Core Viewpoint - The competitive rules of China's AI industry are being rewritten, shifting the focus from hardware performance to ecological collaboration efficiency as a new measure of competitiveness in the AI computing industry [1][4]. Group 1: Industry Trends - The HAIC2025 event showcased over 2,500 upstream and downstream enterprises, indicating a trend towards breaking down "technology walls" and "ecological walls" to achieve a "group leap" in the AI computing industry [1][3]. - The concept of "open architecture" is becoming essential for overcoming industry bottlenecks, as it promotes shared key technologies and lowers the barriers for research and application [4][6]. Group 2: Open Architecture and Collaboration - The AI computing open architecture aims to transform the industry from "physical stacking" to "chemical fusion," addressing issues such as high-end computing power shortages and high innovation thresholds [6][10]. - The launch of the scaleX super cluster, capable of deploying 10,240 AI accelerator cards and exceeding 5 EFlops in total computing power, demonstrates the technical feasibility and advantages of the open architecture [4][6]. Group 3: Partner Practices and Innovations - Companies like Qingdao Thunder Technology and Unisplendour have successfully utilized the open architecture to lower R&D costs and enhance product compatibility, leading to innovations in various industry scenarios [7][8]. - The collaborative model of "multi-vendor cooperation and shared foundation support" has proven effective in driving the domestic AI ecosystem into a "group leap" phase, with significant advancements in sectors like gaming and healthcare [7][9]. Group 4: Future Outlook - The establishment of the "AI Computing Open Architecture Joint Laboratory" aims to invest 1 billion yuan over three years, involving over 150 member units and 1,000 R&D personnel to enhance domestic AI capabilities [12]. - The ongoing reinforcement of the open architecture's "linking" role is expected to lead to a higher quality "group leap" in the domestic AI ecosystem, providing solid support for the implementation of the "Artificial Intelligence +" strategy [12].

Core Insights - The development of AI large models requires significant resources, including a large number of technical experts and substantial financial investment, with a critical need for powerful computing capabilities [1] - The demand for computing power is expected to grow exponentially across various industries, with IDC predicting that China's intelligent computing power demand will reach 2781 EFLOPS by 2028, reflecting an annual growth rate of 46.2% [1] - Traditional computing clusters face bottlenecks when scaling beyond thousands of cards, necessitating innovative solutions like the "ten-thousand card super cluster" [2] Group 1: ScaleX Ten-Thousand Card Super Cluster - The ScaleX ten-thousand card super cluster system was unveiled by Sugon at the HAIC2025 conference, designed to meet the extreme demands of AI infrastructure [3] - This system features 16 super nodes connected by a proprietary high-speed network, capable of supporting 10,240 AI accelerator cards, marking a significant advancement in domestic large-scale computing cluster technology [5] - The ScaleX system achieves a total computing power exceeding 5 EFLOPS, with a power usage effectiveness (PUE) value as low as 1.04, enhancing computing density by 20 times [5][9] Group 2: Technical Advantages - The ScaleX system utilizes a self-developed RDMA high-speed network, achieving 400 Gb/s bandwidth and under 1 microsecond communication latency, significantly improving communication performance [9] - The system incorporates deep optimization for storage, computing, and transmission, enhancing resource utilization by 55% during large model training [9] - It features a digital twin for intelligent scheduling and management, ensuring 99.99% availability and supporting the management of tens of thousands of nodes [9] Group 3: Open Architecture and Ecosystem Development - The ScaleX super cluster supports multiple brands of accelerator cards and mainstream computing ecosystems, promoting an open architecture for AI computing [10] - This initiative aims to lower the barriers for AI companies to develop intelligent computing clusters and foster a collaborative industrial ecosystem [10][12] - The open model allows users greater choice and compatibility with mainstream AI development frameworks, facilitating broader participation in the ecosystem [12][13]

2025年12月18日，在昆山举行的光合组织2025人工智能创新大会（HAIC2025）上，中科曙光发布并展出了全球领先的大规模智能计算系统——scaleX万卡 超集群，这也是国产万卡级AI集群系统首次以真机形式亮相。 作为 "AI计算开放架构"最新重磅成果，scaleX万卡超集群可支持多品牌加速卡以及主流计算生态，并实现400+主流大模型、世界模型等适配优化。在实际应 用中，该超集群可覆盖大模型训练、金融风控、地质能源勘探及科学智能等多元场景。 "AI计算开放架构" 由中科曙光协同20多家AI产业链企业共同推出，以共享若干关键共性技术能力，依托系统工程思维推进智算集群创新。通过scaleX万卡超 集群，AI企业可降低智算集群研发门槛，并从技术"单点突围"走向产业"生态共进"，将开放理念转化为可落地普惠算力。 优势1：全球首创单机柜级640卡超节点。scaleX万卡超集群由16个曙光scaleX640超节点通过scaleFabric高速网络互连而成，可实现10240块AI加速卡部署， 总算力规模超5EFlops。作为世界首个单机柜级640卡超节点，scaleX640采用超高密度刀片、浸没相变液冷等技术，将单机 ...

经济观察网12月18日，光合组织2025人工智能创新大会(HAIC2025)在江苏昆山举行。作为国内首个聚 焦"AI计算开放架构"的行业大会，本次大会汇聚了来自芯片、服务器、存储、超节点、AIPC以及大模 型、智能体和行业应用等环节的产业链上下游机构与企业，覆盖从底层算力到系统平台再到应用落地的 完整链条。与会多方围绕开放架构下的算力协同、软硬件适配和生态共建展开交流，集中展示国产智能 计算在体系化推进中的阶段性成果。 在人工智能加速走向规模化应用的背景下，HAIC2025以"产业大集"的形式搭建跨领域协同平台，将推 动国产计算生态从单点突破向系统化、开放化演进，为智能计算产业的持续发展提供现实路径。 ...

聚焦"AI计算开放架构" 光合组织2025人工智能创新大会即将举办 编辑：王永乐 广告等商务合作，请点击这里 光合组织秘书长任京暘向媒体介绍光合组织2025人工智能创新大会相关情况。中新网记者 孙自法 摄 光合组织秘书长任京暘介绍说，光合组织2025人工智能创新大会将首次大规模集中展示国产人工智能 (AI)加速计算全栈技术，发布AI计算开放架构联合实验室行动计划，基于该架构打造的全球领先大规模 智算超集群系统也将亮相。该系统采用中国自主研发的高速互联网络技术，在算力密度与系统性能上实 现双重突破，验证了开放技术路线的可行性与竞争力。 光合组织2025人工智能创新大会将设立六大分论坛，邀请百余位专家分享前沿案例，促进产业全链协同 创新，为中国AI计算的可持续发展提供开放平台与实践样板。 据悉，光合组织自成立以来，始终以构建自主可控、开放协同的国产计算生态为使命，旨在汇聚产业全 链、共破发展瓶颈，目前已有超6000家合作伙伴，建成28个生态适配中心。(完) 来源：中国新闻网 中新网北京12月5日电 (记者 孙自法)中国国内首个以"AI计算开放架构"为核心的行业盛会——光合组织 2025人工智能创新大会(HAIC2 ...

Core Insights - The World Computing Conference held in Changsha showcased the ScaleX640 super node by Inspur, which is the world's first single-rack 640-card super node, achieving a 20-fold increase in computing density and supporting million-card-level cluster expansion, thus injecting strong domestic computing power into the development of new productivity [1][3]. Group 1: Product Features - The ScaleX640 super node consists of a single immersion liquid cooling heat exchange module and two immersion liquid cooling dedicated computer cabinets, representing a significant breakthrough as it surpasses traditional solutions that would require multiple cabinets to achieve similar computing power [3]. - The device utilizes immersion phase change liquid cooling technology, allowing it to maintain a stable operating temperature below 35 degrees Celsius, which is lower than typical gaming PCs, and achieves a Power Usage Effectiveness (PUE) of 1.04, meaning 96% of electricity is used for computing, resulting in over 30% energy savings compared to traditional air cooling solutions [4]. Group 2: Industry Impact - The ScaleX640 super node adheres to the "AI computing open architecture" concept, initiated by Inspur in collaboration with over 20 industry partners, aiming to build an open and collaborative innovation system to overcome challenges in domestic AI development, such as insufficient software-hardware synergy and fragmented ecosystems [5]. - The super node supports multi-brand acceleration cards and is compatible with mainstream computing ecosystems, enabling users to flexibly select domestic computing power for rapid deployment of trillion-parameter model training and high-throughput inference, effectively addressing the practical pain points of application adaptation and software-hardware disconnection in domestic intelligent computing [5].

Core Insights - The 2025 National College Student Computer System Capability Competition - Intelligent Computing Innovation Design Competition (Pilot Cup) successfully concluded in Hefei, emphasizing the importance of AI computing open architecture in the integration of industry, academia, and research [1][3] Group 1: Competition Overview - The Pilot Cup is the only intelligent computing track in the national competition, featuring a high prize pool and employment referral opportunities for winners [3] - This year, the competition introduced a "teaching and training competition" model, enhancing the relevance of competition topics, coverage of scenarios, and integration of education and industry [3] - The competition attracted nearly 10,000 students from over 1,200 universities, with 58 teams awarded [3] Group 2: Industry Impact - The competition addressed engineering challenges in AI implementation with three key topics: "MoE language model end-to-end efficiency optimization," "ONNX Runtime operator performance optimization," and "GMRES algorithm optimization" [3] - The Senior Vice President of Sugon, Li Bin, highlighted the launch of China's first AI computing open architecture, indicating a new phase for the Chinese AI industry and a growing demand for interdisciplinary AI talent [3] Group 3: Educational Initiatives - Sugon's computing platform is user-friendly for students, comparable to CUDA, and provides extensive free learning resources [4] - The Chief Scientist of Intelligent Computing at Sugon noted an explosive growth in AI talent demand, particularly in the era of large models, and emphasized the competition's role in expanding the audience for AI talent [4] - Sugon has consistently focused on talent education, launching various initiatives such as the Pilot Cup, developer communities, and joint laboratories to explore new models for AI talent cultivation [4]

Core Insights - The European Centre for Medium-Range Weather Forecasts (ECMWF) has announced the opening of its real-time data catalog to global users, providing access to high-resolution weather forecast data [2] - Zhongke Tianji, a subsidiary of Zhongke Shuguang, has launched a "High-Resolution Meteorological Data Sharing Plan," offering global and regional weather data with higher resolution and frequency [2][3] - The trend of data sharing and openness in the meteorological service industry is gaining momentum, driven by technological advancements and policy support [3][4] Group 1: Data Sharing Initiatives - ECMWF provides daily forecasts covering 1-15 days with a maximum resolution of 0.1° grid point data, including various meteorological variables [2] - Zhongke Tianji offers over 160 meteorological elements with a resolution of 12 kilometers globally and 3 kilometers for China, outputting data hourly for 15 days [2][3] - The simultaneous data sharing initiatives by ECMWF and Zhongke Tianji highlight a significant shift in the meteorological data service industry [2] Group 2: Policy and Technological Support - The acceleration of data sharing is supported by systematic restructuring from top-level design, with various provinces in China implementing market-oriented data reform plans [3] - The Chinese government is the largest contributor to data sharing, with platforms providing millions of data downloads and fostering numerous AI application scenarios [3] - The World Meteorological Organization's initiatives have increased the demand for forecast products, further promoting data openness [4] Group 3: Competitive Advantages of Zhongke Tianji - Zhongke Tianji's data offers higher resolution for China at 3 kilometers compared to ECMWF's 12 kilometers, catering to specific industry needs [4][5] - The data output frequency from Zhongke Tianji is more granular, providing hourly updates, while ECMWF uses tiered output intervals [5] - Access to Zhongke Tianji's data is free for domestic users, contrasting with ECMWF's cost structure, which can reach approximately 1.9 million for comprehensive data access [5] Group 4: Technological Innovations - Zhongke Tianji's data sharing is supported by advanced technologies, including deep integration of dynamics and physics, enhancing the quality of meteorological applications [6] - The company aims to address challenges in high-resolution simulations and timeliness through seven foundational technologies [6] - The establishment of an AI open computing architecture by Zhongke Shuguang represents a significant advancement in the AI industry, promoting collaborative innovation [7][8]

Core Viewpoint - The article emphasizes the need for a unified and collaborative computing ecosystem in China's computing industry, particularly in the context of AI development, highlighting the gap between national strategic goals and the current fragmented industry reality [1][2][12][13]. Group 1: Industry Challenges - The Chinese computing industry faces a fundamental dilemma: whether to pursue a vertically integrated model like Apple or an open collaborative model like Android [5][6]. - Currently, the industry is characterized by strong competition and weak cooperation, leading to resource wastage and inefficiencies due to incompatible technologies and private protocols [11][12]. - The lack of unified technical standards has resulted in significant challenges for users, who often face compatibility issues when integrating products from different manufacturers [34]. Group 2: National Strategy - National strategic documents, such as the "High-Quality Development Action Plan for Computing Infrastructure," emphasize the need for optimizing computing resource allocation and promoting standardization [9][10]. - The goal is to build a strong, unified national computing market, which is now a core focus of industry development rather than just a vision of individual companies [9]. Group 3: Company Initiatives - Inspiringly, the leading company in the field, Zhongke Shuguang, has taken the initiative to establish an "AI Computing Open Architecture" in collaboration with over twenty industry partners [5][6]. - This open architecture aims to facilitate systemic innovation across various segments of the computing ecosystem, moving away from isolated advancements to a more integrated approach [37][40]. - Zhongke Shuguang's commitment to open standards and data sharing is seen as a significant step towards addressing industry bottlenecks and enhancing collaboration [35][54]. Group 4: Technological Advancements - Zhongke Shuguang has invested in liquid cooling technology since 2011, achieving significant energy savings and increasing power density in data centers [18][19]. - The company’s comprehensive business model spans high-end computing, storage, and cloud computing, demonstrating its capability to understand and address the entire computing ecosystem [21][22]. Group 5: Financial Performance - In the first half of 2025, Zhongke Shuguang reported a revenue of 5.85 billion yuan, a 2.41% increase year-on-year, with a notable 29.39% growth in net profit [26][27]. - This financial stability allows the company to focus on long-term strategic initiatives that benefit the entire industry ecosystem rather than just short-term profits [28]. Group 6: Data Sharing Initiatives - Zhongke Shuguang has launched a high-resolution meteorological data sharing plan, providing valuable data resources to various industries, which can enhance operational efficiency and innovation [42][44]. - The shared data includes over 160 meteorological elements, significantly lowering the barriers to access for industries that previously faced high costs and complexity in obtaining such data [44][49]. Group 7: Vision for the Future - The ultimate goal of Zhongke Shuguang's initiatives is to create an open and inclusive computing ecosystem that supports the digital transformation of various sectors [53][54]. - By establishing a closed-loop ecosystem from foundational computing to application and data, the company aims to drive continuous optimization and innovation within the industry [52].

Group 1 - Zhongke Shuguang's subsidiary, Zhongke Tianji, has launched a high-resolution meteorological data sharing initiative, marking a significant milestone in China's AI industry for open sharing and industrial integration [1][2] - The shared meteorological data includes global 12 km and regional 3 km resolution data, covering over 160 meteorological elements such as temperature, wind field, and precipitation, with a time scale of up to 15 days and hourly updates [2][3] - The initiative addresses the data bottleneck, a key factor in AI development, as China has abundant data resources but lacks effective and high-quality domain-specific data [3][5] Group 2 - The AI computing open architecture, announced by Zhongke Shuguang in collaboration with over 20 industry partners, aims to foster collaborative innovation across the AI ecosystem, moving away from isolated technological advancements [4][5] - China's AI industry is projected to exceed 900 billion yuan in 2024, with a year-on-year growth of 24%, and over 5,300 companies operating in the sector [5] - The establishment of standards and frameworks for collaborative innovation, along with the development of legal regulations and ethical guidelines, positions China's AI industry for high-quality growth and a more significant role on the global stage [5][6]