Fat-Tree Topology

<p>A fat-tree is a multi-layer network topology in which the number of links (and therefore bandwidth) increases towards the core of the network, ensuring that any-to-any communication can occur at full line rate — no bandwidth bottleneck exists at the core. This property, called full bisection bandwidth, is essential for distributed AI training where every GPU must communicate with every other GPU at high speed.</p><p>In practice, fat-tree networks are implemented using a multi-stage Clos design. A k-port switch fat-tree can connect k³/4 hosts with k² core switches and k²/2 aggregation switches. InfiniBand HDR/NDR fabrics for AI clusters commonly use fat-tree or flattened butterfly topologies. Spine-leaf is a simplified two-tier fat-tree, appropriate when full bisection bandwidth is not required.</p>