2025年的市场有两个比较明显的分水岭。第一个是今年四月初，关税事件落地。 如果站在2024年年底展望2025年，最大的风险事件就是关税问题，尤其是2024年10月份美国政府换届选 举之后，市场普遍预期今年可能会出现关税相关的突发性事件。因此，今年一季度市场走势相对震荡、 纠结，直到四月初关税事件落地，大盘出现了较快下跌。 当然，一季度市场也存在一些结构性行情。比如国内的deepseek、机器人等领域，在产业趋势的催化 下，科技成长板块中仍有不少可挖掘的机会。 但四月的关税事件，是影响巨大的分水岭，整个市场迎来了快速下跌。关税落地初期，大家普遍担忧出 口导向型行业，可能会面临较大问题，这种担忧其实是比较正常的。 但后续我们发现，这一轮关税冲突的进程比2018年快很多——双方在几天之内就将关税加到了较高水 平，随后很快进入谈判阶段。短期之内双边仍存在较强的依赖性，双方都有着较深的联系。因此，关税 问题后续进入谈判阶段，双边关系也有所修复和缓和。再叠加二季度英伟达GB200机柜进入加速出货阶 段，所以二季度和三季度，整个A股产业链中，光模块、服务器、光纤光缆等相关公司的股价表现非常 突出。如果大家在二三季度配置了 ...

Summary of Liquid Cooling Technology Trends and Product Pricing Industry Overview - The liquid cooling technology is becoming a necessary choice for high-power data center cooling, driven by strict policy requirements for data center PUE values, which must reach 1.3 for new data centers and below 1.25 for national projects [1][4] - Liquid cooling significantly reduces operational costs, as demonstrated by a client in Beijing who saved 57.5% in annual electricity consumption after upgrading [1][4] Key Points and Arguments 1. **Demand Drivers**: - The demand for liquid cooling technology arises from the need for high-power chip modules (e.g., AI chips, GPUs, ASICs) and high-performance memory and optical modules [3][4] - Domestic GPU manufacturers are increasing density and quantity to compensate for single-chip performance gaps, with companies like Huawei launching systems to compete with NVIDIA's NVL72 architecture [3][12] 2. **Liquid Cooling Solutions**: - Mainstream liquid cooling solutions include direct contact, immersion, and spray cooling, each with its advantages and disadvantages [7][8] - Direct contact cooling is cost-effective, costing approximately 3,000 to 4,000 RMB per kW, while immersion cooling is more efficient but at a higher cost [3][16] 3. **NVIDIA's Product Development**: - NVIDIA's roadmap shows a strong demand for liquid cooling, with power consumption of the Rubin series expected to reach 1,800 watts in 2026 and 3,600 watts in 2027 [1][4][5] - The GB300 liquid cooling system's value increased by approximately 23% compared to the GB200, reaching $85,000 [10] 4. **Market Trends**: - The expected shipment volume for the GB200 cabinet in 2025 is between 25,000 to 30,000 units, primarily to North American cloud providers [2][11] - Domestic liquid cooling manufacturers are gaining recognition and certification from major companies like NVIDIA, with firms like BYD actively participating in the market [21] 5. **Challenges and Innovations**: - The use of fluorinated liquids poses environmental and safety concerns, prompting companies like Intel to explore new mineral oil alternatives [17] - The cost of immersion systems is high due to the need for large quantities of specialized liquids, which limits widespread adoption [18] 6. **Comparative Analysis**: - Compared to NVIDIA, other major players like Intel and AMD are progressing more slowly in high-power, high-density cooling solutions, relying more on traditional air cooling methods [6] 7. **Future Outlook**: - Domestic manufacturers are expected to achieve greater breakthroughs in the future as brand recognition increases and they establish long-term partnerships with leading clients in North America [21] Additional Important Content - The liquid cooling technology is widely applied in memory modules, optical modules, ASIC chips, and switch chips, with increasing power consumption necessitating these solutions [15] - The market share of traditional cooling methods remains significant, accounting for 70% to 80% of the market, due to lower modification costs and higher power density [18][20]

Core Viewpoint - HUT8's Q2 2025 report highlights the advancement of liquid cooling systems, bridging the gap between traditional air-cooled ASIC infrastructure and liquid-cooled GPU infrastructure, with increasing cabinet density and market potential for liquid cooling solutions [1] Group 1: Market Trends - The trend towards liquid cooling has been initiated by the increasing shipment of NVIDIA's GB200 cabinets, which feature cold plate liquid cooling design, marking the beginning of a new era in liquid cooling [2] - The growth of the liquid cooling market is driven by two main factors: the rising power consumption of GPU chip designs necessitating upgraded cooling solutions, and the increasing integration demands of data centers [2][3] Group 2: Industry Dynamics - The integration of data centers is pushing the need for advanced cooling solutions, as traditional air cooling cannot meet the economic and integration requirements of high-performance computing centers [3] - The future of the liquid cooling industry is clear, with a shift from traditional air cooling to liquid cooling solutions, including cold plate, spray, and immersion cooling systems [3] Group 3: Investment Opportunities - Companies to watch in the liquid cooling space include Invec (002837.SZ), Kehua Data (002335.SZ), Wangsu Science & Technology (300017.SZ), Yimikang (300249.SZ), Shenling Environment (301018.SZ), and Gaolan Co. (300499.SZ) [3]

Core Viewpoint - Huawei's Ascend 384 Super Node has demonstrated performance that surpasses NVIDIA's products in certain aspects, indicating a significant advancement in domestic AI chip capabilities [2][3]. Group 1: Product Overview - Ascend is an AI chip developed by Huawei, specifically designed for AI tasks as an NPU, distinguishing it from traditional GPUs and CPUs [4]. - The main product, Ascend 910, has transitioned from being a backup option to a primary solution for training large models due to restrictions on high-end chips from NVIDIA and AMD [4][6]. Group 2: Performance Metrics - In recent developments, Huawei has successfully trained large models using Ascend chips, achieving a dense model with 135 billion parameters and a MoE model with 718 billion parameters [6]. - The key performance indicator, MFU (Modeling Function Utilization), reached over 50% for the dense model and 41% for the MoE model, indicating efficient utilization of computational resources [9]. Group 3: Competitive Analysis - In a direct comparison with NVIDIA's H100 and H800 during the deployment of large models, Ascend demonstrated comparable performance, achieving the best utilization rate in the competition [10]. - Although a single Ascend chip's performance is only one-third of NVIDIA's Blackwell, the 384 Super Node configuration, which utilizes five times the number of chips, results in an overall computational power that exceeds NVIDIA's GB200 [10].