Core Insights - The rapid development of large models driven by AI demands significant computational power, leading to the emergence of the "SuperPod" as a key solution for efficient AI training [1][2] - The transition from traditional computing architectures to SuperPod technology signifies a shift in the AI infrastructure competition from isolated breakthroughs to a system-level ecosystem [1][5] Industry Trends - The SuperPod, proposed by NVIDIA, represents a Scale Up solution that integrates GPU resources to create a low-latency, high-bandwidth computing entity, enhancing performance and energy efficiency [2][4] - The traditional air-cooled AI servers are reaching their power density limits, prompting the adoption of advanced cooling technologies like liquid cooling in SuperPod designs [2][5] Market Outlook - The market for SuperPods is viewed positively, with many domestic and international server manufacturers selecting it as the next-generation solution, primarily utilizing copper connections [2][4] - Major Chinese tech companies, including Huawei and Xizhi Technology, are actively developing SuperPod solutions, showcasing significant advancements in AI computing capabilities [5][6] Technological Developments - The ETH-X open standard project, led by the Open Data Center Committee, aims to establish a framework for SuperPod architecture, combining Scale Up and Scale Out networking strategies [4] - Companies like Moer Thread are building comprehensive AI computing product lines, emphasizing the need for efficient collaboration among large-scale clusters to enhance AI training infrastructure [6]

Investment Rating - The report initiates coverage on Huafeng Technology with an "Accumulate" rating and a target price of 59.86 RMB per share, based on a 75x PE valuation for 2026 [6][5]. Core Views - Huafeng Technology is positioned as a leader in high-speed connectors in China, benefiting from the increasing demand for short-distance interconnects driven by AI and domestic computing power expansion. The company is gradually releasing production capacity for high-speed line modules developed for major clients, which is expected to lead to sustained performance growth [1][15]. - The report highlights the growth potential in the communications sector, driven by the demand for high-speed interconnects in AI clusters, with a projected market size of 24.1 billion RMB by 2029, growing at a CAGR of 45% from 2025 to 2029 [2][16]. - In the defense sector, the company is expected to benefit from the "14th Five-Year Plan" military budget increase, with a projected 7.2% year-on-year growth in military spending in 2025, enhancing the outlook for defense orders [3][17]. - The industrial segment is anticipated to see stable growth due to the rising penetration of new energy vehicles and the trend towards 800V high-voltage systems, with the high-voltage connector market projected to reach 33.7 billion RMB by 2026, growing at a CAGR of 42% from 2022 to 2026 [3][18]. Summary by Sections Company Overview - Established in 1958, Huafeng Technology is a leading supplier of optical connectors and interconnection solutions in China, focusing on high-speed connectors and system interconnection solutions across communications, defense, and industrial sectors. The company has achieved significant milestones in developing high-speed backplane connectors, breaking the monopoly of foreign leaders in the domestic market [15][25]. Communications Sector - The company is deeply collaborating with major clients to meet the growing demand for high-speed interconnects in AI clusters. The increasing GPU computing power and bandwidth requirements are driving the need for higher signal transmission rates. The domestic high-speed backplane connector market is projected to reach 24.1 billion RMB by 2029, with a CAGR of 45% from 2025 to 2029 [2][16]. Defense Sector - The defense segment focuses on defense connectors and related system interconnection products. With the military budget expected to reach 1.78 trillion RMB in 2025, a 7.2% increase year-on-year, the company is well-positioned to capture growth in defense orders [3][17]. Industrial Sector - The industrial connectors primarily serve the new energy vehicle and rail transportation sectors. The market for high-voltage connectors in new energy vehicles is projected to reach 33.7 billion RMB by 2026, with a CAGR of 42% from 2022 to 2026. The company is also expanding its applications in drone and eVTOL systems [3][18].

Core Viewpoint - The development of models has shifted from early algorithm optimization to deep innovation at the system engineering level, transitioning from a digital era of bit traffic to a Token economy, with daily Token consumption in China rising from hundreds of billions to tens of trillions [1] Group 1: Model Optimization - Huawei has made significant optimizations for DeepSeek, focusing on three main areas to enhance compatibility and support for enterprise applications [3] - The pre-training aspect includes the implementation of DualPipe technology, which has been improved to minimize static memory usage through the introduction of the DualPipe-V solution [6] - At the operator level, Huawei has enhanced execution efficiency with the MRN PO fusion operator and optimized low-latency communication [7] Group 2: System Architecture - Huawei has developed a new architecture for inference called the "super node" architecture, which interconnects multiple GPUs to reduce communication latency and improve training throughput [14] - The Atlas 900 A3 SuperCluster has been designed to enhance cluster computing efficiency and reliability, achieving a training efficiency increase of 2.7 times [15] - The OmniPlacement algorithm has been introduced to optimize resource utilization by dynamically adapting to expert activation data, improving throughput by 10% [19] Group 3: Load Balancing and Efficiency - Huawei has implemented a large-scale expert parallel (large EP) strategy to enhance inference efficiency, achieving a nearly 20-fold increase in the past two months [17] - The company has developed dynamic priority adjustment and communication optimization strategies to address load balancing challenges in expert parallelism [20]

Core Insights - The rapid growth in demand for AI computing power has outpaced the capabilities of traditional computing architectures, necessitating the development of new solutions like the super node architecture [1] - Huawei Cloud's CloudMatrix 384 super node addresses key technical challenges in AI computing, including communication efficiency, memory limitations, and reliability, achieving a computing power scale of up to 300 Pflops, surpassing NVIDIA's NVL72 by 67% [1] - The introduction of distributed inference platforms and innovative technologies such as Elastic Memory Storage (EMS) significantly enhances resource utilization and performance, reducing latency and improving fault detection rates [2] Group 1 - The demand for AI computing power has increased by 10,000 times, while hardware capabilities have only improved by 40 times in the last eight years [1] - The CloudMatrix 384 super node connects 384 cards into a single super cloud server using a new high-speed interconnect bus [1] - The super node features six technical advantages, including MoE affinity and high reliability [1] Group 2 - The distributed inference platform allows for efficient distributed inference with one card acting as one expert, significantly improving MoE computation and communication efficiency [2] - The MatrixLink service consists of two network layers, enabling high-speed interconnection within the super node and low latency communication [2] - The EMS technology decouples memory from computing power, enhancing resource utilization and reducing the first token latency by up to 80% [2]