AI's Hidden Bottleneck: The Network


Networking for data centers is adapting to AI. Since GPU clusters are scaling up in size, they require very synchronized communication that can handle huge bandwidth as well as ultra-low latency.

An Aviz Networks podcast features Taylor Allison, NVIDIA Senior Product Marketing Manager, who talks about the trend of networking with the current AI wave. During this conversation Allison touches upon how communication is essential in the AI training process, where GPUs transfer gradients back and forth, making network a crucial part of total workload performance. NVIDIA's Spectrum-X Ethernet, along with their InfiniBand options, has the capabilities to maintain performance in high demanding environments and help manage network related to AI.

The interview further delves into NVIDIA's new Air feature that helps in deploying and configuring services by leveraging a Digital Twin feature, this can ultimately limit risk in planning for day 0 operations.

Day 0 operations are by far the beginning of Day 1 operations, such as rollouts and orchestration that follow, and will eventually scale to Day N with the core focuses being up-times, upgrades, reliability and day-to-day administration with Aviz ONES to assist. At the AI factory level, ONES follows NVIDIA's reference architecture across DGX, HGX, and NVL systems, unifying Day 0 fabric validation, Day 1 tenant provisioning with guardrails and segmentation, and Day 2 telemetry across both the front-end and back-end networks. NetworkCopilot tool helps in performing audits and network issues that may arise and detect abnormalities that occur over time as it is challenging to monitor operations in today's large-scale infrastructure setup for AI. The message: beyond the GPUs, AI-based infrastructure also depends on network capabilities.

Learn more:
 https://aviznetworks.com/products/accelerating-ai-networking-with-nvidia-ai-factory-and-aviz-ones

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