PReCCL: Performant and Resilient Collective Communication via Integrated Inband Telemetry and Workload Reallocation

Modern collective communication libraries (CCLs) execute a collective communication task (CCT) by decomposing it into multiple sub-tasks, each mapped to a specific Virtual Topology (VT), which is an ordered graph of GPUs (e.g., a ring or a tree), to maximize parallelism and link utilization. As AI training scales to larger clusters, network anomalies (congestion and failures) are unavoidable, and a single straggling VT can delay the entire CCT. Existing solutions either rely on low-level transport-layer solutions which lacks a cross-sub-task perspective, or static CCL scheduling, failing to adapt to the dynamic and heterogeneous networks.