Ennan Zhai

Large Language Model (LLM) inference services in production operate under stringent, fine-grained Service Level Objectives (SLOs). Unlike throughput-oriented LLM training, even sporadic performance anomalies during inference can violate SLOs, underscoring the need for improved tracing and diagnos...

Large-scale ML training jobs are frequently interrupted by hardware and software anomalies, failures, and management events. Existing solutions like checkpoint-restart or runtime reconfiguration suffer from long downtimes and degraded performance. We present TrainMover, a resilient LLM training r...