Pass Guaranteed Quiz 2026 Cisco High Pass-Rate Valid 300-640 Exam Notes

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Cisco 300-640 Exam Syllabus Topics:

SectionWeightObjectives
AI Infrastructure Fundamentals15%- GPU Architecture and Types
- AI Workload Characteristics
- AI Infrastructure Requirements
- AI Ecosystem Components
AI Infrastructure Deployment25%- Cabling and Connectivity
- GPU Server Configuration
- Hardware Installation and Configuration
- Network Switch Configuration
- Storage Configuration for AI
AI Infrastructure Security and Compliance10%- Compliance Considerations
- Security Best Practices
- Access Control and Authentication
AI Infrastructure Operations20%- Troubleshooting Common Issues
- Performance Optimization
- Capacity Planning
- Monitoring and Management Tools
Cisco AI Infrastructure Architecture30%- Hyperconverged Infrastructure for AI
- Network Architecture for AI Workloads
- Cisco UCS AI Infrastructure Solutions
- Storage Architecture Considerations

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Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions (Q21-Q26):

NEW QUESTION # 21
A medium-sized breadmaking operation must deploy a fleet of GPU servers that meet these requirements for their flagship application:
- policy managed through cloud-based interface
- low latency between specific pairs of GPUs
- at least 2 GPUs per server
- all GPUs should be same model
- Intel CPU
- well suited for Inferencing
- customer is power conscious
Which server meets the requirements?

Answer: B

Explanation:
The UCS X210c M8 with the X580 PCIe node fits the requirements because it supports cloud- based policy management through Cisco Intersight, uses Intel Xeon processors, supports multiple same-model GPUs, and is well suited for GPU-accelerated inference workloads while allowing modular scale-out as demand grows. Cisco describes the X580p PCIe node as supporting up to four GPUs with X210c/X215c compute nodes for workloads including inference.
Reference:
https://www.cisco.com/c/en/us/products/collateral/servers-unified-computing/ucs-x-series- modular-system/mlperf-inference-ucs-x580p-wp.html
https://www.cisco.com/c/dam/en/us/products/collateral/servers-unified-computing/ucs-x-series- modular-system/x210cm8-specsheet.pdf


NEW QUESTION # 22
Which set of statements describes Quantized Congestion Notification?

Answer: C

Explanation:
Quantized Congestion Notification relies on Explicit Congestion Notification as the primary congestion signal so the sender can reduce its transmission rate before packet loss occurs.
Priority Flow Control acts as a safety mechanism if congestion becomes severe, and the congestion notification packet is generated by the receiving host when it receives packets marked with congestion-experienced bits.


NEW QUESTION # 23
An engineer deploys BGP EVPN in a Cisco VXLAN fabric. Which route type advertises MAC and IP binding information for endpoints?

Answer: A

Explanation:
EVPN Type 2 routes advertise MAC and optional IP bindings for endpoints, enabling efficient host reachability in VXLAN overlays. Type 5 routes advertise IP prefixes, while Types 1 and 4 handle Ethernet segment and multihoming information. AI fabrics rely heavily on accurate endpoint advertisement for scalability.


NEW QUESTION # 24
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: D

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 # 25
A customer is deploying a new AI fabric with all new NVIDIA GPUs and must verify the performance between the nodes in the network. Which tool must be used to validate the customer benchmarks?

Answer: C

Explanation:
NCCL is the standard tool used to validate GPU-to-GPU communication performance in NVIDIA- based AI fabrics. It measures collective communication behavior between GPU nodes, making it appropriate for benchmarking the AI training network performance.


NEW QUESTION # 26
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