Investment Rating - The industry investment rating is "Positive" (maintained) [1] Core Insights - The CXL protocol ecosystem is continuously improving, with major CPU manufacturers like Intel and AMD releasing CPUs that support CXL 2.0, enhancing compatibility and performance [5][11] - The demand for memory bandwidth and capacity is increasing in the AI era, leading to a need for solutions that address the "compute-storage imbalance" [12][13] - CXL technology allows for the construction of memory pools, enabling the decoupling of storage and compute resources, which is essential for optimizing resource utilization across devices [14][15] Summary by Sections CXL Protocol Ecosystem - The CXL protocol is being adopted by leading CPU manufacturers, with Intel and AMD launching compatible CPUs, and companies like SK Hynix and Samsung developing CXL-compatible memory modules [11][8] - The introduction of CXL Switch technology by Alibaba Cloud marks a significant advancement in server architecture, allowing for efficient memory resource sharing [20][10] Memory Pool Construction - CXL can create memory pools that address the challenges of memory islands and data overflow in data centers, enhancing memory utilization and performance [14][12] - The CXL protocol includes three core sub-protocols that facilitate memory pooling and management, allowing for dynamic memory allocation across multiple servers [15][16] Future Demand Projections - By 2030, the demand for CXL Switch and CXL MXC chips is projected to reach 7.06 million and 64.52 million units, respectively, under optimistic scenarios [27][28] - The report suggests that as the CXL ecosystem matures, the shipment volumes of CPUs and servers compatible with CXL protocols will gradually increase [29] Investment Recommendations - The report recommends focusing on companies such as 澜起科技 (CXL MXC chip supplier), 江波龙 (CXL AIC expansion card supplier), 佰维存储 (CXL 2.0 DRAM memory expansion module supplier), and 聚辰股份 (VPD chip supplier for CXL modules) as potential investment opportunities [29][5]

英特尔、AMD均已发布支持CXL2.0的CPU，SK海力士、三星电子正积极研发并量产CXL兼容的内存模 块，阿里云联合英特尔已推出全球首款基于CXL2.0Switch技术的PolarDB数据库专用服务器。 财通证券（601108）发布研报称，在AI时代，对内存带宽与容量的需求持续增加，存在着内存供给与 计算节点需求不匹配、以及内存使用效率较低的痛点。CXL有望通过构建内存池，实现"存算解耦"，渗 透率有望不断提升，随着CXL生态不断完善，适配CXL协议的CPU、服务器的出货量有望逐步提升。 财通证券主要观点如下： 服务器级CPU新增适配CXL协议，生态正不断完善 参考阿里云首款基于CXL2.0Switch技术的PolarDB数据库专用服务器的分布式内存池系统架构，该行认 为，2030年，CXLSwitch、CXLMXC芯片在乐观情况下的需求量有望分别达706/6452万颗。 投资建议：建议关注：澜起科技(CXLMXC芯片供应商)、江波龙（301308）(CXLAIC扩展卡供应商)、 佰维存储(CXL2.0DRAM内存扩展模块供应商)、聚辰股份(CXL模组的VPD芯片供应商)。 CXL可通过构建内存池解决AI时 ...

Core Insights - Intel and Alibaba Cloud announced a series of cloud instances and storage solutions based on the new generation Xeon® 6 processors, addressing the challenges posed by AI scalability on cloud infrastructure [1][9] - High performance, high elasticity, and low total cost of ownership (TCO) are becoming key competitive indicators for global cloud providers [1] Group 1: Cloud Infrastructure Innovations - The introduction of "memory pooling" and flexible architecture is transforming cloud infrastructure, allowing dynamic allocation of resources based on demand [2][6] - Alibaba Cloud has deployed a unified hardware architecture across 29 global regions and 91 availability zones, enabling rapid resource allocation in response to sudden computing demands [4][9] Group 2: AI and Heterogeneous Computing - AI-driven heterogeneous computing is redefining the role of CPUs as central coordinators, with Intel integrating AMX matrix acceleration instruction sets to support various precision calculations [7] - The Xeon® 6 processors can efficiently handle large AI models, demonstrating significant performance improvements in various applications, such as data preprocessing for autonomous driving [7][8] Group 3: Collaboration and Competitive Edge - The stability and engineering support of the collaboration between Intel and Alibaba Cloud are highlighted as foundational elements for their long-term partnership [8] - The optimization of both hardware and software is becoming a key differentiator in the market, with Alibaba Cloud leveraging CXL 2.0 memory pooling technology for enhanced performance [8][9] Group 4: Future Directions - The shift from cloud adoption to intelligent cloud solutions is seen as an inevitable development path, with AI moving into a phase of large-scale application [9][10] - The collaboration between Intel and Alibaba Cloud aims to provide scalable and sustainable pathways for various industries through enhanced hardware performance and optimized software stacks [9][10]

Core Insights - CXL technology is enhancing computing efficiency through storage pooling and high-speed interconnects, with significant implications for AI applications [1] - Major players like NVIDIA and Alibaba Cloud are actively developing CXL capabilities to improve performance and resource utilization in AI systems [2][3] Group 1: CXL Technology Overview - CXL is an open high-speed serial protocol designed to facilitate communication between CPU, memory, and GPU, achieving higher data throughput and lower latency [1] - The technology supports efficient collaboration between accelerators like GPUs and FPGAs with main processors, addressing memory bandwidth bottlenecks and enhancing computational efficiency [1] Group 2: NVIDIA's Strategic Moves - NVIDIA has invested $5 billion in Intel to develop customized x86 CPUs for its AI infrastructure, leveraging Intel's role in the CXL alliance to enhance interoperability between NVLink and CXL technologies [2] - The acquisition of Enfabrica allows NVIDIA to integrate advanced AI interconnect technologies, including low-latency data paths and high-capacity memory support, optimizing GPU and CPU interconnects [2] Group 3: Alibaba Cloud's Innovations - Alibaba Cloud has launched the world's first CXL 2.0 Switch-based PolarDB database server, achieving ultra-low latency and high bandwidth for remote memory access [3] - The server enhances resource utilization and inference throughput by enabling collaborative pathways between GPU, CPU, and shared memory pools, positioning itself as a robust foundation for AI-driven data solutions [3]