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Cisco 300-640 Exam Syllabus Topics:

SectionObjectives
Topic 1: Security and Governance in AI Data Centers- Infrastructure security
  • 1. Secure access to AI workloads
    • 2. Network segmentation and policy enforcement
      Topic 2: Data Center AI Infrastructure Fundamentals- AI/ML workload requirements in data centers
      • 1. Compute, GPU, and acceleration concepts
        • 2. Data pipeline and workload characteristics
          Topic 3: 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
                  Topic 4: Compute and Storage for AI Infrastructure- Storage systems
                  • 1. High-throughput storage for AI training data
                    • 2. Distributed storage concepts
                      - Compute architecture
                      • 1. HPC-style scaling considerations
                        • 2. GPU-based compute nodes
                          Topic 5: AI Infrastructure Deployment and Operations- Deployment models
                          • 1. Hybrid AI infrastructure integration
                            • 2. On-premises AI clusters
                              - Operations and lifecycle management
                              • 1. Performance tuning and optimization
                                • 2. Monitoring and observability

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                                  300-640 Trustworthy Source - Sample 300-640 Questions Pdf

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                                  Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions (Q77-Q82):

                                  NEW QUESTION # 77
                                  A network engineer analyzes RoCEv2 traffic flows in an AI training cluster and notices that all RoCEv2 packets have the Don't Fragment bit set in the IP header. Why must RoCEv2 set the DF bit in all packets?

                                  Answer: C

                                  Explanation:
                                  RoCEv2 carries InfiniBand transport semantics over UDP/IP, and IP fragmentation would disrupt the expected packet sequencing and ordering behavior required by RDMA. Setting the Don't Fragment bit prevents intermediate devices from fragmenting RoCEv2 packets, preserving reliable RDMA transport behavior across the AI training fabric.


                                  NEW QUESTION # 78
                                  Drag and Drop Question
                                  An organization is deploying an AI/ML infrastructure with multiple network fabrics, each serving a specific purpose. The network architect must match the network fabric type with its primary function. Drag and drop the network fabric types from the left onto the corresponding descriptions on the right.

                                  Answer:

                                  Explanation:


                                  NEW QUESTION # 79
                                  A network architect designs a Cisco AI fabric with spine-leaf topology. What is the primary advantage of this architecture for AI training workloads?

                                  Answer: A

                                  Explanation:
                                  AI workloads generate massive east-west traffic between compute nodes. Spine-leaf designs provide predictable latency and scalable bandwidth because each leaf switch maintains equal- cost paths to all spines. Routing protocols are still required, IP addressing remains necessary, and wireless integration is unrelated to AI fabric performance requirements.


                                  NEW QUESTION # 80
                                  An organization deploys Cisco Nexus switches supporting RoCEv2 traffic. Which QoS behavior is most critical to maintain reliable GPU communication?

                                  Answer: A

                                  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 # 81
                                  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 current compute environment must co-exist with the newly purposed GPU-enabled workload. This environment will continue to grow, so the customer wants to scale out the resources as needed. Which Cisco product meets the requirements?

                                  Answer: A

                                  Explanation:
                                  Cisco UCS X-Series is designed for scalable, modular compute environments that support GPU- enabled workloads, high memory capacity, virtualization, and coexistence with existing infrastructure. Its modular architecture allows the enterprise to expand resources as AI workload demands grow.


                                  NEW QUESTION # 82
                                  ......

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