based console without deploying an on-premises management appliance. Which HPE solution should the integrator recommend?
Answer: C
Explanation:
HPE Compute Ops Management is the cloud-based, GreenLake-delivered management platform for ProLiant/Synergy/Apollo systems, providing lifecycle management, monitoring, and remote console access without requiring a local management appliance. HPE OneView is typically deployed on-premises (or as a VM), Insight Remote Support is focused on support-case automation, and SIM is a legacy product.
NEW QUESTION # 62
A hospital wants to fine-tune an LLM on their own dataset. However, the data needs to have sensitive information redacted.
Duplicate records also need to be cleaned up.
What can the customer use to achieve this goal?
Answer: C
Explanation:
D is correct. NVIDIA NeMo Curator is the data-curation component intended to prepare large datasets for generative-AI training and fine-tuning. Its pipeline capabilities include filtering, quality processing, deduplication, and privacy-oriented data preparation. That directly matches both requirements in the scenario:
duplicate records must be removed and sensitive information must be redacted before the hospital's dataset is used to adapt the LLM. Performing these controls before fine-tuning reduces data leakage risk and prevents repeated records from biasing training.
The distractors address different stages of the AI lifecycle. MLflow is principally used for experiment tracking, model lifecycle management, and related MLOps functions; it is not the primary tool for cleansing the raw training corpus. NeMo Customizer performs model customization or fine-tuning after an appropriate dataset has been prepared. Katib is a Kubernetes-native hyperparameter-optimization component and does not provide the required privacy redaction and deduplication workflow.
The sequencing matters: curate the data first, then customize and evaluate the model. That separation is part of the software-stack knowledge expected for HPE Private Cloud AI with NVIDIA.
References/topics: Advanced HPE Compute Solutions, Rev. 26.21, Module 5 "Using NVIDIA AI Enterprise and Serving Models," NeMo deep dive; NVIDIA NeMo Curator documentation.
NEW QUESTION # 63
An HPE Private Cloud AI Administrator has imported a custom framework. Users can click the framework's endpoint link and access the framework successfully. However, sometimes users will try to go to the framework's page and they get an error.
What is one thing to investigate?
Answer: A
Explanation:
References/topics: Advanced HPE Compute Solutions, Rev. 26.21, Module 3 imported-framework communications and troubleshooting; HPE7-S02 Release Notes, June 15, 2026, framework-import updates and automatic Keycloak redirect URL handling.
NEW QUESTION # 64
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