Efficient Training on Multiple Consumer GPUs with RoundPipe.

arXiv:2604.27085v2 Announce Type: replace-cross Abstract: Fine-tuning Large Language Models (LLMs) on consumer-grade GPUs is highly cost-effective, yet constrained by limited GPU memory and slow PCIe interconnects. Pipeline parallelism combined with CPU offloa