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Cisco 300-640 Exam Syllabus Topics:

SectionWeightObjectives
AI Infrastructure Fundamentals20%- Explain Cisco AI infrastructure solutions and portfolio
- Describe AI use cases in data center environments
- Describe core components of AI infrastructure: network, compute, storage, orchestration, monitoring
- Describe AI and machine learning concepts
- Describe types of AI infrastructure: on-premises, cloud, hybrid, edge
AI Infrastructure Operations and Troubleshooting20%- Optimize performance, security, and reliability
- Manage health, logs, and events
- Troubleshoot network, compute, storage, and orchestration issues
- Monitor infrastructure: Nexus Dashboard, Intersight, telemetry, alerts
- Implement performance benchmarking and validation
AI Infrastructure Deployment and Data Management30%- Configure high-performance networks for AI: Cisco Nexus, NDFC, lossless fabrics
- Implement data management and lifecycle for AI workloads
- Integrate AI frameworks and applications with Cisco infrastructure
- Deploy and manage AI infrastructure with orchestration tools
- Configure compute and storage using Cisco UCS: profiles, policies, Intersight
AI Infrastructure Components and Architecture30%- Evaluate storage requirements: capacity, performance, data pipelines, distributed architectures
- Evaluate network requirements for AI workloads: bandwidth, latency, congestion control, RoCEv2, QoS
- Evaluate power, cooling, and efficiency requirements
- Evaluate hybrid and multi-cloud AI integration
- Evaluate compute requirements: CPU, GPU, NVLink, virtualization, containerization, scalability

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Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions (Q58-Q63):

NEW QUESTION # 58
An administrator configures VXLAN EVPN in a Cisco AI data center fabric. The requirement is to provide Layer 2 adjacency across multiple leaf switches while maintaining scalable control-plane learning. Which protocol fulfills this function?

Answer: A


NEW QUESTION # 59
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: B

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 # 60
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 compute and GPU resources selected must provide direct GPU to GPU access leveraging NVLink technology.
Which set of products meets the requirements?

Answer: C

Explanation:
Cisco UCS C885A M8 with NVIDIA H200 GPUs is designed for high-performance AI workloads that require dense GPU acceleration, large memory capacity, and direct GPU-to-GPU communication through NVIDIA NVLink. This combination supports demanding analytics, training, and inference workloads where high-bandwidth GPU interconnect is required.


NEW QUESTION # 61
Which set of statements describes Quantized Congestion Notification?

Answer: C

Explanation:
Quantized Congestion Notification relies on Explicit Congestion Notification as the primary congestion signal so the sender can reduce its transmission rate before packet loss occurs.
Priority Flow Control acts as a safety mechanism if congestion becomes severe, and the congestion notification packet is generated by the receiving host when it receives packets marked with congestion-experienced bits.


NEW QUESTION # 62
A Cisco UCS C885A M8 server contains a GPU sled configured with six power supply units (PSUs) in an N+2 redundancy configuration. The workload on the GPU sled is currently drawing a load of 4500W. Using Power Save Mode, how many PSUs can be placed into standby mode to improve power efficiency without compromising redundancy?

Answer: D

Explanation:
With six PSUs in an N+2 configuration and a 4500W load, at least two PSUs must remain available to carry the active workload, and two additional PSUs must remain available to preserve redundancy. Therefore, four PSUs must stay active, allowing two PSUs to be placed into standby mode for power efficiency without compromising the N+2 redundancy requirement.


NEW QUESTION # 63
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