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Cisco 300-640 Exam Syllabus Topics:

SectionObjectives
Topic 1: Security and Governance in AI Data Centers- Infrastructure security
  • 1. Network segmentation and policy enforcement
    • 2. Secure access to AI workloads
      Topic 2: Data Center Networking for AI Workloads- High-performance fabric design
      • 1. Leaf-spine architecture in AI environments
        • 2. Low-latency switching and routing considerations
          - Cisco Data Center networking technologies
          • 1. Cisco Nexus platform concepts
            • 2. Cisco ACI integration concepts
              Topic 3: 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
                      Topic 4: Data Center AI Infrastructure Fundamentals- AI/ML workload requirements in data centers
                      • 1. Data pipeline and workload characteristics
                        • 2. Compute, GPU, and acceleration concepts
                          Topic 5: Compute and Storage for AI Infrastructure- Compute architecture
                          • 1. HPC-style scaling considerations
                            • 2. GPU-based compute nodes
                              - Storage systems
                              • 1. Distributed storage concepts
                                • 2. High-throughput storage for AI training data

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                                  Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions (Q10-Q15):

                                  NEW QUESTION # 10
                                  A nationwide grocery chain has deployed Unified Edge to all its locations. Each store has 10 or more surveillance cameras that write approximately 1 Gb per hour. The surveillance retention policy requires maintaining 2 weeks of recording per camera. Which type of cost-effective centralized storage solution must be evaluated with Unified Edge devices to adhere to this policy?

                                  Answer: A

                                  Explanation:
                                  Unified Edge deployments that need centralized, cost-effective retention for large surveillance data volumes should evaluate IP-based shared storage. It provides scalable network-accessible capacity for multiple edge devices without requiring specialized Fibre Channel or InfiniBand infrastructure, making it appropriate for distributed video retention workloads.


                                  NEW QUESTION # 11
                                  A Cisco AI cluster requires segmentation between multiple research teams sharing the same physical infrastructure. Which solution provides scalable tenant isolation?

                                  Answer: C

                                  Explanation:
                                  VXLAN overlays provide scalable multi-tenant segmentation using large VNI spaces beyond traditional VLAN limitations. AI infrastructures often support many isolated environments simultaneously. VLAN-only designs have scalability constraints, while WAN topologies and NAT do not provide modern data center tenant segmentation.


                                  NEW QUESTION # 12
                                  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: A

                                  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 # 13
                                  An engineer deploys an AI fabric on Cisco Nexus 9000 Series Switches connected to Cisco UCS nodes with NVIDIA GPUs. The requirements call for optimal network performance for training workloads. Adaptive routing is enabled on the NICs, and per-packet load balancing is enabled on the switches. Which other configuration must be implemented for this integration to be fully operational?

                                  Answer: C

                                  Explanation:
                                  The NIC must be explicitly configured with the Cisco dynamic load-balancing setting so it recognizes that the connected Cisco Nexus fabric supports adaptive routing. This completes the integration between NIC-side adaptive routing and switch-side per-packet load balancing for optimized AI training traffic.


                                  NEW QUESTION # 14
                                  A financial company plans to deploy an AI training and inference infrastructure to support its customers. The team must use a solution that provides 96 GPUs, aligns with NVIDIA-compliant reference architectures, and enables cloud-based management of the entire on-premises network environment. Which Cisco solution meets the requirements?

                                  Answer: B

                                  Explanation:
                                  Cisco HyperFabric AI Small AI Cluster matches the 96-GPU requirement because the validated HyperFabric reference architecture uses 12 Cisco UCS C885A M8 servers with NVIDIA HGX for a total of 96 GPUs. Cisco Nexus HyperFabric is also cloud-managed and compliant with NVIDIA Enterprise Reference Architecture, enabling centralized management of the on-premises AI network, GPU servers, and storage.


                                  NEW QUESTION # 15
                                  ......

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