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Cisco 300-640 Exam Syllabus Topics:

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

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Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions (Q31-Q36):

NEW QUESTION # 31
Which aspect of rapid provisioning supports a scalable workload execution in an AI infrastructure?

Answer: D

Explanation:
Rapid provisioning supports scalable AI workload execution by enabling computational platforms to be launched quickly and consistently as workload demand grows. This allows AI infrastructure to add or prepare compute resources efficiently for training, inference, or data-processing tasks.


NEW QUESTION # 32
A medium-sized breadmaking operation must deploy a fleet of GPU servers that meet these requirements for their flagship application:
- policy managed through cloud-based interface
- low latency between specific pairs of GPUs
- at least 2 GPUs per server
- all GPUs should be same model
- Intel CPU
- well suited for Inferencing
- customer is power conscious
Which server meets the requirements?

Answer: C

Explanation:
The UCS X210c M8 with the X580 PCIe node fits the requirements because it supports cloud- based policy management through Cisco Intersight, uses Intel Xeon processors, supports multiple same-model GPUs, and is well suited for GPU-accelerated inference workloads while allowing modular scale-out as demand grows. Cisco describes the X580p PCIe node as supporting up to four GPUs with X210c/X215c compute nodes for workloads including inference.
Reference:
https://www.cisco.com/c/en/us/products/collateral/servers-unified-computing/ucs-x-series- modular-system/mlperf-inference-ucs-x580p-wp.html
https://www.cisco.com/c/dam/en/us/products/collateral/servers-unified-computing/ucs-x-series- modular-system/x210cm8-specsheet.pdf


NEW QUESTION # 33
A Cisco AI infrastructure requires fast convergence after a spine switch failure. Which routing design principle best supports this objective?

Answer: B

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 # 34
A bank is planning to deploy an AI inference solution at its branch locations. The solution must support workloads that require a balance of compute, memory, and potential GPU acceleration, and it must be suitable for installation by nontechnical onsite resources. The requirements are:
- high availability of the chassis management plane.
- support for up to 768 GB of memory for in-memory model storage and
processing
- remote server launch requiring no on-site IT staff
- use of Cisco Intersight for SaaS-based infrastructure lifecycle
management
Which solution meets the requirements?

Answer: A


NEW QUESTION # 35
Which function is provided through natural language processing?

Answer: C

Explanation:
Natural language processing enables systems to interpret, process, and transform human language from spoken or written inputs into structured data that applications can analyze, search, classify, or use for automation.


NEW QUESTION # 36
......

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