300-640 Official Practice Test | High Pass-Rate 300-640: Implementing Cisco Data Center AI Infrastructure 100% Pass

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Cisco 300-640 Exam Syllabus Topics:

Section	Weight	Objectives
AI Infrastructure Components and Architecture	30%	- Evaluate compute requirements: CPU, GPU, NVLink, virtualization, containerization, scalability - Evaluate network requirements for AI workloads: bandwidth, latency, congestion control, RoCEv2, QoS - Evaluate hybrid and multi-cloud AI integration - Evaluate storage requirements: capacity, performance, data pipelines, distributed architectures - Evaluate power, cooling, and efficiency requirements
AI Infrastructure Deployment and Data Management	30%	- Deploy and manage AI infrastructure with orchestration tools - Integrate AI frameworks and applications with Cisco infrastructure - Implement data management and lifecycle for AI workloads - Configure compute and storage using Cisco UCS: profiles, policies, Intersight - Configure high-performance networks for AI: Cisco Nexus, NDFC, lossless fabrics
AI Infrastructure Operations and Troubleshooting	20%	- Monitor infrastructure: Nexus Dashboard, Intersight, telemetry, alerts - Implement performance benchmarking and validation - Manage health, logs, and events - Optimize performance, security, and reliability - Troubleshoot network, compute, storage, and orchestration issues
AI Infrastructure Fundamentals	20%	- Describe types of AI infrastructure: on-premises, cloud, hybrid, edge - Describe core components of AI infrastructure: network, compute, storage, orchestration, monitoring - Explain Cisco AI infrastructure solutions and portfolio - Describe AI use cases in data center environments - Describe AI and machine learning concepts

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Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions (Q74-Q79):

NEW QUESTION # 74
A Cisco AI infrastructure requires fast convergence after a spine switch failure. Which routing design principle best supports this objective?

A. Equal-cost multipath routing
B. Single-path forwarding
C. Static route redistribution
D. Layer 2 loop dependency

Answer: A

Explanation:
ECMP provides multiple active forwarding paths and enables rapid failover when a path becomes unavailable. AI environments benefit from resilient high-bandwidth forwarding. Static redistribution slows operational flexibility, while single-path forwarding and Layer 2 dependency reduce scalability and convergence efficiency.

NEW QUESTION # 75
Which set of statements describes Quantized Congestion Notification?

A. Explicit Congestion Notification reacts first to mitigate congestion, and Priority Flow Control acts as a fail-safe to prevent traffic drops if Explicit Congestion Notification is insufficient.
A congestion notification packet sent toward the source by a host in response to receiving Explicit Congestion Notification with congestion experienced bits set.
B. Explicit Congestion Notification reacts first to mitigate congestion, and Priority Flow Control acts as a fail-safe to prevent traffic drops if Explicit Congestion Notification is insufficient.
A congestion notification packet sent toward the source by hosts and the network switch in response to receiving Explicit Congestion Notification with congestion experienced bits set.
C. Priority Flow Control reacts first to mitigate congestion, and Explicit Congestion Notification acts as a fail-safe to prevent traffic drops if Priority Flow Control is insufficient.
A congestion notification packet sent toward the source by hosts and the network switch in response to receiving Explicit Congestion Notification with congestion experienced bits set.
D. Priority Flow Control reacts first to mitigate congestion, and Explicit Congestion Notification acts as a fail-safe to prevent traffic drops if Priority Flow Control is insufficient.
A congestion notification packet sent toward the source by a network switch in response to receiving Explicit Congestion Notification with congestion experienced bits set.

Answer: A

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 # 76
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?

A. BGP EVPN route count per leaf switch
B. PFC pause frame transmission rate per interface
C. spanning tree topology change notifications
D. VXLAN tunnel packet encapsulation rate

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 # 77
A data center team enables jumbo frames in a Cisco AI cluster. What is the primary benefit of increasing the MTU for east-west GPU traffic?

A. Elimination of packet buffering
B. Increased encryption overhead
C. Reduced Layer 3 convergence time
D. Lower CPU utilization and fewer frames

Answer: D

Explanation:
Jumbo frames reduce the number of packets needed to transmit large AI datasets, decreasing CPU interrupts and protocol overhead. This improves throughput and efficiency for GPU communication. Larger MTUs do not directly affect convergence or eliminate buffering, and they typically reduce rather than increase processing overhead.

NEW QUESTION # 78
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?

A. UCS C845A M8 with AMD MI210 GPU
B. UCS C240 M8 with NVIDIA L40 GPU
C. UCS C220 M8 with NVIDIA A16 GPU
D. UCS C885A M8 with NVIDIA H200 GPU

Answer: D

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 # 79
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