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| Section | Weight | Objectives |
|---|---|---|
| AI Infrastructure Fundamentals | 15% | - AI Infrastructure Requirements - GPU Architecture and Types - AI Workload Characteristics - AI Ecosystem Components |
| Cisco AI Infrastructure Architecture | 30% | - Hyperconverged Infrastructure for AI - Cisco UCS AI Infrastructure Solutions - Storage Architecture Considerations - Network Architecture for AI Workloads |
| AI Infrastructure Deployment | 25% | - Hardware Installation and Configuration - Cabling and Connectivity - Network Switch Configuration - Storage Configuration for AI - GPU Server Configuration |
| AI Infrastructure Security and Compliance | 10% | - Compliance Considerations - Access Control and Authentication - Security Best Practices |
| AI Infrastructure Operations | 20% | - Troubleshooting Common Issues - Performance Optimization - Capacity Planning - Monitoring and Management Tools |
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NEW QUESTION # 49
A global enterprise is deploying a new AI-driven analytics platform that requires high-performance GPU acceleration, large memory capacity, and robust virtualization support. The current compute environment must co-exist with the newly purposed GPU-enabled workload. This environment will continue to grow, so the customer wants to scale out the resources as needed. Which Cisco product meets the requirements?
Answer: D
Explanation:
Cisco UCS X-Series is designed for scalable, modular compute environments that support GPU- enabled workloads, high memory capacity, virtualization, and coexistence with existing infrastructure. Its modular architecture allows the enterprise to expand resources as AI workload demands grow.
NEW QUESTION # 50
When considering a rail-only network design, when would adding spine switches make sense?
Answer: B
Explanation:
In a rail-only design, each scalable unit provides optimized east-west GPU communication within that unit. Spine switches are added when the design must scale beyond a single scalable unit and support traffic between multiple scalable units while preserving predictable performance for larger AI training environments.
NEW QUESTION # 51
Which components are part of the HyperFabric AI solution?
Answer: B
Explanation:
HyperFabric AI combines Cisco UCS servers with NVIDIA GPUs, Cisco Nexus 6000 Series switches, optional VAST Data storage, and cloud-managed networking to provide an integrated AI infrastructure solution for training and inference workloads.
NEW QUESTION # 52
A server administrator must monitor the performance and utilization of GPUs in Cisco UCS servers running AI workloads. Which two metrics must be used in Cisco Intersight to accomplish these goals? (Choose two.)
Answer: A,B
Explanation:
Cisco Intersight provides GPU-focused telemetry for UCS servers, including utilization and performance metrics. These measurements allow the administrator to monitor how heavily the GPUs are being used and whether the AI workload is receiving the expected GPU performance.
NEW QUESTION # 53
A data center facility experienced a power outage, and the UCS X-Series servers did not restart automatically when power is restored. The configuration must be updated to prioritize these servers to boot as soon as possible to resume their work. Which set of power policy configurations must be used to meet these requirements?
Answer: C
Explanation:
The servers must be configured to power back on automatically after power is restored, so the restore behavior should be set to always power on. Setting the power priority to high ensures these UCS X-Series servers receive priority during power recovery, allowing them to resume workloads as quickly as possible.
NEW QUESTION # 54
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