HPE2-B08 무료 덤프문제 온라인 액세스

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.Multi-Instance GPU (MIG) to partition GPUs for each workload.
• B.GPUDirect Storage (GDS) to enable a direct data path between storage and GPUs for the analytics workload.
• 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.InfiniBand for the server-to-server fabric and Fibre Channel for the storage fabric.

An architect is using the HPE One Config Advanced (OCA) Smart Template for "HPE Private Cloud AI
- Small - Standard".
What is the worker node configuration they should expect to see in the generated Bill of Materials (BOM)?

• A.3x HPE ProLiant DL325 Gen11 servers for management
• B.4x HPE ProLiant DL380a Gen11 servers with a total of 16x NVIDIA H100 NVL GPUs
• C.2x HPE ProLiant DL380a Gen11 servers with a total of 8x NVIDIA L40S GPUs
• D.1x HPE ProLiant DL380a Gen11 server with 4x NVIDIA L40S GPUs

A customer at the 'Early AI User' maturity stage wants to begin using generative AI. Their primary concern is the complexity of deploying and managing the AI software stack. They are looking for a solution that accelerates their journey by providing a pre-integrated, enterprise-supported software platform for both development and deployment.
How do the software components of HPE Private Cloud AI address this customer's main challenge?
(Select all that apply.)
```
Customer Profile:
- Maturity: Early AI User
- Main Challenge: Complexity of AI software stack
- Goal: Accelerate adoption of generative AI
```

• A.The solution requires the customer to manually integrate all software components, which promotes learning.
• B.NVIDIA NIMs drastically simplify the deployment of pre-trained models into production-ready microservices.
• C.NVIDIAAI Enterprise provides enterprise-grade support, security, and API stability for the entire AI software stack.
• D.HPE AI Essentials provides a unified, self-service platform with curated open-source tools, eliminating integration complexity.
• E.The software stack is limited to only HPE-developed tools to ensure a single point of contact.

An enterprise wants to deploy pre-trained foundation models from various sources for multiple business units. A key requirement is to simplify and standardize the deployment process, regardless of the model's origin. They want a solution that packages models into scalable, optimized, and easy-to-use microservices with a standard API.
Which component of the NVIDIA AI Enterprise software suite directly addresses this need?

• A.NVIDIA TAO Toolkit
• B.NVIDIA NeMo
• C.NVIDIA NIM (NVIDIA Inference Microservices)
• D.NVIDIA Triton Inference Server

A sales professional is preparing a quote for an HPE Private Cloud AI solution in OCA and needs to ensure the correct support services are attached.
What is the default level of support included with all components when using the "Flexible services" option in the Smart Template?

• A.HPE Tech Care, Basic
• B.HPE Tech Care, Critical
• C.HPE Tech Care, Essential
• D.HPE Complete Care Service