Free PDF Quiz Cisco - 300-640–Efficient Reliable Exam Pdf

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Cisco 300-640 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: AI Infrastructure Components and Architecture	30%	- Evaluate hybrid and multi-cloud AI integration - Evaluate power, cooling, and efficiency requirements - Evaluate storage requirements: capacity, performance, data pipelines, distributed architectures - Evaluate network requirements for AI workloads: bandwidth, latency, congestion control, RoCEv2, QoS - Evaluate compute requirements: CPU, GPU, NVLink, virtualization, containerization, scalability
Topic 2: AI Infrastructure Operations and Troubleshooting	20%	- Troubleshoot network, compute, storage, and orchestration issues - Monitor infrastructure: Nexus Dashboard, Intersight, telemetry, alerts - Manage health, logs, and events - Implement performance benchmarking and validation - Optimize performance, security, and reliability
Topic 3: AI Infrastructure Deployment and Data Management	30%	- Deploy and manage AI infrastructure with orchestration tools - Implement data management and lifecycle for AI workloads - 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
Topic 4: AI Infrastructure Fundamentals	20%	- Describe AI use cases in data center environments - Explain Cisco AI infrastructure solutions and portfolio - Describe core components of AI infrastructure: network, compute, storage, orchestration, monitoring - Describe AI and machine learning concepts - Describe types of AI infrastructure: on-premises, cloud, hybrid, edge

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300-640 Cert Exam | Valid 300-640 Test Topics

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Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions (Q70-Q75):

NEW QUESTION # 70
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 hosts and the network switch in response to receiving Explicit Congestion Notification with congestion experienced bits set.
B. 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.
C. 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.
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 a host in response to receiving Explicit Congestion Notification with congestion experienced bits set.

Answer: D

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 # 71
Which aspect of rapid provisioning supports a scalable workload execution in an AI infrastructure?

A. delayed rollout of new network resources
B. limited connectivity within isolated locations
C. distinct management for isolated components
D. efficient launch of computational platforms

Answer: D

Explanation:
Rapid provisioning supports scalable AI workload execution by enabling computational platforms to be launched quickly and consistently as workload demand grows. This allows AI infrastructure to add or prepare compute resources efficiently for training, inference, or data-processing tasks.

NEW QUESTION # 72
Which function is provided through natural language processing?

A. filtration of duplicate entries from transaction records
B. annotation of data transmission protocols for device authorization
C. compression of large configuration files for storage efficiency
D. automated conversion of spoken or written content into structured data

Answer: D

Explanation:
Natural language processing enables systems to interpret, process, and transform human language from spoken or written inputs into structured data that applications can analyze, search, classify, or use for automation.

NEW QUESTION # 73
What is a function of NVLink technology within a high-performance AI server or cluster?

A. to provide a high-speed, low-latency direct interconnect for GPU-to-GPU communication
B. to establish a secure, encrypted channel for data transfer between the AI server and external storage
C. to manage power distribution and thermal regulation across all installed GPU units
D. to enable remote access and virtualization of GPU resources for distributed AI development teams

Answer: A

Explanation:
NVLink provides a high-bandwidth, low-latency direct interconnect between GPUs. In AI servers and clusters, it accelerates GPU-to-GPU communication for training and inference workloads by allowing GPUs to exchange data much faster than through standard PCIe paths.

NEW QUESTION # 74
Drag and Drop Question
An engineer must configure vNIC templates for a UCS X-Series deployment. Drag and drop the policy types from the left onto the corresponding configuration settings on the right. Not all options are used.

Answer:

Explanation:

NEW QUESTION # 75
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