300-640 Certification Test Answers - Exam 300-640 Outline

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Cisco 300-640 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Cisco AI Infrastructure Architecture	30%	- Cisco UCS AI Infrastructure Solutions - Hyperconverged Infrastructure for AI - Storage Architecture Considerations - Network Architecture for AI Workloads
Topic 2: AI Infrastructure Fundamentals	15%	- AI Infrastructure Requirements - AI Ecosystem Components - AI Workload Characteristics - GPU Architecture and Types
Topic 3: AI Infrastructure Deployment	25%	- Cabling and Connectivity - Storage Configuration for AI - GPU Server Configuration - Hardware Installation and Configuration - Network Switch Configuration
Topic 4: AI Infrastructure Security and Compliance	10%	- Access Control and Authentication - Security Best Practices - Compliance Considerations
Topic 5: AI Infrastructure Operations	20%	- Troubleshooting Common Issues - Capacity Planning - Performance Optimization - Monitoring and Management Tools

>> 300-640 Certification Test Answers <<

Web-Based Cisco 300-640 Practice Test

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Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions (Q65-Q70):

NEW QUESTION # 65
Which set of statements describes Quantized Congestion Notification?

A. Priority Flow Control reacts first to mitigate congestion, and Explicit Congestion Notification acts as a fail-safe to prevent traffic drops if Priority Flow Control is insufficient.
A congestion notification packet sent toward the source by a network switch in response to receiving Explicit Congestion Notification with congestion experienced bits set.
B. Priority Flow Control reacts first to mitigate congestion, and Explicit Congestion Notification acts as a fail-safe to prevent traffic drops if Priority Flow Control is insufficient.
A congestion notification packet sent toward the source by hosts and the network switch in response to receiving Explicit Congestion Notification with congestion experienced bits set.
C. Explicit Congestion Notification reacts first to mitigate congestion, and Priority Flow Control acts as a fail-safe to prevent traffic drops if Explicit Congestion Notification is insufficient.
A congestion notification packet sent toward the source by a host in response to receiving Explicit Congestion Notification with congestion experienced bits set.
D. Explicit Congestion Notification reacts first to mitigate congestion, and Priority Flow Control acts as a fail-safe to prevent traffic drops if Explicit Congestion Notification is insufficient.
A congestion notification packet sent toward the source by hosts and the network switch in response to receiving Explicit Congestion Notification with congestion experienced bits set.

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 # 66
An engineer notices excessive broadcast traffic inside a legacy AI server VLAN. Which technology should be implemented to reduce flooding and improve scalability?

A. GRE tunneling
B. PAT
C. RIP
D. VXLAN EVPN

Answer: D

Explanation:
VXLAN EVPN reduces unknown unicast and broadcast flooding by using control-plane learning with BGP EVPN. This improves scalability in modern AI data centers. RIP is outdated for large- scale fabrics, while PAT and GRE tunneling do not address broadcast domain limitations.

NEW QUESTION # 67
Which network design approach should be used to build a high-performance, nonblocking AI/ML data center fabric that supports 64 fully equipped UCS C885A nodes and provides the lowest possible latency and lossless Ethernet?

A. traditional three-tier
B. rail optimized
C. flat Layer 2
D. leaf-spine

Answer: B

Explanation:
A rail-optimized design is used for large AI/ML clusters because it aligns GPU-to-GPU communication paths across the fabric, minimizes latency, and supports high-throughput lossless Ethernet for distributed training workloads.

NEW QUESTION # 68
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?

A. Cisco UCS C885A M8
B. Cisco UCS S3260
C. Cisco UCS X-Direct
D. Cisco UCSXE Unified Edge

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 # 69
A financial company plans to deploy an AI training and inference infrastructure to support its customers. The team must use a solution that provides 96 GPUs, aligns with NVIDIA-compliant reference architectures, and enables cloud-based management of the entire on-premises network environment. Which Cisco solution meets the requirements?

A. Cisco Nexus Dashboard deployed in AWS or Azure with Nexus 9000 switches and AI servers on premises
B. Cisco Intersight AI fabric with Nexus 9000 switches and AI servers on premises
C. Cisco HyperFabric AI Medium AI Cluster with Cisco 6000 switches and AI servers on premises
D. Cisco HyperFabric AI Small AI Cluster with Cisco 6000 switches and AI servers on premises

Answer: D

Explanation:
Cisco HyperFabric AI Small AI Cluster matches the 96-GPU requirement because the validated HyperFabric reference architecture uses 12 Cisco UCS C885A M8 servers with NVIDIA HGX for a total of 96 GPUs. Cisco Nexus HyperFabric is also cloud-managed and compliant with NVIDIA Enterprise Reference Architecture, enabling centralized management of the on-premises AI network, GPU servers, and storage.

NEW QUESTION # 70
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