星环科技-U（688031） 算力架构革命，星环 GPU-Native 数据库先 行 证券研究报告·公司深度研究·软件开发 执业证书：S0600521080005 021-60199781 wangzj@dwzq.com.cn 证券分析师 王世杰 执业证书：S0600523080004 wangshijie@dwzq.com.cn 股价走势 -25% -14% -3% 8% 19% 30% 41% 52% 63% 74% 2024/12/17 2025/4/17 2025/8/16 2025/12/15 星环科技-U 沪深300 买入（首次） | [Table_EPS] 盈利预测与估值 | 2023A | 2024A | 2025E | 2026E | 2027E | | --- | --- | --- | --- | --- | --- | | 营业总收入（百万元） | 490.81 | 371.49 | 425.55 | 487.86 | 583.02 | | 同比（%） | 31.72 | (24.31) | 14.55 | 14.64 | 19.51 | | 归母净利润（百万元） | (288.24) ...

Investment Rating - The report maintains an "Overweight" rating for the computer industry [1] Core Insights - The emergence of AI inference necessitates a new storage architecture centered around GPU directly connected to SSD, which will replace the CPU-dominated era [9][14] - The shift from CPU-centric to GPU-centric architecture will drive significant changes in database software design, optimizing for GPU's data processing capabilities [18][19] - The industry is witnessing accelerated advancements in both hardware and software, with notable collaborations and innovations aimed at enhancing performance for AI workloads [22][24] Summary by Sections AI Inference Era and New Storage Architecture - AI inference requires different I/O demands compared to training, with a focus on small data blocks and high concurrency, leading to the need for a new storage architecture [9][10] - The traditional CPU-centric data loading architecture is becoming a bottleneck for AI workloads, necessitating a shift to GPU as the primary controller for data access [11][14] Changes in Database Architecture - The transition to GPU-centric architecture will require a complete redesign of database software, with GPU taking on the role of the main computing unit [18][19] - Key components such as storage engines and query execution engines will need to be restructured to optimize for GPU capabilities and direct SSD connections [19][21] Industry Progress - Hardware advancements include the development of High Bandwidth Flash (HBF) technology, which is expected to play a crucial role in the future of AI storage solutions [22] - Collaborations between companies like SanDisk and SK Hynix aim to standardize HBF technology, with initial products expected by 2027 [22] - Software improvements are being made to enhance data orchestration and performance, such as Hammerspace's advancements in metadata reading and Cloudian HyperStore's object storage capabilities [24] Investment Recommendations - The report suggests that as AI inference grows, the importance of GPU will increase, leading to new opportunities in the database industry as software architectures adapt to these changes [25][26]