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市场调查报告书
商品编码
1790275
Chiplet 市场规模、份额和趋势分析报告:按处理器类型、封装技术、最终用户产业、地区和细分市场预测,2025 年至 2033 年Chiplet Market Size, Share & Trends Analysis Report By Processor Type (CPU Chiplets, GPU Chiplets, AI/ML Accelerators), By Packaging Technology (2.5D/3D Packaging, Multi-Chip Module), By End-user Industry, By Region, And Segment Forecasts, 2025 - 2033 |
Chiplet市场概览
2024 年全球小晶片市场规模估计为 90.6 亿美元,预计到 2033 年将达到 2,235.6 亿美元,2025 年至 2033 年的复合年增长率为 43.7%。受人工智慧和高效能运算 (HPC) 工作负载需求激增的推动,该市场正在获得发展动力,这些工作负载需要可扩展、模组化的处理架构。
单晶片系统晶片(SoC) 的成本和复杂性不断上升,推动了晶片向基于晶片的分解式设计的转变,这种设计可以提高产量比率并加快产品上市时间。此外,2.5D/3D 整合和先进封装技术的快速发展,使得异质整合更加可行且更具成本效益。该市场在边缘 AI 和物联网应用领域也拥有巨大潜力,而这些应用的能源效率和客製化至关重要。然而,高昂的设计和检验成本是一个障碍,尤其对于研发预算有限的中小企业而言。
对 AI 和 HPC 工作负载的激增需求推动了晶片技术的重大进步,以满足对可扩展且高效的运算解决方案的需求。医疗保健、汽车和金融等行业越来越多地使用 AI 进行数据处理,而 HPC 应用则需要强大的运算能力来执行模拟和分析等任务。传统的单片式晶片难以有效应对这些挑战,因此灵活、经济高效且模组化的晶片架构更具吸引力。例如,2025 年 3 月,Accela AI 发布了 Titania,这是一款基于数位记忆体运算 (D-IMC) 架构的可扩展 AI 推理晶片。 Titania 透过 DARE计划获得了高达 6,620 万美元(6,160 万欧元)的欧盟资助,瞄准边缘到云端的 AI 和 HPC 应用,符合欧洲处理器独立性和超大规模运算战略。
随着半导体节点的进步,设计、製造和检验大规模单片SoC的成本急剧上升,通常每个晶片的成本高达数亿至十亿美元以上,尤其是在3奈米和5奈米等尖端製程节点。成本成长的驱动力在于电晶体数量的增加、先进的封装技术以及为确保产量比率而进行的严格测试。相较之下,晶片小片 (Chiplet) 提供了一种模组化方法,可将功能划分为更小、更易于製造的晶粒),从而降低了风险和成本。这种模组化设计还可以透过将缺陷隔离到单一晶片小片而非整个SoC来加快开发週期并提高产量比率,从而为复杂的半导体设计提供更具成本效益和可扩展性的解决方案。
2.5D/3D 和先进封装技术的快速发展,推动了小晶片市场显着成长。这些封装创新使得多个异构晶粒能够整合到单一封装中,与传统的单片式晶片相比,性能、能源效率和尺寸均有提升。硅中介层、穿透硅通孔(TSV) 和基板晶片 (CoWoS) 等技术实现了高密度互连、更低的讯号延迟和更佳的温度控管。
边缘人工智慧和物联网 (IoT) 设备的扩展,源自于对可扩展、低延迟、节能且更靠近资料来源的处理解决方案日益增长的需求。这一趋势源于汽车和工业自动化应用中智慧型设备、互联感测器和即时分析的快速普及。为了满足这一需求,提供模组化和可自订整合的晶片集线器 (chiplet) 架构已变得至关重要,从而能够提升边缘部署的效能并缩短时间。例如,2025 年 1 月,DreamBig 宣布其 MARS 晶片集线器平台的升级,将 3D HBM 堆迭晶片集线器与网路 IO 晶片集线器整合在一起。 DreamBig 与三星代工厂和 Silicon Box 合作,提供高性能人工智慧、资料中心和汽车解决方案,并降低延迟和提高能源效率。这表明基于晶片集的平台是下一代边缘人工智慧和物联网创新的关键推动因素。
高昂的设计和检验成本严重限制了Chiplet晶片的市场发展,每个计划的成本通常高达数百万美元。将多个晶粒整合到一个整合系统中非常复杂,需要大量的工程资源、全面的测试和彻底的检验,以确保各个组件之间的兼容性和可靠性。这些高昂的前期成本增加了财务风险,尤其对于中小企业和新兴企业而言,并限制了其更广泛的应用。此外,儘管Chiplet架构具有明显的技术优势,但高昂的成本阻碍了创新和市场扩张。
Chiplet Market Summary
The global chiplet market size was estimated at USD 9.06 billion in 2024 and is projected to reach USD 223.56 billion by 2033, growing at a CAGR of 43.7% from 2025 to 2033. The market is gaining momentum, driven by surging demand for AI and high-performance computing (HPC) workloads, which require scalable, modular processing architectures.
The rising cost and complexity of monolithic system-on-chips (SoCs) are encouraging a shift toward disaggregated chiplet-based designs that improve yield and reduce time-to-market. Additionally, rapid advancements in 2.5D/3D integration and advanced packaging technologies are making heterogeneous integration more feasible and cost-effective. The market also holds significant potential in edge AI and IoT applications, where power efficiency and customization are critical. However, high design and validation costs further act as a restraint, particularly for smaller players with limited R&D budgets.
The surging demand for AI and HPC workloads is driving significant advancements in chiplet technology to meet the need for scalable, efficient computing solutions. Industries across sectors such as healthcare, automotive, and finance increasingly rely on AI for data processing, while HPC applications require enhanced computational power for tasks such as simulations and analytics. Traditional monolithic chips face challenges in addressing these demands efficiently, making modular chiplet architectures more attractive due to their flexibility and cost-effectiveness. For instance, in March 2025, Axelera AI unveiled Titania, a scalable AI inference chiplet based on its Digital In-MemoryComputing (D-IMC) architecture. Supported by up to USD 66.2 million (EUR 61.6 million) in EU funding through the DARE Project, Titania targets edge-to-cloud AI and HPC applications, aligning with Europe's strategy for processor independence and extreme-scale computing.
As semiconductor nodes advance, the expense to design, manufacture, and validate large monolithic SoCs has escalated dramatically, with costs often ranging from hundreds of millions to over a billion dollars per chip, especially at cutting-edge process nodes like 3nm or 5nm. This increase is driven by the need for greater transistor counts, advanced packaging, and rigorous testing to ensure high yields. Chiplets, by contrast, offer a modular approach that divides functionality across smaller, easier-to-manufacture dies, reducing risk and cost. This modularity also accelerates development cycles and enhances yield by isolating defects to individual chiplets rather than the entire SoC, presenting a more cost-effective and scalable solution for complex semiconductor designs.
Rapid advancements in 2.5D/3D and advanced packaging technologies are driving significant growth in the chiplet market. These packaging innovations enable the integration of multiple heterogeneous dies within a single package, enhancing performance, power efficiency, and form factor compared to traditional monolithic chips. Techniques such as silicon interposers, through-silicon vias (TSVs), and chip-on-wafer-on-substrate (CoWoS) allow for high-density interconnects, reduced signal latency, and improved thermal management.
The expansion into Edge AI and IoT devices is being propelled by the increasing need for scalable, low-latency, and energy-efficient processing solutions that can operate closer to data sources. This trend is driven by the rapid adoption of smart devices, connected sensors, and real-time analytics in automotive and industrial automation applications. To address these demands, chiplet architectures offering modular and customizable integration have become essential, enabling improved performance and faster time-to-market for edge deployments. For instance, in January 2025, DreamBig announced advancements in its MARS Chiplet Platform, integrating 3D HBM-stacked Chiplet Hub and Networking IO Chiplets. Partnering with Samsung Foundry and Silicon Box, DreamBig aims to deliver high-performance AI, data center, and automotive solutions with reduced latency and enhanced energy efficiency. This indicates that chiplet-based platforms are critical enablers of next-generation edge AI and IoT innovations.
High design and validation costs significantly restrain the chiplet market, frequently totaling several million USD per project. The complexity of integrating multiple dies into a cohesive system demands extensive engineering resources, comprehensive testing, and thorough validation to ensure compatibility and reliability across diverse components. These substantial upfront expenses increase financial risk, particularly for smaller companies and startups, limiting broader adoption. Also, the high cost barrier slows innovation and market expansion despite the clear technological advantages of chiplet architectures.
Global Chiplet Market Report Segmentation
This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2021 to 2033. For this study, Grand View Research has segmented the global chiplet market report based on processor type, packaging technology, end-user industry, and region: