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Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions:

1. A bank is planning to deploy an AI inference solution at its branch locations. The solution must support workloads that require a balance of compute, memory, and potential GPU acceleration, and it must be suitable for installation by nontechnical onsite resources. The requirements are:
- high availability of the chassis management plane.
- support for up to 768 GB of memory for in-memory model storage and
processing
- remote server launch requiring no on-site IT staff
- use of Cisco Intersight for SaaS-based infrastructure lifecycle
management
Which solution meets the requirements?

A) Cisco UCS C845A M8 Server
B) Cisco Unified Edge
C) Cisco UCS X-Series Direct
D) Cisco UCS C240 Servers

2. 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?

A) Use VXLAN with separate VNIs per project and Group Policy Option to control granular access to shared storage.
B) Implement port-based VLANs for each project with router ACLs controlling storage access at the distribution layer.
C) Deploy separate physical networks for each project with dedicated switches and cross-connects to shared storage.
D) Configure QoS-based traffic steering with separate DSCP markings per project and policy-based routing to shared storage.

3. 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?

A) VAST Data Universal Storage
B) NetApp All-Flash FAS (AFF)
C) Local NVMe SSDs within each GPU server
D) Pure Storage FlashBlade

4. An engineer must configure dynamic load balancing (DLB) on a Cisco Nexus 9000 Series Switch AI fabric using a CLI. Which configuration must be implemented for only the odd-numbered interfaces?

A) Create a DLB hardware profile and include the list of desired interfaces.
B) Create a QoS policy that enables DLB and apply that policy to the relevant interfaces.
C) Exclude the desired interfaces from DLB with the interface level configuration of no dlb-interface.
D) Under the relevant interface-level configuration, add the keyword dlb-interface.

5. What is a function of NVLink technology within a high-performance AI server or cluster?

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

Solutions: