Core Insights - The article highlights the growth of storage revenue in Q3 2025, primarily driven by sales of mid-range all-flash arrays, with Pure Storage showing the fastest revenue growth among the top five vendors [2]. Market Overview - The global External OEM Enterprise Storage Systems (ESS) market grew by only 2.1% year-over-year, reaching approximately $8 billion, with the top five vendors holding a combined market share of 56.5% [2]. - Dell leads the market with a 22.7% share, generating $1.812 billion in revenue, but experienced a 49% decline year-over-year [2]. - Huawei ranks second with a 12% market share and $953 million in revenue, marking a 9.5% increase, outperforming the market average [2]. - NetApp, in third place, reported a revenue of $750.16 million, growing by 2.8% due to its all-flash array sales [2]. - Pure Storage achieved a revenue of $539.22 million, reflecting a significant growth of 15.5% year-over-year [2]. - HPE saw a revenue decline of 7.5%, totaling $450.23 million [2]. Product Segment Performance - The overall storage market growth rate from Q3 2024 to Q3 2025 was 2.1% [2]. - All-flash arrays experienced a robust growth rate of 17.6%, while hybrid flash disk arrays and disk drive arrays saw declines of 9.8% and 6.3%, respectively [3][4]. Geographic Performance - The U.S. market faced a decline attributed to weak OEM performance, with a notable drop of 9.9% [7]. - Other regions showed varying growth rates, with Japan at 14.4%, Canada at 12.6%, and Europe, the Middle East, and Africa at 10.5% [7]. Future Outlook - IDC anticipates that the demand for specialized and efficient enterprise storage systems will increase due to the penetration of AI applications in enterprise data centers [5]. - The need for flash storage is expected to grow continuously to support AI-related projects, including training and inference [5].

来源：内容转自小米技术，谢谢。 近日， 第71届国际电子器件大会 IEDM 2025 （International Electron Devices Meeting，简称 IEDM）在美国旧 金山召开。 IEDM 是 全球半导体与电子器件领域最具权威和影响力的顶级会议之一， 以其严苛的评审标准与前瞻性的技 术视野，被誉为"电子器件突破性技术的风向标"和"器件的奥林匹克盛会"，在国际半导体技术界享有很高的学 术地位和广泛的影响力。 会议始于1955年，距今已有七十余年历史，是报告半导体和电子器件技术、设计、制造、物理和建模等领域的 关键技术突破的世界顶级论坛，同时它也是国际著名高校、研发机构和 Intel、 TSMC、三星、 IBM 等发布先 进技术和最新进展的重要窗口和平台。 每一年的 IEDM 盛会，都是全球半导体行业关注的焦点。 本次会议以100 YEARS of FETs: SHAPING the FUTURE of DEVICE INNOVATIONS 为主题，于2025年12月6日至10日召开。 论文简介 入选论文题目：《First Integration of GaN Low-Voltage PA ...

Core Viewpoint - PowerLattice has developed a new chip technology that significantly reduces power consumption in data centers by up to 50% and doubles performance per watt, addressing the growing energy demands of AI data centers [2][5][7]. Group 1: Power Consumption and Efficiency - Traditional systems convert AC power from the grid to DC power for AI chips, which then requires further conversion to low-voltage DC for GPUs, leading to energy loss due to long-distance current flow [4]. - PowerLattice's innovation involves reducing voltage within a few millimeters of the processor, minimizing power loss by shortening the distance high current must travel [5][6]. - The new micro-power chips designed by PowerLattice are significantly smaller than current voltage regulators, allowing for closer installation to processors and freeing up space for other components [6]. Group 2: Technology and Design - PowerLattice utilizes a special magnetic alloy to manufacture inductors, enabling efficient operation at high frequencies, which allows for smaller inductors that require less material [6]. - The final microchip design is less than one-twentieth the area of current voltage regulators and only 100 micrometers thick, comparable to the thickness of a human hair [6]. Group 3: Market Position and Competition - PowerLattice is currently conducting reliability and validation tests, with plans to release its first product in two years, facing competition from established companies like Intel, which is also developing integrated voltage regulators [9]. - Despite the competition, there is a trend towards heterogeneous integration, allowing customers to mix components from different companies for better system optimization, which may benefit smaller firms like PowerLattice [9][10].

Core Viewpoint - The article discusses the differences between chiplets and soft IP, emphasizing that while both can accelerate time-to-market, they serve different needs and come with distinct challenges in design, integration, and testing [2][20]. Group 1: Chiplet vs Soft IP - Chiplets can be seen as a new type of semiconductor IP, but they differ significantly from the current IP licensing ecosystem, particularly in design integration and verification [2][20]. - Chiplets can be either custom-designed or off-the-shelf, with two camps emerging: one that designs its own chiplets and another that sources components externally [2][20]. - The market for chiplets will coexist with custom chips, with many IP modules becoming off-the-shelf chips that system vendors can mix and match [2][20]. Group 2: Customization and Functionality - The key difference between chiplets and soft IP lies in their customizability; soft IP offers high configurability, while chiplets have fixed functionalities [6][20]. - Chiplets require careful management of startup processes and debugging, which are less of a concern with soft IP [6][20]. - The physical integration of chiplets presents unique challenges, such as managing signal integrity and power distribution, which are not as critical in soft IP [24][20]. Group 3: Testing and Supply Chain - Testing chiplets is more complex than testing soft IP, as chiplets are typically tested independently by suppliers, requiring integration into the overall system testing process [20][20]. - The supply chain for chiplets is more traditional and complex, closely tied to manufacturing nodes and foundries, which increases dependency on suppliers [20][20]. - Built-in self-test (BiST) technology is expected to become more prevalent to address the transparency issues associated with chiplets [22][20]. Group 4: Security and Integration Challenges - Security considerations for chiplets are more challenging than for soft IP, as chiplets have a larger attack surface due to their interconnections and shared resources [20][20]. - Each chip in a multi-chip system must coordinate its security measures, which can lead to inefficiencies if not managed properly [20][20]. - The physical design of chiplets must account for thermal management and signal integrity, requiring advanced modeling tools that go beyond those used for soft IP [24][20].

Core Viewpoint - The semiconductor market is expected to reach a record revenue of over $800 billion by 2025, driven by strong demand in artificial intelligence and memory products, with a more balanced growth across various segments compared to previous years [2][6][9]. Group 1: Market Performance - In Q3 2025, the semiconductor market revenue reached $216.3 billion, marking a historic high with a quarter-on-quarter growth of 14.5%, the first time the market surpassed $200 billion in a single quarter [2][6]. - The average growth rate for Q3 historically is slightly above 7%, while the market had previously anticipated a growth of about 5% for Q3 2025, indicating a significant outperformance [6][9]. - The overall semiconductor revenue for 2024 is projected to exceed $650 billion, with an annual growth rate of over 20%, although this growth is uneven across the industry [3][9]. Group 2: Segment Contributions - Demand for artificial intelligence and memory products continues to be robust, with both segments outpacing overall market growth [6][10]. - In Q3 2025, the revenue growth exceeded 14% across the semiconductor market, and even when excluding NVIDIA and memory chips, the revenue still grew by over 9% [3][9]. - The top four semiconductor companies by revenue in Q3 2025 were NVIDIA and the three major memory suppliers: Samsung, SK Hynix, and Micron, highlighting the dominance of AI accelerators and advanced memory technologies [3][10][11]. Group 3: Future Outlook - The semiconductor industry is expected to maintain strong momentum into Q4 2025, with predictions of record revenues continuing into the following year [4][11]. - The growth trend for 2025 indicates a shift towards broader industry expansion rather than reliance on a few high-growth segments, with an expected annual growth rate of approximately 9% even when excluding NVIDIA and memory products [3][9].

公众号记得加星标⭐️，第一时间看推送不会错过。 在刚刚结束的IEDM 2025上，台积电首次证实了采用下一代晶体管技术——互补场效应晶体管 （CFET）的集成电路的运行情况。 根据IEDM 官方此前的预告，台积电在本届大会宣布两项了重要里程碑：首款全功能 101 级 3D 单 片互补场效应晶体管 (CFET) 环形振荡器 (RO)以及全球最小的 6T SRAM 位单元，该位单元同时提 供高密度和高电流设计。 据介绍，基于先前基于纳米片的单片 CFET 工艺架构，台积电研究人员引入了新的集成特性，进一 步将栅极间距缩小至 48nm 以下，并在相邻 FET 之间采用纳米片切割隔离 (NCI) 技术，以及在 6T SRAM 位单元内采用对接接触 (BCT) 互连技术实现反相器的交叉耦合。电学特性分析对比了两种环 形振荡器布局，重点展示了 6T 位单元对性能以及稳健 SRAM 器件指标的影响。 这些进展标志着 CFET 开发的关键性转变，从器件级优化迈向电路级集成。 台积电新进展 CFET 是一种通过垂直堆叠 n 沟道 FET 和 p 沟道 FET（CMOS 器件的基本组件）来提高晶体管密 度的技术，理论上与目前最先 ...

Core Viewpoint - Rivian Automotive has launched its first custom computer chip for autonomous driving, named Autonomy+, which is priced significantly lower than Tesla's offerings, marking a pivotal moment in the company's journey towards achieving Level 4 autonomous driving [2][5][6]. Group 1: Chip Development and Technology - Rivian's core technology roadmap focuses on transitioning to in-house developed chips designed for vision-centric physical AI, with the first generation being a custom 5nm processor [4]. - The new chip, capable of executing 16 trillion operations per second (TOPS) in a dual-chip configuration, integrates processing and storage into a single multi-chip module, enhancing efficiency and performance [4]. - Rivian claims its chip can process 5 billion pixels of camera data per second and utilizes RivLink technology for low-latency interconnectivity, which increases processing capabilities [4][6]. Group 2: Competitive Positioning - Rivian's move to develop its own chips aligns it with Tesla, which is also pursuing in-house chip development for autonomous vehicles, while other manufacturers increasingly rely on Nvidia [5][6]. - The company plans to integrate LiDAR into its upcoming R2 model to improve redundancy and real-time driving performance, contrasting with Tesla's approach of not using LiDAR [5][8]. Group 3: Product Offerings and Pricing - The Autonomy+ driving assistance suite is priced at $2,500 for a one-time payment or $49.99 per month, significantly lower than Tesla's $8,000 full self-driving system [7][8]. - Rivian aims to launch a "no-look" driving feature by 2026, leveraging its advancements in chip technology and AI models [8]. Group 4: Long-term Goals and Market Strategy - Rivian's long-term goal is to achieve Level 4 autonomous driving, allowing vehicles to operate without human intervention under specific conditions [6]. - The company emphasizes deep vertical integration as a key strategy to reduce costs by eliminating supplier margins and customizing components according to its needs [6].

公众号记得加星标⭐️，第一时间看推送不会错过。 光子平台、存储架构和光开关领域的最新进展表明，光计算领域正在不断发展。 世界各地的研究团队正在加速推进光子计算的发展，过去一年发表的研究成果涵盖器件、存储器、开 关、特征提取和高速调制等领域。近期研究成果包括硅锗光子学、集成光存储器、单光子开关、光学 衍射引擎以及400 Gb/s电吸收调制器等，每一项都旨在降低数据密集型系统的延迟或提高带宽。 综合来看，这些项目展现了光学技术如何能够支持未来的人工智能、高性能计算和实时决策工作负 载，同时保持与大规模半导体制造的兼容性。 01 IHP发布搭载140 GHz调制器的SiGe光子平台 IHP 推出了其所谓的首个硅锗光子平台，该平台能够支持带宽远超当前硅光子极限的电吸收调制器和 光电二极管，并报告称其调制器的外推 3 dB 截止频率为 140 GHz，鳍式光电二极管的外推 3 dB 截 止频率高达 200 GHz。 威斯康星大学麦迪逊分校的研究人员开发并测试了一种完全由商用硅光子代工厂现有组件构建的集成 光子存储芯片，为可扩展的光计算硬件提供了一条切实可行的途径。 该器件采用由光电二极管、微环谐振器和光波导构成的"交叉 ...

Core Viewpoint - The article emphasizes the rising importance of compound semiconductors, particularly VCSEL technology, in the context of the smart era driven by AI and intelligent vehicles, highlighting the shift from traditional silicon chips to these advanced materials [1][2][4]. Group 1: VCSEL Technology - VCSEL (Vertical Cavity Surface Emitting Laser) is a semiconductor laser that emits light vertically, offering advantages such as low threshold current, stable single-wavelength operation, and low manufacturing costs [3][4]. - The VCSEL market is projected to reach $1.4 billion by 2028, driven by demand from data centers and smart vehicles [4]. - The introduction of VCSEL in Apple's Face ID technology in 2017 significantly boosted its visibility and application in consumer electronics [3][4]. Group 2: China's Semiconductor Industry - Chinese companies are now leading the main application areas for VCSEL, such as optical modules and lidar, marking a shift from previous reliance on foreign giants [6][8]. - The article discusses the transition of China's semiconductor industry from imitation to innovation, with a focus on achieving original technology breakthroughs [6][8]. - The establishment of local VCSEL production capabilities is deemed essential for China's semiconductor self-sufficiency [6][8]. Group 3: Industry Trends and Future Outlook - The current AI infrastructure market is characterized by rapid changes, with significant growth expected in server and storage infrastructure spending, projected to reach $758 billion by 2029 [10]. - The industry is moving towards collaborative designs among multiple manufacturers, indicating a shift from isolated chip development to a more integrated ecosystem [12]. - The company aims to play a significant role in the "optical interconnect" and "optical sensing" markets, positioning itself as a key player in the global semiconductor landscape [12].

Core Viewpoint - Broadcom has reported impressive financial performance for the fourth quarter, driven by strong demand for artificial intelligence processors, with a significant revenue increase of 28% to $18.02 billion, surpassing expectations [2] Financial Performance - The company's earnings per share before stock compensation costs were $1.95, exceeding analyst expectations of $1.86 [2] - Net profit for the quarter increased by 97% year-over-year to $8.51 billion, compared to $4.32 billion in the same period last year [2] - Broadcom forecasts revenue of approximately $19.1 billion for the upcoming quarter, higher than Wall Street's estimate of $18.3 billion [2] AI Chip Demand - AI chip sales surged by 74%, contributing an additional $8.2 billion in sales [2] - The company has secured its fifth custom chip client, with a $1 billion order expected to be delivered by the end of 2026 [3] - Broadcom's backlog for custom AI chips and other data center components totals $73 billion, with plans to convert these orders into revenue within 18 months [5] Market Position and Competition - Broadcom is positioned as a major beneficiary of the AI industry's growth, with its stock rising over 75% this year, despite a recent drop of over 6% post-earnings report [3] - The custom AI chip market is expected to grow significantly, with projections of $1 trillion in annual growth over the next few years, and Broadcom is anticipated to capture 70% to 80% of the custom chip market share [6] - The company's semiconductor solutions segment reported AI chip sales of $11.07 billion, a 22% year-over-year increase [6]