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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. High-throughput storage for AI training data
        • 2. Distributed storage concepts
          - Compute architecture
          • 1. HPC-style scaling considerations
            • 2. GPU-based compute nodes
              AI Infrastructure Deployment and Operations- Operations and lifecycle management
              • 1. Performance tuning and optimization
                • 2. Monitoring and observability
                  - Deployment models
                  • 1. Hybrid AI infrastructure integration
                    • 2. On-premises AI clusters
                      Data Center AI Infrastructure Fundamentals- AI/ML workload requirements in data centers
                      • 1. Compute, GPU, and acceleration concepts
                        • 2. Data pipeline and workload characteristics
                          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

                                  >> Latest 300-640 Test Objectives <<

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                                  Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions (Q47-Q52):

                                  NEW QUESTION # 47
                                  An engineer configures Cisco Nexus Dashboard Fabric Controller for AI infrastructure automation. The company wants centralized policy management and simplified fabric provisioning across multiple pods. Which capability provides this benefit?

                                  Answer: C

                                  Explanation:
                                  Intent-based fabric automation simplifies deployment and policy consistency across large AI infrastructures. Nexus Dashboard Fabric Controller automates provisioning, validation, and operational management. Distributed ACLs and local VLAN switching are operational features but do not centralize orchestration. Manual CLI verification is error-prone and unsuitable for rapidly scaling AI environments.


                                  NEW QUESTION # 48
                                  A network operations team deploys HyperFabric AI and wants to monitor fabric health to proactively identify performance issues. The team must track metrics specifically relevant to AI training workloads. Which metric is most critical for identifying congestion issues that could impact AI training performance in a HyperFabric AI deployment?

                                  Answer: D

                                  Explanation:
                                  PFC pause frame transmission rate is the key congestion indicator for lossless Ethernet fabrics used by AI training workloads. A high or increasing pause frame rate shows that interfaces are experiencing congestion and applying flow control, which can directly affect GPU-to-GPU communication performance in a HyperFabric AI environment.


                                  NEW QUESTION # 49
                                  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: D


                                  NEW QUESTION # 50
                                  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 compute and GPU resources selected must provide direct GPU to GPU access leveraging NVLink technology.
                                  Which set of products meets the requirements?

                                  Answer: B

                                  Explanation:
                                  Cisco UCS C885A M8 with NVIDIA H200 GPUs is designed for high-performance AI workloads that require dense GPU acceleration, large memory capacity, and direct GPU-to-GPU communication through NVIDIA NVLink. This combination supports demanding analytics, training, and inference workloads where high-bandwidth GPU interconnect is required.


                                  NEW QUESTION # 51
                                  An Intersight administrator plans to deploy new server solutions to several small branch offices across the country. Each location needs at least one chassis. The servers must have redundant CPUs, memory, and 200 Gbps of unified fabric connectivity per compute node. Which hybrid AI compute solution meets the requirements?

                                  Answer: C

                                  Explanation:
                                  Cisco UCS X-Direct is designed for smaller distributed or branch deployments that still need chassis-based UCS X-Series compute capabilities. It supports redundant compute resources and high-speed unified fabric connectivity, including 200 Gbps per compute node, making it the best fit for hybrid AI workloads across multiple branch office locations.


                                  NEW QUESTION # 52
                                  ......

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