AI Data Center Networking: Scaling Up, Out, and Across With 102.4T Ethernet
Data Center Knowledge, Thursday, August 20th, 2026
As network silicon becomes the bottleneck, 102.4 Tbps switching targets latency and multi-site AI cluster connectivity.
Data Center Knowledge contributor Drew Robb examines next-generation switching architecture for AI clusters. AI clusters depend on predictable bandwidth and low tail latency, and network silicon has become the bottleneck as clusters scale.
The article covers 102.4 Tbps Ethernet switching and what that capacity enables. It distinguishes scaling up within a rack, scaling out across a cluster, and scaling across multiple sites.
Multi-site connectivity is treated as a distinct problem because training jobs increasingly span facilities.