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Cisco 300-640 Exam Syllabus Topics:

Section	Objectives
Compute and Storage for AI Infrastructure	- Storage systems 1. High-throughput storage for AI training data 2. Distributed storage concepts - Compute architecture 1. GPU-based compute nodes 2. HPC-style scaling considerations
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
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 Nexus platform concepts 2. Cisco ACI integration concepts
Security and Governance in AI Data Centers	- Infrastructure security 1. Secure access to AI workloads 2. Network segmentation and policy enforcement
Data Center AI Infrastructure Fundamentals	- AI/ML workload requirements in data centers 1. Data pipeline and workload characteristics 2. Compute, GPU, and acceleration concepts

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Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions (Q46-Q51):

NEW QUESTION # 46
A network engineer is deploying an AI training fabric using Cisco Nexus switches with RoCEv2 enabled. During testing, packet drops occur when traffic bursts exceed buffer capacity. Which feature should be configured to minimize congestion and improve lossless Ethernet performance for GPU traffic?

A. Priority Flow Control
B. BPDU Guard
C. Storm Control
D. DHCP Snooping

Answer: A

Explanation:
Priority Flow Control (PFC) allows selective pausing of traffic classes during congestion, which is critical for RoCEv2 environments carrying GPU-to-GPU communication. AI workloads are highly sensitive to packet loss and retransmissions. BPDU Guard and DHCP Snooping are security features, while Storm Control only limits broadcast or multicast traffic and does not create lossless behavior for RDMA traffic.

NEW QUESTION # 47
An engineer must configure dynamic load balancing (DLB) on a Cisco Nexus 9000 Series Switch AI fabric using a CLI. Which configuration must be implemented for only the odd-numbered interfaces?

A. Create a QoS policy that enables DLB and apply that policy to the relevant interfaces.
B. Exclude the desired interfaces from DLB with the interface level configuration of no dlb-interface.
C. Under the relevant interface-level configuration, add the keyword dlb-interface.
D. Create a DLB hardware profile and include the list of desired interfaces.

Answer: C

Explanation:
Dynamic load balancing is enabled on the selected Cisco Nexus 9000 interfaces by applying the interface-level dlb-interface command. For this deployment requirement, the command is applied only to the odd-numbered interfaces that participate in the DLB configuration.

NEW QUESTION # 48
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?

A. Implement port-based VLANs for each project with router ACLs controlling storage access at the distribution layer.
B. Use VXLAN with separate VNIs per project and Group Policy Option to control granular access to shared storage.
C. Deploy separate physical networks for each project with dedicated switches and cross-connects to shared storage.
D. Configure QoS-based traffic steering with separate DSCP markings per project and policy-based routing to shared storage.

Answer: B

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 # 49
Server administrators receive reports of power utilization being near capacity across multiple UCS X-Series servers in the data center after a hardware upgrade. The chassis operates with six power supply units in redundant power mode. How can the administrator use additional power without impacting redundancy?

A. Add more power supplies.
B. Enable extended power capacity.
C. Disable extended power capacity.
D. Implement a power capping policy.

Answer: B

Explanation:
Extended power capacity allows a UCS X-Series chassis with six power supplies in redundant mode to make additional power available while still preserving redundancy. This is used when power demand increases after hardware upgrades and the administrator needs more usable power without changing the redundant power configuration.

NEW QUESTION # 50
An engineer is deploying a Cisco AI POD environment to support large-scale AI workloads. The solution must provide a software-defined storage platform with a Disaggregated Shared- Everything architecture, allow compute nodes to run on Cisco UCS C225 M8 servers managed through Cisco Intersight, and deliver exabyte-scale, all-flash performance with integrated high- speed RDMA and GPU Direct Storage capabilities. Which solution meets the requirements?

A. NetApp All-Flash FAS (AFF)
B. Pure Storage FlashBlade
C. Local NVMe SSDs within each GPU server
D. VAST Data Universal Storage

Answer: D

Explanation:
VAST Data Universal Storage provides a software-defined, disaggregated shared-everything storage architecture designed for AI-scale workloads. It supports Cisco UCS-based deployments managed through Intersight and delivers high-performance all-flash storage with RDMA and GPU Direct Storage capabilities for large-scale AI training, fine-tuning, and inference environments.

NEW QUESTION # 51
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