Networking & Interconnects
High-speed fabrics connecting GPU clusters—InfiniBand, 800G Ethernet, NVLink, and the architectures that eliminate training bottlenecks.
In distributed AI training, your network is often the bottleneck, not your GPUs. When thousands of accelerators need to synchronize gradients, the difference between a well-designed fabric and an afterthought can mean weeks of training time—or models that simply can't converge.
This hub covers the networking technologies that make large-scale AI possible: from InfiniBand's dominance in HPC to Ethernet's push into AI-optimized territory.
What We Cover
- InfiniBand vs. Ethernet — When to use each technology, and how RDMA capabilities are converging across both
- Network Topologies — Fat-tree, dragonfly, and rail-optimized designs: matching topology to workload characteristics
- GPU Interconnects — NVLink, NVSwitch, and the evolution toward coherent multi-GPU systems
- 800G and Beyond — Next-generation Ethernet speeds and the optical technologies enabling them
- Congestion & Flow Control — DCQCN, ECN, and the traffic engineering that keeps large clusters performing
The network connecting your GPUs deserves as much attention as the GPUs themselves. Our networking coverage helps you design fabrics that let your accelerators actually accelerate.
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