Exam Name: HPE Private Cloud AI Solutions
Certification Provider: HP
Corresponding Certification: Hybrid Cloud
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HP HPE2-B08 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Solution Sizing and Configuration | 17% | - Building configurations via One Config Advanced (OCA) - Using HPE Intelligent Configurator for sizing - Differences between configuration sizes and options |
| Fundamental AI Concepts | 28% | - General AI concepts, applications and workloads - Impact of AI on industries and infrastructure requirements |
| Software Components of HPE Private Cloud AI with NVIDIA | 20% | - Benefits of HPE and NVIDIA software stack - Software functions supporting AI operations |
| Customer Assessment and Solution Positioning | 15% | - Assess AI maturity, workload characteristics and use cases - Position appropriate HPE AI solutions |
| Infrastructure Components of HPE Private Cloud AI with NVIDIA | 20% | - Benefits of HPE and NVIDIA integrated infrastructure - Infrastructure capabilities for AI workload requirements |
HPE Private Cloud AI Solutions Sample Questions:
An enterprise wants to build an internal AI platform that functions like an "App Store." Their goal is to provide various internal development teams with a catalog of curated AI models that they can easily deploy and integrate into their applications without needing deep AI expertise. The platform must be secure, reliable, and scalable.
Which software components within the HPE Private Cloud AI stack are essential to building this platform? (Select all that apply.)
- A. The HPE Intelligent Configurator
- B. A collection of pre-trained community and custom-built AI models
- C. HPE AI Essentials for a unified data science and MLOps plane
- D. NVIDIAAI Enterprise for enterprise-grade support and security
- E. NVIDIA NIM (NVIDIA Inference Microservices)
Correct Answer: B,C,D,E 🗳️
An architect is selecting the appropriate HPE Private Cloud AI configuration for a customer. The customer's primary workload is fine-tuning a 70B parameter model, a task that is extremely sensitive to compute latency and requires the highest possible performance for multi-node distributed training.
Which specific infrastructure components included in the "Large" configuration of HPE Private Cloud AI are essential for meeting this high-performance training requirement? (Select all that apply.)
- A. NVIDIA SN4700M switches supporting 200GbE RoCE
- B. HPE Aruba Networking CX 6300M switches
- C. NVIDIA NVLink Bridge
- D. NVIDIA H100 NVL GPUs
- E. NVIDIA L40S GPUs
Correct Answer: A,C,D 🗳️
A customer is considering the HPE Private Cloud AI solution. They need to run a moderately sized RAG application for 150 users. They do not have any fine-tuning requirements.
Why would an architect recommend a "Medium" configuration over a "Large" configuration for this customer?
- A. The L40S GPUs in the Medium configuration are more cost-effective and power-efficient for this specific inference-heavy workload.
- B. The Medium configuration is the only one that includes the HPE AI Essentials software.
- C. The Large configuration does not support Retrieval-Augmented Generation (RAG).
- D. The Medium configuration has more storage capacity than the Large configuration.
Correct Answer: A 🗳️
A company has developed a custom fraud detection model. Their data science team wants to deploy this model into production for other applications to use. They want to avoid the complexity of manually configuring the serving environment, optimizing for hardware, and creating a scalable API endpoint.
How does using an NVIDIA Inference Microservice (NIM) within HPE Private Cloud AI simplify this process?
- A. NIM directly connects to the raw data sources to perform data preparation and cleaning.
- B. NIM provisions the underlying Kubernetes cluster and physical servers.
- C. NIM provides a framework that packages the model into an optimized, ready-to-deploy container with a standard API.
- D. NIM automatically fine-tunes the model on new data to improve its accuracy.
Correct Answer: C 🗳️
What is the primary purpose of using RDMA over Converged Ethernet (RoCE) in the AI interconnect fabric of an HPE Private Cloud AI solution?
- A. To partition a single physical network adapter into multiple virtual adapters for different tenants.
- B. To guarantee packet delivery over lossy internet connections using the TCP protocol.
- C. To encrypt data in transit between compute nodes and storage.
- D. To allow direct memory-to-memory data transfers between nodes, bypassing the CPU kernel and reducing latency.
Correct Answer: D 🗳️
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