Vedrfolnir: RDMA Network Performance Anomalies Diagnosis in Collective Communications

Collective communication becomes increasingly crucial as large language models rapidly evolve, but the RDMA it uses inevitably faces network performance anomalies (NPAs). Vedrfolnir is an accurate and efficient diagnosis system for RDMA NPAs in collective communication, which (1) constructs waiting graphs through algorithm decomposition, (2) adaptively detects anomalies while efficiently collecting diagnostic data, and (3) precisely analyzes performance bottlenecks and root causes. Evaluation shows that Vedrfolnir can achieve accurate diagnosis results with low overhead.