中信证券：国产算力建设提速，超节点驱动网络侧高速成长

Core Viewpoint - The evolution of AI large models towards trillion parameters, multi-modal capabilities, and intelligent agents is driving a transition in computing infrastructure towards "super-node" architecture, which significantly enhances training efficiency and inference throughput [1] Group 1: Technological Advancements - Traditional architectures are facing communication and energy consumption bottlenecks, necessitating a shift to super-node architecture [1] - NVL72 represents a solution that improves training efficiency and inference throughput through high bandwidth and low latency interconnections [1] Group 2: Market Opportunities - The demand for switching chips, optical modules, and high-speed connection modules is shifting from linear growth to exponential growth due to the architectural transformation [1] - There is significant room for improvement in domestic AI computing investments compared to overseas, making super-node architecture essential for catching up in domestic computing infrastructure [1] Group 3: Industry Recommendations - Companies are advised to focus on the value reassessment opportunities arising from increased interconnection density [1] - Recommended sectors include high-speed connection module manufacturers, switching interconnection manufacturers, optical module manufacturers, and AIDC and supporting manufacturers [1]