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Cisco 300-640 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Infrastructure Deployment and Data Management | 30% | - Deploy and manage AI infrastructure with orchestration tools - Integrate AI frameworks and applications with Cisco infrastructure - Configure high-performance networks for AI: Cisco Nexus, NDFC, lossless fabrics - Configure compute and storage using Cisco UCS: profiles, policies, Intersight - Implement data management and lifecycle for AI workloads |
| Topic 2: AI Infrastructure Operations and Troubleshooting | 20% | - Optimize performance, security, and reliability - Manage health, logs, and events - Troubleshoot network, compute, storage, and orchestration issues - Implement performance benchmarking and validation - Monitor infrastructure: Nexus Dashboard, Intersight, telemetry, alerts |
| Topic 3: AI Infrastructure Fundamentals | 20% | - Describe core components of AI infrastructure: network, compute, storage, orchestration, monitoring - Describe AI and machine learning concepts - Explain Cisco AI infrastructure solutions and portfolio - Describe AI use cases in data center environments - Describe types of AI infrastructure: on-premises, cloud, hybrid, edge |
| Topic 4: AI Infrastructure Components and Architecture | 30% | - Evaluate storage requirements: capacity, performance, data pipelines, distributed architectures - Evaluate power, cooling, and efficiency requirements - Evaluate hybrid and multi-cloud AI integration - Evaluate compute requirements: CPU, GPU, NVLink, virtualization, containerization, scalability - Evaluate network requirements for AI workloads: bandwidth, latency, congestion control, RoCEv2, QoS |
Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions:
Which result is provided through image recognition using AI?
- A. scheduling of management tasks during maintenance periods
- B. detection and labeling of visual elements from digital sources
- C. routing of multicast messages across network boundaries
- D. anonymization of audit trails for compliance objectives
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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.
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?
- A. Set the cisco_dlb=1 option in the NIC configuration so the NIC knows it can use adaptive routing.
- B. Include switch configuration "hardware profile spectrum-x" in global configuration mode.
- C. Include matching statements in your QoS policy so the switch knows which incoming packets to load balance.
- D. Add the "adaptive-routing" keyword under the switch load balancing configuration.
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A customer uses Cisco AI Products within Intersight and observes packet drops for RoCEv2 traffic. Which System QoS policy configuration must be deployed to ensure that RoCEv2 traffic is classified as lossless?
- A. Disable Platinum system class.
- B. Disable Gold system class.
- C. Enable all QoS system classes.
- D. Enable Platinum class and uncheck Allow Packet Drops.
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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?
- A. configuring the server with the minimum amount of RAM to reduce initial costs
- B. selecting the appropriate Nexus Fabric and its configuration to minimize latency
- C. implementing a redundant power supply configuration to ensure high availability
- D. using the maximum number of CPU cores to support the virtualization overhead
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