Network Fabric

Network fabrics encompass the underlying communication infrastructure connecting computational units, impacting performance in diverse applications from large-scale machine learning to multi-robot coordination. Current research focuses on optimizing communication schedules for heterogeneous fabrics, employing techniques like spanning trees for efficient collective communication and dynamic optimization fabrics for real-time motion planning in robotics. These advancements aim to improve the speed and scalability of complex systems, leading to significant performance gains in areas such as large language model training and real-time robotic control.