CAD Decouples Attention, Boosts LLM Training 1.35x

Core Attention Disaggregation (CAD) solves the LLM long-context bottleneck by decoupling the attention mechanism, achieving a 1.35x training throughput boost. This innovation enables significantly more efficient, large-scale LLM application.