来源：鲁网 "惟楚有材，于斯为盛。"岳麓书院门前的千古名联，一直是三湘大地文化自信的象征。 而随着世界计算大会永久落户长沙，国家超算长沙中心建成运营，今日之湖南俨然已成为全国计算产业 的重要节点。算力恰如当代的"洞庭水系"，滋养着湖南千行万业的数智化转型，为湖南数字经济注入源 源不断的智能活水。 超节点其实代表了算力工程化创新的极致水平。当智算中心转向"精打细算的挤效率"，这就要求算力从 分散部署走向泛在协同，超节点的出现则以极致的密度、效率与协同能力，成为当下算力工程化创新的 标尺。 而华为恰是通过系统工程创新，在整体方案上形成更强优势。目前，华为超节点已交付300多套给30多 个关键客户，在实践中验证了其技术领先性。 郁赛华强调说，"超节点也是华为最低时延+最强算力的组合"。这背后其实也是华为聚焦ICT基础能力 的使然，华为长期聚焦于联接产业和计算产业，也正是这一战略定位使华为在算力领域形成了完整的技 术栈。 湖南也正依托华为的算力，将技术与数智化经验相融合，催生出一系列创新实践，湖南的数字经济版图 也由此焕发出蓬勃生机。 1）算力筑基，构建系统级创新的发展底座 现阶段人工智能的竞争，本质上就是算力的竞争 ...

Investment Rating - The report maintains an "Outperform" rating for the industry [6] Core Insights - Huawei's new products, including Ascend chips and supernodes, are set to lead a new era in computing power, with a clear roadmap for product iterations from 2025 to 2028 [1][14] - The introduction of self-developed HBM technology marks a significant advancement in memory bandwidth, enhancing the efficiency of large model training [3][23] - The supernode architecture is designed to integrate hundreds of processors, reshaping the competitive landscape in AI infrastructure [22][24] Summary by Sections 1. Huawei Computing Power Product Launch - Ascend chips will follow a yearly iteration schedule, with the 910C launching in Q1 2025 and subsequent models (950PR, 950DT, 960, 970) planned through 2028 [14][15] - The Ascend 950 series introduces low-precision data formats and self-developed HBM, enhancing training efficiency for large models [15][16] - The Ascend 960 and 970 are expected to double performance metrics across various parameters, including computing power and memory bandwidth [18][19] 2. Supernode Products - The supernode data center (Atlas 900/950/960 SuperPoD) is designed for large-scale AI training, achieving EFLOPS-level computing power with high bandwidth and low latency [2][27] - The supernode cluster (Atlas 950/960 SuperCluster) enhances network performance and energy efficiency, reaching ZFLOPS-level computing power [2][37] - The enterprise-grade air-cooled supernode server (Atlas 850) is tailored for post-training and multi-scenario inference, supporting flexible scaling [2][38] 3. Related Investment Targets - Key investment targets include hardware partners for Ascend, domestic wafer foundries, and companies involved in copper connections, optical connections, power supplies, PCBs, and cooling solutions [4][46]