AI 基礎設施/分散式運算
Ray Pushes TPU Slice Scheduling Down into Serve, Data, and Train, Unifying Multi-Host AI Workflows
Google has unveiled a complete AI library path for running Ray on TPUs, using a topology field to ensure model workers are placed within the same ICI slice. The new release also adds native JAX data batching, JaxTrainer, official containers, and TPU monitoring, though GKE remains the primary validated environment.