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Cisco 300-640 Exam Syllabus Topics:

SectionObjectives
Security and Governance in AI Data Centers- Infrastructure security
  • 1. Secure access to AI workloads
    • 2. Network segmentation and policy enforcement
      Compute and Storage for AI Infrastructure- Storage systems
      • 1. Distributed storage concepts
        • 2. High-throughput storage for AI training data
          - Compute architecture
          • 1. GPU-based compute nodes
            • 2. HPC-style scaling considerations
              Data Center AI Infrastructure Fundamentals- AI/ML workload requirements in data centers
              • 1. Data pipeline and workload characteristics
                • 2. Compute, GPU, and acceleration concepts
                  Data Center Networking for AI Workloads- High-performance fabric design
                  • 1. Low-latency switching and routing considerations
                    • 2. Leaf-spine architecture in AI environments
                      - Cisco Data Center networking technologies
                      • 1. Cisco ACI integration concepts
                        • 2. Cisco Nexus platform concepts
                          AI Infrastructure Deployment and Operations- Operations and lifecycle management
                          • 1. Monitoring and observability
                            • 2. Performance tuning and optimization
                              - Deployment models
                              • 1. Hybrid AI infrastructure integration
                                • 2. On-premises AI clusters

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                                  Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions (Q37-Q42):

                                  NEW QUESTION # 37
                                  A server administrator must monitor the performance and utilization of GPUs in Cisco UCS servers running AI workloads. Which two metrics must be used in Cisco Intersight to accomplish these goals? (Choose two.)

                                  Answer: C,D

                                  Explanation:
                                  Cisco Intersight provides GPU-focused telemetry for UCS servers, including utilization and performance metrics. These measurements allow the administrator to monitor how heavily the GPUs are being used and whether the AI workload is receiving the expected GPU performance.


                                  NEW QUESTION # 38
                                  An engineer is deploying a Cisco AI POD environment to support large-scale AI workloads. The solution must provide a software-defined storage platform with a Disaggregated Shared- Everything architecture, allow compute nodes to run on Cisco UCS C225 M8 servers managed through Cisco Intersight, and deliver exabyte-scale, all-flash performance with integrated high- speed RDMA and GPU Direct Storage capabilities. Which solution meets the requirements?

                                  Answer: A

                                  Explanation:
                                  VAST Data Universal Storage provides a software-defined, disaggregated shared-everything storage architecture designed for AI-scale workloads. It supports Cisco UCS-based deployments managed through Intersight and delivers high-performance all-flash storage with RDMA and GPU Direct Storage capabilities for large-scale AI training, fine-tuning, and inference environments.


                                  NEW QUESTION # 39
                                  How does RAG enhance the capabilities of LLMs?

                                  Answer: D

                                  Explanation:
                                  RAG enhances LLMs by retrieving relevant external or proprietary information at generation time and using that context to produce more accurate, current, and domain-specific responses without changing the model's core parameters.


                                  NEW QUESTION # 40
                                  An end customer plans to deploy an AI fabric in a new data center. Their engineers are more familiar with CLI-based networks and require the capability to automate standardized configuration templates and monitor flows for the fabric. Which data center automation tool meets the requirements?

                                  Answer: B

                                  Explanation:
                                  Nexus Dashboard is the Cisco data center automation and operations platform used with Nexus fabrics. It supports standardized fabric configuration through automation templates and provides visibility features such as flow monitoring, making it the appropriate tool for engineers who need CLI-oriented data center fabric operations with automation and telemetry.


                                  NEW QUESTION # 41
                                  A server administrator must monitor the performance and utilization of GPUs in Cisco UCS servers running AI workloads. Which two metrics must be used in Cisco Intersight to accomplish these goals? (Choose two.)

                                  Answer: B,E

                                  Explanation:
                                  Cisco Intersight performance monitoring uses resource utilization metrics to identify bottlenecks in AI workloads. Active CPU utilization shows whether host processing is limiting workload execution, while GPU memory utilization shows how effectively GPU memory is being consumed during model processing and training or inference tasks.


                                  NEW QUESTION # 42
                                  ......

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