![]() |
市場調查報告書
商品編碼
1790275
Chiplet 市場規模、佔有率和趨勢分析報告:按處理器類型、封裝技術、最終用戶產業、地區和細分市場預測,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市場概覽
2024 年全球小晶片市場規模估計為 90.6 億美元,預計到 2033 年將達到 2,235.6 億美元,2025 年至 2033 年的複合年成長率為 43.7%。受人工智慧和高效能運算 (HPC) 工作負載需求激增的推動,該市場正在獲得發展動力,這些工作負載需要可擴展、模組化的處理架構。
單晶片系統晶片(SoC) 的成本和複雜性不斷上升,推動了晶片向基於晶片的分解式設計的轉變,這種設計可以提高產量比率並加快產品上市時間。此外,2.5D/3D 整合和先進封裝技術的快速發展,使得異質整合更加可行且更具成本效益。該市場在邊緣 AI 和物聯網應用領域也擁有巨大潛力,而這些應用的能源效率和客製化至關重要。然而,高昂的設計和檢驗成本是一個障礙,尤其對於研發預算有限的中小企業而言。
對 AI 和 HPC 工作負載的激增需求推動了晶片技術的重大進步,以滿足對可擴展且高效的運算解決方案的需求。醫療保健、汽車和金融等行業擴大使用 AI 進行數據處理,而 HPC 應用則需要強大的運算能力來執行模擬和分析等任務。傳統的單片式晶片難以有效應對這些挑戰,因此靈活、經濟高效且模組化的晶片架構更具吸引力。例如,2025 年 3 月,Accela AI 發布了 Titania,這是一款基於數位記憶體運算 (D-IMC) 架構的可擴展 AI 推理晶片。 Titania 透過 DARE計劃獲得了高達 6,620 萬美元(6,160 萬歐元)的歐盟資助,瞄準邊緣到雲端的 AI 和 HPC 應用,符合歐洲處理器獨立性和超大規模運算戰略。
隨著半導體節點的進步,設計、製造和檢驗大規模單片SoC的成本急劇上升,通常每個晶片的成本高達數億至十億美元以上,尤其是在3奈米和5奈米等尖端製程節點。成本成長的驅動力在於電晶體數量的增加、先進的封裝技術以及為確保產量比率而進行的嚴格測試。相較之下,晶片小片 (Chiplet) 提供了一種模組化方法,可將功能分類為更小、更易於製造的晶粒),從而降低了風險和成本。這種模組化設計還可以透過將缺陷隔離到單一晶片小片而非整個SoC來加快開發週期並提高產量比率,從而為複雜的半導體設計提供更具成本效益和可擴展性的解決方案。
2.5D/3D 和先進封裝技術的快速發展,推動了小晶片市場顯著成長。這些封裝創新使得多個異構晶粒能夠整合到單一封裝中,與傳統的單片式晶片相比,性能、能源效率和尺寸均有提升。矽中介層、穿透矽通孔(TSV) 和基板晶片 (CoWoS) 等技術實現了高密度互連、更低的訊號延遲和更佳的溫度控管。
邊緣人工智慧和物聯網 (IoT) 設備的擴展,源自於對可擴展、低延遲、節能且更靠近資料來源的處理解決方案日益成長的需求。這一趨勢源於汽車和工業自動化應用中智慧型設備、互聯感測器和即時分析的快速普及。為了滿足這一需求,提供模組化和可自訂整合的晶片集線器 (chiplet) 架構已變得至關重要,從而能夠提升邊緣部署的效能並縮短時間。例如,2025 年 1 月,DreamBig 宣布其 MARS 晶片集線器平台的升級,將 3D HBM 堆疊晶片集線器與網路 IO 晶片集線器整合在一起。 DreamBig 與三星代工廠和 Silicon Box 合作,提供高性能人工智慧、資料中心和汽車解決方案,並降低延遲和提高能源效率。這表明基於晶片集的平台是下一代邊緣人工智慧和物聯網創新的關鍵推動因素。
高昂的設計和檢驗成本嚴重限制了Chiplet晶片的市場發展,每個計劃的成本通常高達數百萬美元。將多個晶粒整合到一個整合系統中非常複雜,需要大量的工程資源、全面的測試和徹底的檢驗,以確保各個組件之間的兼容性和可靠性。這些高昂的前期成本增加了財務風險,尤其對於中小企業和新興企業而言,並限制了其更廣泛的應用。此外,儘管Chiplet架構具有明顯的技術優勢,但高昂的成本阻礙了創新和市場擴張。
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: