Stateless scheduler doubles LLM training speed

Fine-tuning large language models often faces bottlenecks from rigid GPU allocation and inefficient pipeline parallelism. A new stateless scheduler, RoundPipe, optimizes training by dynamically dispatching computation stages across a pool of GPUs, effectively doubling LLM training speed.