AI Cluster Reference Design

When building a large GPU cluster for artificial intelligence (AI) training purposes, the backend network fabric should be a high-performance, lossless and predictable one. This guide describes the capabilities of DriveNets Network Cloud-AI and showcases a high-level reference design for an 8,000 GPU cluster, equipped with 400Gbps Ethernet connectivity per GPU.

Martin Perlin Marketing Communications Director

September 4, 2024

1 min read

This design explores network segmentation, high-performance fabrics, and scalable topologies, all optimized for the unique demands of large-scale AI deployments.
In this guide you will learn about:

  • The GPU cluster network architecture
  • Example – an 8,192 GPU cluster build
  • The rack elevation and data center layout

Download the Guide

TopicsAI Networking

Continue reading

DriveNets Advances Open Backend Networking for AI with AMD

Industry Events

DriveNets Advances Open Backend Networking for AI with AMD

DriveNets works with AMD to deliver an open, full stack backend networking solution for AI advanced by AMD Instinct™ M ...

Read more

Collateral

AMD and DriveNets Reference Architecture

Building high-performance AI clusters is no longer a matter of adding GPUs.

Read more

White Papers

Faster LLM Inference on AMD Requires Rethinking All-Reduce

Extracting maximum ROI from AMD AI clusters requires moving beyond out-of-the-box software bottlenecks.

Read more