Free PDF Quiz 2026 High Pass-Rate Cisco Exam 300-640 Duration

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| Section | Objectives |
|---|
| Topic 1: 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
|
| Topic 2: AI Infrastructure Deployment and Operations | - Deployment models
- 1. Hybrid AI infrastructure integration
- 2. On-premises AI clusters
- Operations and lifecycle management
- 1. Performance tuning and optimization
- 2. Monitoring and observability
|
| Topic 3: Security and Governance in AI Data Centers | - Infrastructure security
- 1. Network segmentation and policy enforcement
- 2. Secure access to AI workloads
|
| Topic 4: Data Center Networking for AI Workloads | - High-performance fabric design
- 1. Leaf-spine architecture in AI environments
- 2. Low-latency switching and routing considerations
- Cisco Data Center networking technologies
- 1. Cisco Nexus platform concepts
- 2. Cisco ACI integration concepts
|
| Topic 5: 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 (Q39-Q44):
NEW QUESTION # 39
Drag and Drop Question
A network engineer is designing congestion management for an AI cluster using RoCEv2 transport. Based on Cisco best practices, the engineer must understand how ECN and PFC work together to provide lossless Ethernet transport. Drag and drop the congestion management mechanisms from the left onto the corresponding descriptions on the right. Not all options are used.

Answer:
Explanation:

NEW QUESTION # 40
A large-scale retail store manages many compute resources spread across branch offices, which enables AI workloads to be processed on-premises. Each workload and site location requires specific OS installation and configuration. To simplify management, configuration, and deployment of the workloads, a Cisco Intersight feature must be used that enables workload deployment at scale. Which feature must be used to accomplish this functionality?
- A. server management
- B. fleet management
- C. chassis management
- D. domain management
Answer: B
Explanation:
Fleet management in Cisco Intersight is used to manage and deploy workloads consistently across many distributed compute resources. It supports scalable operations such as OS installation, configuration, and policy-driven deployment across multiple servers and locations, making it the correct feature for large distributed AI workload environments.
NEW QUESTION # 41
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 Intersight AI fabric with Nexus 9000 switches and AI servers on premises
- B. Cisco Nexus Dashboard deployed in AWS or Azure with Nexus 9000 switches and AI servers on premises
- C. Cisco HyperFabric AI Small AI Cluster with Cisco 6000 switches and AI servers on premises
- D. Cisco HyperFabric AI Medium AI Cluster with Cisco 6000 switches and AI servers on premises
Answer: C
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 # 42
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. Enable Platinum class and uncheck Allow Packet Drops.
- C. Enable all QoS system classes.
- D. Disable Gold system class.
Answer: B
Explanation:
RoCEv2 traffic must be mapped to a lossless system class. Enabling the Platinum class and clearing Allow Packet Drops configures that class as lossless, preventing packet drops for RoCEv2 traffic and supporting reliable RDMA communication for AI workloads.
NEW QUESTION # 43
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?
- A. Intent-based fabric automation
- B. Manual CLI consistency checks
- C. Local VLAN switching
- D. Distributed ACL processing
Answer: A
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 # 44
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