Year: 2025
Type: conference-paper
Abstract: 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.
Authors: Yuxuan Chen, Menghao Zhang, Xiheng Li, Fangzheng Jiao, Xiao Li, Jiaxun Huang, Shicheng Wang, Chunming Hu
Institutions: Beihang University, Tsinghua University
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Awards: G1215463260, G7291191679
OpenAlex ID: W4414109804