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Cisco 300-640 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Cisco AI Infrastructure Architecture30%- Cisco UCS AI Infrastructure Solutions
- Hyperconverged Infrastructure for AI
- Network Architecture for AI Workloads
- Storage Architecture Considerations
Topic 2: AI Infrastructure Security and Compliance10%- Security Best Practices
- Compliance Considerations
- Access Control and Authentication
Topic 3: AI Infrastructure Deployment25%- Storage Configuration for AI
- Network Switch Configuration
- GPU Server Configuration
- Cabling and Connectivity
- Hardware Installation and Configuration
Topic 4: AI Infrastructure Fundamentals15%- AI Ecosystem Components
- AI Workload Characteristics
- AI Infrastructure Requirements
- GPU Architecture and Types
Topic 5: AI Infrastructure Operations20%- Troubleshooting Common Issues
- Performance Optimization
- Monitoring and Management Tools
- Capacity Planning

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Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions (Q54-Q59):

NEW QUESTION # 54
An engineer deploys an AI fabric on Cisco Nexus 9000 Series Switches connected to Cisco UCS nodes with NVIDIA GPUs. The requirements call for optimal network performance for training workloads. Adaptive routing is enabled on the NICs, and per-packet load balancing is enabled on the switches. Which other configuration must be implemented for this integration to be fully operational?

Answer: C

Explanation:
The NIC must be explicitly configured with the Cisco dynamic load-balancing setting so it recognizes that the connected Cisco Nexus fabric supports adaptive routing. This completes the integration between NIC-side adaptive routing and switch-side per-packet load balancing for optimized AI training traffic.


NEW QUESTION # 55
What is a purpose of Cisco AI PODs?

Answer: B

Explanation:
Cisco AI PODs are designed as integrated, validated full-stack infrastructure solutions that combine compute, networking, storage, and management capabilities to support AI training, fine- tuning, and inferencing workloads with faster deployment and operational consistency.


NEW QUESTION # 56
A corporate network administrator manages a HyperFabric AI environment and wants to receive email notifications about assertions in the fabric. The administrator sets up a recipient email endpoint under the notification endpoints in the controller, but notifications are not received.
Which two configurations cause the issue? (Choose two.)

Answer: A,D

Explanation:
Email endpoints must be verified before they can receive HyperFabric notifications, and the endpoint must also be included with the relevant fabric in the notification policy. Creating the email endpoint alone does not activate assertion notifications for a fabric until both of these notification requirements are completed.


NEW QUESTION # 57
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: C

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 # 58
A network operations team deploys HyperFabric AI and wants to monitor fabric health to proactively identify performance issues. The team must track metrics specifically relevant to AI training workloads. Which metric is most critical for identifying congestion issues that could impact AI training performance in a HyperFabric AI deployment?

Answer: C

Explanation:
PFC pause frame transmission rate is the key congestion indicator for lossless Ethernet fabrics used by AI training workloads. A high or increasing pause frame rate shows that interfaces are experiencing congestion and applying flow control, which can directly affect GPU-to-GPU communication performance in a HyperFabric AI environment.


NEW QUESTION # 59
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