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Cisco 300-640 Exam Syllabus Topics:

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

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                                  Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions (Q14-Q19):

                                  NEW QUESTION # 14
                                  What is a primary behavior that occurs during the model training stage of the AI lifecycle?

                                  Answer: C

                                  Explanation:
                                  During model training, the model learns from training data by iteratively adjusting its internal weights and biases to reduce prediction error and improve performance against the defined objective function.


                                  NEW QUESTION # 15
                                  To support growing AI workload requirements, a regional medical practice is adding new X9516 X-Fabric module, UCS PCI Mezz cards, and UCS X580p PCIe nodes to their existing X-Series chassis. Which two administrative actions must be taken before the X-Fabric module is added to the chassis? (Choose two.)

                                  Answer: C,E

                                  Explanation:
                                  Before adding the X9516 X-Fabric module, the affected X-Series blades must be powered down because the X-Fabric connectivity path requires hardware installation and cannot be safely introduced while the connected compute nodes are running. The UCS PCI Mezzanine cards must also be installed in the blades so they can physically connect through the X-Fabric module to the X580p PCIe nodes for GPU expansion.


                                  NEW QUESTION # 16
                                  A network team is configuring quality of service (QoS) for RoCEv2 traffic on a VXLAN fabric. The team must ensure that congestion notification packets (CNP) generated by storage targets are never dropped in the network, as these packets are critical for congestion control feedback. How must CNP packets be handled in the QoS configuration to ensure reliable delivery?

                                  Answer: B

                                  Explanation:
                                  CNP packets provide congestion feedback for RoCEv2 traffic and must be delivered reliably so senders can reduce their transmission rate when congestion is detected. Classifying CNP packets into a high-priority queue based on their DSCP marking ensures that these control packets receive preferential treatment and are not dropped during congestion.


                                  NEW QUESTION # 17
                                  A data center is deploying an AI infrastructure for LLM training and model inference. This infrastructure requires high GPU density, low-latency interconnects, and the ability to scale compute resources. When considering the Cisco UCS C885A M8 Rack Server for the deployment, which design aspect is the most critical for achieving optimal performance and scalability in this environment?

                                  Answer: C

                                  Explanation:
                                  For UCS C885A M8 servers running LLM training and inference workloads, the surrounding Nexus fabric design is critical because GPU-dense systems depend on low-latency, high- bandwidth, lossless network connectivity for scale-out performance. Selecting and configuring the correct Nexus fabric minimizes communication delays between compute nodes and enables the AI infrastructure to scale efficiently.


                                  NEW QUESTION # 18
                                  An organization deploys Cisco Nexus switches supporting RoCEv2 traffic. Which QoS behavior is most critical to maintain reliable GPU communication?

                                  Answer: D

                                  Explanation:
                                  RoCEv2 depends on low-latency and near-lossless Ethernet transport to maintain efficient RDMA communication. Packet drops trigger retransmissions and significantly degrade AI training performance. Best-effort forwarding cannot guarantee delivery quality, while fragmentation and randomized path selection do not address the primary RDMA requirement.


                                  NEW QUESTION # 19
                                  ......

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