Core Viewpoint - The recent developments in China's semiconductor industry, including new regulations and export restrictions from the U.S., highlight the urgent need for domestic computing power localization as a critical choice for various sectors in China [1]. Group 1: Domestic Computing Power Development - The "2024 China Computing Power Development Report" indicates that by 2024, the total scale of computing power centers in China will exceed 8.3 million standard racks, with a total computing power of 246 EFLOPS, ranking among the top globally [2]. - Experts emphasize the importance of confidence in domestic computing facilities, asserting that they possess international competitiveness and should be actively utilized [2]. - A "research first" strategy is proposed to overcome the bottlenecks in the application of domestic computing power, particularly in commercial sectors where cost pressures exist [2]. Group 2: High-Performance Computing (HPC) Significance - High-performance computing centers, with vast storage and advanced processing capabilities, are crucial for scientific research and innovation in fields such as engineering simulation and genetic analysis [3]. - The advancement of domestic high-performance computing has significantly improved capabilities in areas like cosmic simulations, enhancing the precision of research [3]. Group 3: Systematic Innovation for Competitiveness - Experts argue that surpassing foreign counterparts in domestic computing power requires systematic innovation rather than relying on individual devices or metrics [4]. - The urgency for domestic computing power localization is underscored by recent restrictions on access to key biomedical databases for Chinese users, highlighting the need for a robust domestic supply chain [4]. Group 4: Policy and Ecosystem Development - The establishment of a domestic computing ecosystem is deemed essential, with suggestions for collaboration between manufacturers and research institutions to create open-source communities [7]. - Strong policy measures are advocated to ensure the successful implementation of domestic computing power solutions, as voluntary efforts may not suffice [7].

Core Insights - The increasing global supply chain risks for high-performance computing highlight the importance of domestic computing capabilities in China's information industry and other sectors [1][3] - Experts emphasize the need for confidence in domestic computing facilities, innovative systems, and collaborative ecosystems to build a self-sufficient computing framework [1][3] Group 1: Domestic Computing Development - The "2024 China Computing Development Report" indicates that the total scale of computing centers in use will exceed 8.3 million standard racks, with a total computing capacity of 246 EFLOPS, ranking among the top globally [3] - Despite the large total computing capacity, the contribution of domestic computing facilities remains low, necessitating a shift in mindset to utilize domestic technology confidently [3][4] - Zhang Yunquan suggests a "research-first" strategy to overcome bottlenecks in the adoption of domestic computing technologies, particularly in commercial sectors facing cost pressures [3][4] Group 2: High-Performance Computing Significance - High-performance computing centers play a crucial role in advanced research fields such as scientific computation, engineering simulation, and genetic analysis, making their domestic development vital for sustainable innovation [4] - Domestic high-performance computing clusters, such as those developed by Sugon, can seamlessly integrate with mainstream software ecosystems, addressing over 95% of migration issues [4] - The recent restrictions by the U.S. National Institutes of Health on access to core biomedical databases for countries including China underscore the urgency of domestic computing capabilities [4][5] Group 3: Innovation and Collaboration - Achieving innovation in domestic computing requires attention to foundational theories, as highlighted by Chen Runsheng, who notes the efficiency of the human brain compared to large AI computing clusters [5] - Recommendations include forming open-source communities among domestic manufacturers and research institutions to foster iterative innovation while adhering to international standards [5] - Collaborative efforts across academia, industry, and application sectors are essential to identify common algorithms and optimize chip design and software development for broader domestic adoption [5]