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| Section | Objectives |
|---|---|
| Security and Governance in AI Data Centers | - Infrastructure security
|
| AI Infrastructure Deployment and Operations | - Operations and lifecycle management
|
| Data Center AI Infrastructure Fundamentals | - AI/ML workload requirements in data centers
|
| Data Center Networking for AI Workloads | - High-performance fabric design
|
| Compute and Storage for AI Infrastructure | - Storage systems
|
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NEW QUESTION # 56
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?
Answer: C
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 # 57
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: A
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 # 58
What does workload distribution offer in an AI infrastructure with local and external resources?
Answer: C
Explanation:
Workload distribution in AI infrastructure enables computational tasks to be spread across local and external resources, improving scalability, resource utilization, and execution flexibility across multiple processing locations.
NEW QUESTION # 59
An administrator configures VXLAN EVPN in a Cisco AI data center fabric. The requirement is to provide Layer 2 adjacency across multiple leaf switches while maintaining scalable control-plane learning. Which protocol fulfills this function?
Answer: A
Explanation:
BGP EVPN provides scalable control-plane MAC and IP route advertisement for VXLAN fabrics.
It eliminates excessive flooding associated with traditional Layer 2 networks and supports efficient multi-tenant AI infrastructures. STP only prevents loops, OSPF is a Layer 3 routing protocol, and HSRP provides gateway redundancy rather than overlay endpoint learning.
NEW QUESTION # 60
A company is building a network fabric for an AI training cluster that will train large language models. The cluster includes 256 GPUs distributed across 32 servers. Security requirements mandate isolation between different training projects and allowing shared access to a central storage system. Which approach provides the required security isolation and maintains optimal performance for GPU-to-GPU communication?
Answer: C
Explanation:
VXLAN provides scalable network segmentation by assigning separate VNIs to different training projects, preserving isolation without building separate physical fabrics. Group Policy Option adds policy-based control within the VXLAN overlay, allowing controlled shared access to central storage while maintaining high-performance GPU-to-GPU communication across the AI training fabric.
NEW QUESTION # 61
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