A nchor : Mitigating GPU Shallow Disruptions with Decoupled Memory

Job failures are frequent in large-scale GPU clusters for LLM workloads, leading to significant resource wastage. The vast majority of these are shallow disruptions (e.g., software errors or updates), where only the worker process crashes while the underlying GPU and OS kernel remain intact. Existing recovery systems, however, are failure-agnostic, relying on heavyweight checkpointing that forces a full, slow state reload even when the data could have survived on the GPU.