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| Section | Weight | Objectives |
|---|---|---|
| AI Infrastructure Fundamentals | 15% | - AI Workload Characteristics - AI Ecosystem Components - GPU Architecture and Types - AI Infrastructure Requirements |
| AI Infrastructure Operations | 20% | - Performance Optimization - Capacity Planning - Troubleshooting Common Issues - Monitoring and Management Tools |
| AI Infrastructure Deployment | 25% | - GPU Server Configuration - Network Switch Configuration - Cabling and Connectivity - Hardware Installation and Configuration - Storage Configuration for AI |
| Cisco AI Infrastructure Architecture | 30% | - Storage Architecture Considerations - Hyperconverged Infrastructure for AI - Cisco UCS AI Infrastructure Solutions - Network Architecture for AI Workloads |
| AI Infrastructure Security and Compliance | 10% | - Access Control and Authentication - Security Best Practices - Compliance Considerations |
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NEW QUESTION # 32
A network administrator configures RDMA over Converged Ethernet version 2 (RoCEv2). Which transport protocol does RoCEv2 use at Layer 4?
Answer: D
Explanation:
RoCEv2 encapsulates RDMA traffic over UDP/IP, enabling routable RDMA communication across Layer 3 networks. TCP introduces retransmission and latency overhead unsuitable for high-performance GPU communication. SCTP and ICMP are not used for RoCEv2 transport.
NEW QUESTION # 33
A network architect designs a Cisco AI fabric with spine-leaf topology. What is the primary advantage of this architecture for AI training workloads?
Answer: D
Explanation:
AI workloads generate massive east-west traffic between compute nodes. Spine-leaf designs provide predictable latency and scalable bandwidth because each leaf switch maintains equal- cost paths to all spines. Routing protocols are still required, IP addressing remains necessary, and wireless integration is unrelated to AI fabric performance requirements.
NEW QUESTION # 34
Server administrators receive reports of power utilization being near capacity across multiple UCS X-Series servers in the data center after a hardware upgrade. The chassis operates with six power supply units in redundant power mode. How can the administrator use additional power without impacting redundancy?
Answer: A
Explanation:
Extended power capacity allows a UCS X-Series chassis with six power supplies in redundant mode to make additional power available while still preserving redundancy. This is used when power demand increases after hardware upgrades and the administrator needs more usable power without changing the redundant power configuration.
NEW QUESTION # 35
How does RAG enhance the capabilities of LLMs?
Answer: B
Explanation:
RAG enhances LLMs by retrieving relevant external or proprietary information at generation time and using that context to produce more accurate, current, and domain-specific responses without changing the model's core parameters.
NEW QUESTION # 36
An Intersight administrator plans to deploy new server solutions to several small branch offices across the country. Each location needs at least one chassis. The servers must have redundant CPUs, memory, and 200 Gbps of unified fabric connectivity per compute node. Which hybrid AI compute solution meets the requirements?
Answer: B
Explanation:
Cisco UCS X-Direct is designed for smaller distributed or branch deployments that still need chassis-based UCS X-Series compute capabilities. It supports redundant compute resources and high-speed unified fabric connectivity, including 200 Gbps per compute node, making it the best fit for hybrid AI workloads across multiple branch office locations.
NEW QUESTION # 37
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