证券代码：603019 证券简称：中科曙光 公告编号：2026-014 曙光信息产业股份有限公司 2026年第一次临时股东会决议公告 一、 会议召开和出席情况 (三) 出席会议的普通股股东和恢复表决权的优先股股东及其持有股份情况： | 1、出席会议的股东和代理人人数 | 3,823 | | --- | --- | | 2、出席会议的股东所持有表决权的股份总数（股） | 359,006,489 | | 3、出席会议的股东所持有表决权股份数占公司有表决权股 | | | 份总数的比例（%） | 24.5502 | (四) 表决方式是否符合《公司法》及《公司章程》的规定，会议主持情况等。 本次股东会由公司董事会召集，经公司过半数董事推举，由董事崔梓杰先生 主持，会议采用现场投票与网络投票相结合的表决方式，会议的通知、召开、表 决方式符合《公司法》及《公司章程》的规定。 (五) 公司董事和董事会秘书的列席情况 (一) 股东会召开的时间：2026 年 3 月 25 日 (二) 股东会召开的地点：北京市海淀区中关村软件园 36 号楼会议室 本公司董事会及全体董事保证本公告内容不存在任何虚假记载、误导性陈述 或者重大遗漏，并 ...

北京市中伦律师事务所 关于曙光信息产业股份有限公司 2026 年第一次临时股东会的 法律意见书 二〇二六年三月 北京市中伦律师事务所 关于曙光信息产业股份有限公司 2026 年第一次临时股东会的 法律意见书 致：曙光信息产业股份有限公司 北京市中伦律师事务所（以下简称"本所"）接受曙光信息产业股份有限公 司（以下简称"公司"）委托，指派本所律师对公司 2026 年第一次临时股东会 进行见证，并出具《北京市中伦律师事务所关于曙光信息产业股份有限公司 2026 年第一次临时股东会的法律意见书》（以下简称"法律意见书"）。 为出具本法律意见书，本所律师见证了公司 2026 年第一次临时股东会，并 根据《中华人民共和国证券法》（下称《证券法》）、《中华人民共和国公司法》 （下称《公司法》）、《上市公司股东会规则》（下称《股东会规则》）、《律 师事务所从事证券法律业务管理办法》等法律、法规和规范性文件的要求以及《曙 光信息产业股份有限公司章程》（下称《公司章程》），按照律师行业公认的业 务标准、道德规范和勤勉尽责精神，查阅了本所律师认为出具本法律意见书所必 须查阅的文件，对公司本次股东会的召集和召开程序、出席会议人员资 ...

受再融资新政落地等因素影响，今年以来可转债发行明显提速。 Wind数据显示，截至3月23日，今年以来已有20家A股上市公司发布可转债发行预案，发行规模 在310亿元以上，相比2025年同期增长230%。其中，中科曙光、中创智领、申通快递等公司计划 可转债发行规模排名居前。 业内人士指出，可转债发行规模提速，是政策松绑、企业融资需求共振的积极信号，也为缓解长 期困扰市场的供需矛盾带来转机。 新政"松绑"点燃发行热情 近日，申通快递发公告称，公司拟通过向不特定对象发行可转换公司债券募集资金，总额不超过 人民币30亿元（含本数）。扣除发行费用后，募集资金将全部用于智慧物流设备升级项目及干线 运力网络提升项目。 公司表示，本次发行方案考虑了公司目前所处行业的现状、未来发展趋势及公司的发展战略，经 董事会审慎研究制定，并经全体董事表决通过。本次发行方案的实施将有利于公司持续稳定的发 展，有利于增加全体股东的权益。 记者梳理发现，申通快递此次发行预案为今年以来新增可转债预案中，发行金额排名第三的项 目。今年2月，中科曙光透露，拟发行不超过80亿元可转债，发行期限为6年，募集资金将全部用 于先进算力集群系统、AI训推一体机 ...

证券研究报告 计算机 报告日期：2026 年 03 月 23 日 Minimax 发布 M2.7，阿里云部分产品提价 ——计算机行业周报 华龙证券研究所 投资评级：推荐（维持） 最近一年走势 执业证书编号：S0230526030001 邮箱：zhulx@hlzq.com 《政府工作报告再提"人工智能+"， 2026.03.09 AI 基建投资机会—计算机行业周报》 2026.03.02 《北美云服务局部涨价，AI 应用按下加 速键—计算机行业周报》2026.02.02 请认真阅读文后免责条款 摘要： 执业证书编号：S0230523080004 邮箱：sunbw@hlzq.com 分析师：孙伯文 MiniMax 发布 M2.7，首次实现模型自我进化能力。MiniMax 于 2026 年 3 月 18 日发布了新一代 Agent 旗舰大模型 M2.7，核心的 突破在于首次实现了"模型自我进化" 。M2.7 能够通过构建复 杂 Agent Harness，深度参与自身的训练、优化与迭代流程，例如 自动执行超过 100 轮"分析-改进-验证"的闭环，最终通过优化 在内部评测集上实现约 30%的效果提升，并能够在 RL ...

Investment Rating - The report maintains a "Recommended" rating for the computer industry [1] Core Insights - The demand for AI inference is continuously growing, driven by a significant increase in tokens usage, with a reported increase from 1.62 trillion tokens in March 2025 to 18 trillion tokens in March 2026, representing a growth of approximately 1011% [6][11] - Cloud service providers are raising prices for AI computing products due to rising hardware costs and increased demand for AI services, with price hikes ranging from 5% to 34% for various services [8][33] - The report highlights that the expansion of AI capabilities is expected to lead to a substantial increase in the number of active agents and token consumption, with annual token consumption projected to grow from 0.0005 PetaTokens in 2025 to 152,667 PetaTokens by 2030, reflecting a compound annual growth rate of 3418% [9][38] Summary by Sections Recent Trends - The computer industry has shown a relative performance decline of -10.1% over the past month, while the Shanghai Composite Index has remained stable [5] Price Adjustments - Major cloud providers like Alibaba Cloud and Baidu Cloud are increasing prices for AI computing services due to rising hardware procurement costs, with specific increases of up to 34% for Alibaba's AI computing services and 30% for Baidu's [8][27] Token Consumption Growth - The report indicates a significant rise in token consumption, with OpenClaw being a major contributor, achieving a monthly token call volume of 13.4 trillion as of March 2026 [17] - The share of domestic models in token consumption is increasing, with domestic models accounting for approximately 53.4% of the top models' total token calls as of March 2026 [14] Future Outlook - The report anticipates that the demand for AI computing and tokens will continue to rise, benefiting cloud service providers and related upstream and downstream companies [10][44] - The ongoing increase in hardware costs and the demand for AI services suggest that price adjustments in the cloud computing sector may persist [9][33]

风险提示：宏观经济下行；股市波动率上升；金融监管力度抬升超预期。 该基金属于股票型基金，预期风险收益水平较高；历史表现不代表未来。 2026 年 03 月 21 日 证券分析师 于明明 执业证书：S0600525120002 yumm@dwzq.com.cn 证券研究报告·金融工程·金工专题报告 金工专题报告 20260321 新华中证云计算 50ETF：AI 时代的算力配置 核心工具 证券分析师 孙石 执业证书：S0600526020001 suns@dwzq.com.cn 相关研究 《 市场情绪温和修复，大盘波动仍需 警惕》 2026-03-15 《华安国证石油天然气 ETF 正在发 行：一键布局油气产业链》 2026-03-12 东吴证券研究所 1 / 17 请务必阅读正文之后的免责声明部分 [Table_Tag] [Table_Summary] 作为人工智能时代的关键基础设施，云计算是人工智能深度赋能实体行 业的必要基座，也是加快形成新质生产力，推动我国数字经济走向新发 展阶段的重要助力。 中证云计算 50 指数（指数代码：931469，以下简称"云计算 50"）选取 50 只业务涉及提供基础设施即服 ...

当智算成为新质生产力的核心底座，融资租赁正从 "融物承新" 迈向 "智融赋产" 的全新阶段。算力需求从集中式训练走向分布式推理，从巨头专属走 向中小企业普惠，"算力 + 能源 + 服务 + 生态" 已成为行业方向。如何以融资租赁为桥，打通智算资源+能源资源，从而赋能实体产业？如何了解上市 公司真实需求，盘活算力资产、释放服务潜能？ 上海市融资租赁行业协会、第一财经、上海交易集团联合主办的《融资租赁产融讲坛丨算电协同与租赁业务拓展》，特邀头部租赁机构负责人、智算 企业负责人及金融基础设施负责人齐聚上海，聚合AI和智算协同产业链的多方力量，助力产业公司与租赁机构深度链接。 2026年3月27日 14:00 会议议程 14:00-14:10 主办方/指导单位致辞 14:10-14:40 主题分享1:《新阶段 智算业务发展前瞻》 韩雪斌 中科曙光 (603019) 智算业务负责人 资深工程师 14:40-15:10 主题分享2:《上市公司算力业务发展及财务规划》 林 明 优刻得(688158)财务总监 15:10-15:40 主题分享3:《"算电协同"实践与产业应用》 朗新科技(300682)集团股份有限公司 杜杰 ...

| I | | --- | | 2026 年第一次临时股东会会议议程 | | 2026 年第一次临时股东会会议须知 | | 议案一 关于公司符合向不特定对象发行可转换公司债券条件的议案 4 | | 议案二 关于公司向不特定对象发行可转换公司债券方案的议案 5 | | (一)发行证券的种类 . | | (二) 发行规模 | | (三) 票面金额和发行价格 . | | (四) 债券期限 | | (五) 债券利率 | | (六) 付息的期限和方式 | | (七) 转股期限 . | | (八) 转股价格的确定及其调整 | | (九)转股价格向下修正条款 | | (十)转股股数确定方式 | | (十一) 赎回条款 . | | (十二) 回售条款 . | | (十三) 转股年度有关股利的归属 | | (十四) 发行方式及发行对象 | | (十五)向原股东配售的安排 | | (十六) 债券持有人会议相关事项 . | | (十七) 本次募集资金用途 | | (十八) 担保事项 | | (十九) 评级事项 | | (二十) 募集资金存管 | | (二十一) 本次发行方案的有效期 | | 议案三 关于公司向不特定对象发行可转换公 ...

Investment Rating - The report does not explicitly state an investment rating for the cloud computing industry or the specific ETFs mentioned. Core Insights - The AI technology innovation cycle is divided into two halves: the first half focuses on model and method innovation, while the second half emphasizes problem definition and the integration of AI into real-world applications, with a focus on application value [4][7]. - The CSI Cloud Computing 50 Index comprehensively covers the entire cloud computing industry chain, balancing hardware and software, and aims to capture both AI computing infrastructure benefits and software growth opportunities [4][9]. - The report highlights that the cloud is a core component in the second half of the AI technology cycle, where the focus shifts from training to inference, making cloud computing essential for AI applications [7][79]. Summary by Sections Cloud Computing Overview - Cloud computing is defined as the centralized management and dynamic allocation of resources via the internet, likened to utilities like water and electricity [18]. - The global cloud computing market reached a size of 586.4 billion yuan in 2023, with a growth rate of 19.4%, and is expected to exceed one trillion dollars by 2027 [20]. AI's Impact on Cloud Computing - AI is creating new demands in the IaaS and MaaS layers, particularly for large model calls and custom model needs, leading to a shift in cloud service architectures [8][82]. - The business model for cloud computing is anticipated to transition from resource pricing to value pricing, which could enhance gross margins for cloud resources in the long term [8][85]. CSI Cloud Computing 50 Index - The index includes companies providing IaaS, PaaS, and SaaS, selected based on liquidity, growth potential, and market capitalization, ensuring a balanced representation of the cloud computing sector [9][10]. - The index has shown strong performance compared to mainstream indices, indicating its long-term investment value [9]. New Investment Opportunities - The report emphasizes the growth potential in the AI large model solutions market and the MaaS market, both expected to experience rapid growth in the coming years [87][88]. - The integration of GPU, cloud, and AI is seen as a significant growth driver, allowing cloud providers to differentiate their services and enhance their competitive edge [8][94].

Core Insights - The AI era is facing a critical challenge with the shortage of high-speed interconnect networks, which is essential for the efficient operation of large-scale computing clusters [1][10] - Domestic companies are making strides in developing their own computing chips, but the core technology for high-speed interconnects remains dominated by Nvidia, posing a significant risk to the industry [1][10] Group 1: Industry Challenges - The transition from GPU to high-speed interconnects is becoming a new bottleneck as the scale of computing clusters increases from thousands to tens of thousands of nodes [1][4] - The communication time in distributed training can account for 30-50% of the total time, indicating that a significant portion of the investment in computing power is wasted on data transfer rather than computation [4][5] - The demand for high-speed networks has increased by 10 to 20 times as servers now require multiple network cards to support GPU-centric architectures [6] Group 2: Technological Landscape - There are two main technological routes in the high-speed network domain: RoCE and InfiniBand, with the latter being the preferred choice for high-performance computing due to its superior performance metrics [7][10] - InfiniBand networks are used in approximately 60% of the world's high-performance computing systems, and they are almost standard in the largest AI training clusters [10] Group 3: Domestic Developments - In response to the challenges posed by the dominance of foreign technology, companies like Zhongke Shuguang have developed their own high-speed network solutions, such as the scaleFabric, which is fully self-developed [2][11] - The decision to pursue a fully self-developed InfiniBand system was driven by the inadequacy of available commercial IPs and open-source solutions to meet the performance and reliability requirements for large-scale clusters [12]