HP HPE2-B08模試エンジン、HPE2-B08資格参考書

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HP HPE2-B08 Exam Syllabus Topics:

Section	Objectives
HPE GreenLake for AI Solutions	- GreenLake architecture and services - Consumption-based IT model for AI
Deployment and Operations	- Monitoring and optimization - Deployment models for AI solutions - Lifecycle management of AI infrastructure
HPE Private Cloud AI Fundamentals	- Core AI workload characteristics - Overview of private cloud AI concepts
AI Infrastructure Design	- Storage and data pipeline design - Networking for AI workloads - Compute and GPU considerations
Security in Private Cloud AI	- Identity and access management - Workload and data protection
Data Management and Governance	- Data lifecycle management - Data governance and compliance

>> HP HPE2-B08模試エンジン <<

プロフェッショナルHPE2-B08模試エンジン & 資格試験におけるリーダーオファー & 信頼できるHPE2-B08資格参考書

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HPE Private Cloud AI Solutions 認定 HPE2-B08 試験問題 (Q16-Q21):

質問 # 16
A customer needs a solution for their deployed customer service chatbot. They state: "We don't need to change the model itself, but we need the chatbot to answer questions using our product documentation, which is updated every night. The answers must be fast and based on the latest documents." How would you categorize this workload?

A. A model development and experimentation workload.
B. A classic AI inferencing workload.
C. A large-scale model training workload.
D. A RAG (Retrieval-Augmented Generation) inferencing workload.

正解：D

質問 # 17
An architect is explaining the HPE Private Cloud AI configurations to a customer.
What is the key differentiator between the "Large" configuration and the "Small" and "Medium" configurations in terms of hardware?

A. The Large configuration uses NVIDIA H100 NVL GPUs, while the Small and Medium configurations use NVIDIA L40S GPUs.
B. The Large configuration is the only one that includes HPE GreenLake for File Storage.
C. The Large configuration uses AMD processors, while the Small and Medium configurations use Intel processors.
D. The Large configuration is deployed in a single rack, while the Small and Medium require two racks.

正解：A

質問 # 18
A customer needs a solution for AI inferencing at the edge for a computer vision application. They have determined a Small configuration of HPE Private Cloud AI is sufficient. The solution also requires several value-added services, including an AI transformation workshop and a data design service.
How should an architect attach these services in One Config Advanced (OCA)?

A. The services can be selected and added to the configuration as optional line items within OCA.
B. The services must be quoted separately from the hardware and software configuration.
C. The architect must open a support ticket with HPE to have the services added to the quote.
D. The services are automatically included in the Smart Template and require no action.

正解：A

質問 # 19
A hospital is developing an AI application to automatically detect specific anomalies in medical images like X-rays and MRIs. The task requires the model to learn and identify complex spatial patterns, such as the shapes and textures of tissues and potential tumors.
Which type of neural network architecture is specifically designed for and best suited to this kind of image analysis task? (Select all that apply.)

A. A transformer-based model designed for Natural Language Processing (NLP)
B. A Convolutional Neural Network (CNN)
C. A model architecture that includes pooling layers to reduce spatial dimensions
D. A model architecture that includes convolutional layers for feature extraction
E. A basic, fully connected Artificial Neural Network (ANN)

正解：B、C、D

質問 # 20
An architect is designing a high-performance computing environment for a customer with two distinct, demanding workloads:
1. A large-scale, multi-node deep learning model that requires the fastest possible server-to-server communication.
2. A data-intensive analytics workload that requires the fastest possible data ingestion from an HPE GreenLake for File Storage array.
Which combination of technologies from the HPE Private Cloud AI solution should the architect select to optimize both workloads? (Select all that apply.)

A. GPUDirect Storage (GDS) to enable a direct data path between storage and GPUs for the analytics workload.
B. InfiniBand for the server-to-server fabric and Fibre Channel for the storage fabric.
C. NVLink for intra-server GPU communication and RoCE for the server-to-server and server-to-storage fabric.
D. A flat TCP/IP network for simplicity, relying on the speed of the 200GbE adapters.
E. Multi-Instance GPU (MIG) to partition GPUs for each workload.

正解：A、C

質問 # 21
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