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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Infrastructure Deployment | 25% | - Storage Configuration for AI - Cabling and Connectivity - GPU Server Configuration - Hardware Installation and Configuration - Network Switch Configuration |
| Topic 2: AI Infrastructure Operations | 20% | - Monitoring and Management Tools - Capacity Planning - Troubleshooting Common Issues - Performance Optimization |
| Topic 3: Cisco AI Infrastructure Architecture | 30% | - Storage Architecture Considerations - Hyperconverged Infrastructure for AI - Network Architecture for AI Workloads - Cisco UCS AI Infrastructure Solutions |
| Topic 4: AI Infrastructure Security and Compliance | 10% | - Compliance Considerations - Security Best Practices - Access Control and Authentication |
| Topic 5: AI Infrastructure Fundamentals | 15% | - AI Infrastructure Requirements - AI Workload Characteristics - AI Ecosystem Components - GPU Architecture and Types |
私たちの世界は絶え間ない変化と進化の状態にあります。時間のペースを保ち、絶えず変化し、自分自身に挑戦したい場合は、1種類の300-640証明書テストに参加して、実用的な能力を向上させ、知識の量を増やしてください。 300-640学習実践ガイドを購入すると、テストにスムーズに合格できます。 300-640試験資料は、上級専門家による厳密な分析と検証を経ており、いつでも新しいリソースを補足する準備ができています。
質問 # 39
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?
正解：C
解説：
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.
質問 # 40
A solutions architect must implement a monitoring strategy for a new AI/ML data center infrastructure built on Cisco UCS X-Series servers with NVIDIA H100 GPUs, managed by Cisco Intersight. The main objectives are to gain deep visibility into GPU performance, identify resource bottlenecks for AI training workloads, and ensure the overall health and efficiency of the compute environment. Which Cisco Intersight capability is most critical for effectively monitoring this AI- centric infrastructure?
正解：B
解説：
Cisco Intersight provides health and performance monitoring for UCS servers, including real-time telemetry and GPU-specific metrics for NVIDIA GPUs. This visibility is essential for identifying bottlenecks, tracking AI training workload behavior, and maintaining the health and efficiency of GPU-accelerated UCS X-Series infrastructure.
質問 # 41
A Cisco AI cluster requires segmentation between multiple research teams sharing the same physical infrastructure. Which solution provides scalable tenant isolation?
正解：C
解説：
VXLAN overlays provide scalable multi-tenant segmentation using large VNI spaces beyond traditional VLAN limitations. AI infrastructures often support many isolated environments simultaneously. VLAN-only designs have scalability constraints, while WAN topologies and NAT do not provide modern data center tenant segmentation.
質問 # 42
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?
正解：D
解説：
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.
質問 # 43
A global enterprise is deploying a new AI-driven analytics platform that requires high-performance GPU acceleration, large memory capacity, and robust virtualization support. The current compute environment must co-exist with the newly purposed GPU-enabled workload. This environment will continue to grow, so the customer wants to scale out the resources as needed. Which Cisco product meets the requirements?
正解：B
解説：
Cisco UCS X-Series is designed for scalable, modular compute environments that support GPU- enabled workloads, high memory capacity, virtualization, and coexistence with existing infrastructure. Its modular architecture allows the enterprise to expand resources as AI workload demands grow.
質問 # 44
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300-640試験の急流を学び、300-640試験を準備するのに20〜30時間しかかかりません。多くの人々、特に現職のスタッフは仕事、学習、家族生活、その他の重要な事柄で忙しく、300-640試験を学習して準備する時間とエネルギーがほとんどありません。しかし、300-640テストトレントを購入すれば、最も重要なことにメインエネルギーを投資し、試験を学習して準備するために毎日1〜2時間を割くことができます。 300-640試験の質問と回答は実際の試験に基づいており、Implementing Cisco Data Center AI Infrastructure受験者の一般的な傾向に準拠しています。
300-640テキスト: https://www.mogiexam.com/300-640-exam.html