Authentic NVIDIA Certification Exam NCP-AIN Questions Answers

Modern AI training (especially with LLMs) requires extremely high-speed, parallel access to large datasets. Adedicated storage fabricseparates data I/O traffic from the training compute path and avoids contention.

FromNVIDIA DGX Infrastructure Reference Architectures:

"Dedicated storage networks eliminate I/O bottlenecks by providing low-latency, high-bandwidth access to distributed storage for large-scale training jobs."

"Parallel access to datasets is key for performance, especially in multi-node, multi-GPU AI clusters."

Security (B)is important, but not the core reason for a storage fabric.

Cost (D)is typicallyincreased, not reduced, with dedicated fabrics.

To perform Flow Analysis with NetQ, the following prerequisites must be met:​

Cumulus Linux Version: NetQ Flow Analysis requires Cumulus Linux 5.x or later.​

Switch Hardware: The feature is supported on Spectrum-2 and later switch models.​

Lifecycle Management (LCM): LCM must be enabled to utilize Flow Analysis capabilities.​

These requirements ensure compatibility and proper functioning of the Flow Analysis feature within NetQ.​

The NVIDIA Spectrum-X Reference Architecture (RA) 1.0.1 is designed for Ethernet AI cloud deployments and includes the SN5600 Spectrum-4 switches and BlueField-3 SuperNICs. This architecture supports adaptive routing and DOCA programmable congestion control (PCC) for lossless RoCE traffic, optimizing performance for AI workloads.

The SN5600 switch offers 64 ports of 800GbE in a dense 2U form factor, providing high throughput and low latency essential for AI applications.