lawrencel05/topology-aware-gpu-scheduling

This is an experimental GPU placement and scheduling research toolkit. A user discovers cluster GPU inventory, supplies a workload profile and inter-node link costs, plans a placement, and executes it through Ray or submits it through KAI; Dynamo supports a separate managed inference lifecycle. Comparison records and matched traces evaluate scheduling outcomes. The README documents topology discovery, NIC inventory, baseline policies and integrations; unsampled subsystems are shown only where their documented role is clear, and wiring is limited to supported calls.