2026 Professional Cisco 300-640: Reliable Implementing Cisco Data Center AI Infrastructure Exam Papers

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Cisco 300-640 Exam Syllabus Topics:

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

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Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions (Q55-Q60):

NEW QUESTION # 55
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: A

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 # 56
A company deploys a Cisco UCS environment to host AI inferencing workloads that demand low latency, high throughput, and efficient resource utilization. Which set of actions must be taken to deploy a high-performance fabric within the Cisco UCS infrastructure?

Answer: A

Explanation:
A dual-fabric design with redundant Cisco Fabric Interconnects provides high availability, bandwidth scale, and resilient server-to-fabric connectivity. Using 100 Gb Ethernet and port- channel uplinks supports the low-latency, high-throughput fabric required for AI inferencing workloads while improving utilization and avoiding single points of failure.


NEW QUESTION # 57
A customer deploys a UCS 885a server in a data center with two power grids. Three of the
3000W power supplies in the server connect to each grid. Due to an external event, one of the grids will be shut down for maintenance. How does the server respond to this event?

Answer: D

Explanation:
With three 3000W power supplies lost from one power grid, the UCS C885A continues operating on the remaining grid but no longer has the full power budget available for maximum GPU operation. The server reduces performance by enforcing power limits, including capping GPU power, so workloads can continue running within the available power capacity.


NEW QUESTION # 58
A Cisco Nexus switch is configured with QoS policies for AI traffic. Which scheduling mechanism guarantees bandwidth for critical traffic classes during congestion?

Answer: A

Explanation:
Weighted scheduling allocates bandwidth according to configured priorities, ensuring critical AI traffic receives adequate forwarding resources during congestion. FIFO provides no prioritization, while MAC filtering and port mirroring are unrelated to congestion management or QoS scheduling.


NEW QUESTION # 59
A company is building a network fabric for an AI training cluster that will train large language models. The cluster includes 256 GPUs distributed across 32 servers. Security requirements mandate isolation between different training projects and allowing shared access to a central storage system. Which approach provides the required security isolation and maintains optimal performance for GPU-to-GPU communication?

Answer: C

Explanation:
VXLAN provides scalable network segmentation by assigning separate VNIs to different training projects, preserving isolation without building separate physical fabrics. Group Policy Option adds policy-based control within the VXLAN overlay, allowing controlled shared access to central storage while maintaining high-performance GPU-to-GPU communication across the AI training fabric.


NEW QUESTION # 60
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