Cisco 300-640 Exam Dumps - Actual Questions Answers

Cisco Intersight's automated OS installation workflow requires the operating-system installation media to be available through the Software Repository and an appropriate OS configuration source to supply unattended-install parameters. Cisco's UCS X-Series installation workflow first adds an OS image link to the Software Repository and subsequently selects an OS configuration file during the installation wizard.

The configuration file contains or exposes variables needed for unattended deployment, such as hostname, IP addressing, gateway, DNS configuration, credentials, and other operating-system installation parameters. Cisco also supports validated configuration templates for supported operating systems, depending on the deployment mode and OS version.

A firmware policy is not an OS-installation prerequisite; firmware lifecycle configuration is separate from installation of the guest operating system. A virtual KVM policy is likewise unnecessary for an unattended Cisco Mode installation.

A Server Configuration Utility can be relevant to certain Intersight installation workflows and older/standalone platform procedures, but the question specifically asks for the Cisco Mode prerequisite pair represented by the available choices. The combination of the OS image and operating-system configuration file is therefore the intended answer.

Study Guide Reference: AI Infrastructure Deployment and Data Management — Cisco Intersight automated provisioning, Software Repository, and operating-system deployment.

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Cisco Nexus 9000 integration with NVIDIA adaptive-routing capabilities requires the Nexus switch to enable the Spectrum-X hardware profile . Cisco's current NX-OS configuration guide explicitly specifies the global configuration command hardware profile spectrum-x to enable NVIDIA Spectrum-X adaptive routing. When a Nexus switch peers with a supported NVIDIA NIC, this capability allows the NIC to handle packet reordering created by granular techniques such as per-packet Dynamic Load Balancing.

This is particularly important for AI training because large synchronized RDMA flows can create uneven utilization under conventional hash-based ECMP. Cisco explains that per-packet DLB can spray packets over multiple paths and that NVIDIA adaptive routing/direct data placement enables the receiver to correctly handle packets that arrive out of order, improving utilization and collective-operation performance.

Option A is not the documented NX-OS configuration syntax. Option B is not the Cisco-prescribed Nexus integration command. Option D may be relevant to traffic classification in other designs but does not activate Spectrum-X adaptive-routing interoperability.

Therefore, the Cisco-documented configuration is C. This differs from the supplied file's marked answer B.

Study Guide Reference: 3.0 AI Infrastructure Deployment and Data Management — 3.1.d Load distribution.

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NVIDIA NVLink is a high-bandwidth interconnect technology designed primarily to accelerate communication between GPUs. Within systems such as the Cisco UCS C885A M8 equipped with NVIDIA HGX H100 or H200 GPUs, NVLink creates a high-speed GPU interconnect that allows accelerator devices to exchange data substantially more efficiently than would be possible through conventional host-mediated communication paths.

Cisco specifically documents that the eight NVIDIA H200 SXM GPUs in the C885A M8 are interconnected through high-speed NVLink interconnects . Cisco positions this architecture for demanding workloads such as large language model training, fine-tuning, inference, and RAG, where frequent exchange of tensors, gradients, and intermediate values between GPUs can become a major performance constraint.

Option A concerns remote GPU access and resource virtualization, which require separate virtualization or orchestration technologies. Option B describes platform power and thermal management rather than interconnect functionality. Option C incorrectly characterizes NVLink as a secure external-storage transport; storage connectivity instead uses technologies such as Ethernet/RDMA, NVMe, GPUDirect Storage, or Fibre Channel depending on the architecture.

The defining examination concept is therefore direct, high-bandwidth, low-latency communication among GPUs within an accelerated computing platform.

Study Guide Reference: AI Infrastructure Components and Architecture — GPU architecture, GPU interconnects, compute performance, latency, and scalability.

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