RDMA Over Converged Ethernet

RDMA over Converged Ethernet (RoCE) aims to leverage the high-speed capabilities of RDMA for data transfer within standard Ethernet networks, addressing the communication bottlenecks in large-scale computing tasks. Current research focuses on optimizing RoCE for demanding applications like large language model (LLM) training and inference, including developing efficient data transfer strategies (e.g., chunked transmission) and congestion control mechanisms tailored to the specific communication patterns of these models. These advancements are crucial for improving the scalability and performance of distributed AI systems, enabling faster training and deployment of increasingly complex models across diverse hardware environments.