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市場調查報告書
商品編碼
2106720

下一代晶片和先進封裝架構：重新定義人工智慧和高效能運算的效能和可擴展性

Next-Generation Chiplet and Advanced Packaging Architectures: Redefining Performance and Scalability in AI and HPC
出版日期: | 出版商: Frost & Sullivan | 英文 61 Pages | 商品交期: 最快1-2個工作天內

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簡介目錄

本研究並非對整個封裝市場進行全面概述，而是著重探討下一代晶片架構、高頻寬記憶體 (HBM) 以及諸如 2.5D/3D 整合和扇出型晶圓級封裝等先進封裝技術如何推動人工智慧 (AI) 和高效能運算 (HPC)系統結構的新浪潮。研究分析了基於晶片的分區、開放的晶片間互連標準以及緊密耦合的 HBM 整合如何實現更高的頻寬、更高的良率、更低的設計複雜性以及可擴展的模組化平台，從而克服傳統單晶片 AI/HPC 處理器和加速器的物理和經濟限制。具體而言，本研究檢驗了這些技術對 AI 加速器、GPU、資料中心和雲端基礎設施、網路以及邊緣系統的架構和發展藍圖影響，並評估了商業化趨勢以及代工廠、整合元件製造商 (IDM)、無晶圓廠供應商、外包半導體組裝測試 (OSAT) 和電子設計自動化 (EDA) 供應商在建構以新晶片為中心的晶片時所扮演的角色。此外，我們也評估了影響這些 AI/HPC 架構的關鍵機會和限制因素。這些因素包括晶片間的互通性和標準、封裝能力、人工智慧級功率密度下的散熱和電源管理、測試和可靠性複雜性、成本效益、供應鏈依賴性，以及影響先進人工智慧/高效能運算晶片製造和部署地點及方式的地緣政治因素。同時，我們也關注未來的技術藍圖和生態系統主導的創新趨勢。

分析和細分範圍

  • 分析範圍
  • 分割

策略要務

  • 為什麼成長變得越來越困難？策略要務八要素™：阻礙成長的因素
  • The Strategic Imperative 8 TM
  • 半導體產業三大策略要務的影響
  • 成長機會驅動Growth Pipeline Engine™
  • 調查方法

成長機會分析

  • 成長促進因素
  • 抑制生長的因素

技術概述

  • 技術概述 - 晶片組和先進封裝
  • 實現人工智慧記憶體整合的封裝方法
  • 晶片和封裝領域的最新技術趨勢
  • 塑造晶片和先進封裝價值鏈的策略關係
  • Chiplet生態系的技術組成部分
  • 主要特點、價值提案與挑戰
  • 挑戰、困難和戰略考量
  • 架構優勢和整合複雜性
  • 人工智慧和高效能運算系統的關鍵特性

戰略意義與技術整合

  • 戰略觀點及其影響
  • 塑造人工智慧和高效能運算的技術融合

主要研發與創新主題

  • 主要研發與創新主題
  • 對相關人員的策略意義
  • 針對晶片主導運算生態系統的策略建議與願景

專利和資金籌措趨勢評估

  • 晶片組和先進封裝領域的專利申請趨勢
  • 近期公共資金投入與先進包裝領域的生態系統建設舉措
  • Chiplet生態系的發展
  • 策略藍圖—技術應用與新趨勢

產業應用案例

  • 案例研究1 - NVIDIA Blackwell GB200 架構：基於晶片組的 AI 加速器領域的領導者
  • 案例研究2 - AMD 第四代 EPYC“Genoa”：面向人工智慧和高效能運算的晶片組 CPU 平台
  • 案例研究3 - 英特爾 Max 系列資料中心 GPU：異質 AI/HPC 封裝領域的領導者

未來展望與戰略洞察

  • 未來展望（未來3-5年）－市場及擴散狀況
  • 先進晶片和3D整合技術演進藍圖
  • 關於促進晶片組、HBM 和 2.5D/3D 整合的策略建議

成長機會整體情況

  • 成長機會 1：基於 UCIe 的多廠商晶片平台，適用於人工智慧和高效能運算
  • 成長機會 2：相容於 HBM4 的 2.5D/3D 封裝平台，適用於記憶體受限的 AI 工作負載
  • 成長機會 3：節能型分散式 AI 架構的光學 UCIe 晶片

附錄

  • 技術成熟度等級（TRL）：說明

未來計劃

  • 成長機會的益處和影響
  • 未來計劃
  • 免責聲明
簡介目錄
Product Code: DB8E

This study focuses on how next-generation chiplet architectures, high-bandwidth memory (HBM), and advanced packaging technologies such as 2.5D/3D integration and fan-out wafer-level packaging are enabling the next wave of AI and high-performance computing (HPC) system architectures, rather than providing a broad packaging market overview. It analyzes how chiplet-based partitioning, open die-to-die interconnect standards, and tightly coupled HBM integration unlock higher bandwidth, improved yield, reduced design complexity, and scalable, modular platforms that overcome the physical and economic limits of traditional monolithic AI/HPC processors and accelerators. The study specifically examines architecture and roadmap implications for AI accelerators, GPUs, data-center and cloud infrastructure, networking and edge systems that are adopting these technologies, and evaluates commercialization trends and ecosystem roles across foundries, IDMs, fabless vendors, OSATs, and EDA providers as they build chiplet-centric AI/HPC platforms. It further assesses the key opportunities and constraints shaping these AI/HPC architectures—including interoperability of chiplets and standards, packaging capacity, thermal and power management at AI-class power densities, test and reliability complexity, cost efficiency, supply-chain dependencies, and geopolitical factors that influence where and how advanced AI/HPC silicon can be manufactured and deployed, while highlighting future technology roadmaps and ecosystem-driven innovation trends.

Scope and Segmentation

  • Scope of Analysis
  • Segmentation

Strategic Imperatives

  • Why Is It Increasingly Difficult to Grow? The Strategic Imperative 8TM: Factors Creating Pressure on Growth
  • The Strategic Imperative 8TM
  • The Impact of the Top 3 Strategic Imperatives on the Semiconductor Industry
  • Growth Opportunities Fuel the Growth Pipeline EngineTM
  • Research Methodology

Growth Opportunity Analysis

  • Growth Drivers
  • Growth Restraints

Technology Overview

  • Technology Overview-Chiplets and Advanced Packaging
  • Packaging Approaches Enabling AI Memory Integration
  • Recent Technology Developments in Chiplet and Packaging
  • Strategic Relationships Shaping the Chiplet and Advanced Packaging Value Chain
  • Technological Components of the Chiplet Ecosystem
  • Essential Features, Value Propositions, and Hurdles
  • Hurdles, Challenges, and Strategic Considerations
  • Architecture Benefits and Integration Complexities
  • Key Capabilities for AI and HPC Systems

Strategic Implications and Technology Convergence

  • Strategic Viewpoint and Implications
  • Technology Convergence Shaping AI & HPC

Key R&D Innovation Themes

  • Key R&D Innovation Themes
  • Strategic Implications for Stakeholders
  • Strategic Recommendations and Vision for a Chiplet-Driven Computing Ecosystem

Patent and Funding Trends Assessment

  • Patent Filing Trends in Chiplets & Advanced Packaging
  • Recent Public Funding and Ecosystem Initiatives in Advanced Packaging
  • Chiplet Ecosystem Development
  • Strategic Roadmap-Technology Adoption and Emerging Trends

Industry Use Cases

  • Case Study 1-NVIDIA Blackwell GB200 Architecture: Chiplet-Based AI Accelerator Leadership
  • Case Study 2-AMD 4th Gen EPYC "Genoa": Chiplet CPU Platform for AI and HPC
  • Case Study 3-Intel Data Center GPU Max Series: Heterogeneous AI/HPC Packaging Leadership

Future Outlook and Strategic Insights

  • Future Outlook (3–5 Year Horizon)-Market and Adoption
  • Technology Evolution Roadmap for Advanced Chiplet and 3D Integration
  • Strategic Recommendations for Advancing Chiplet, HBM, and 2.5D/3D Integration

Growth Opportunities Universe

  • Growth Opportunity 1: UCIe-Based Multi-Vendor Chiplet Platforms for AI & HPC
  • Growth Opportunity 2: HBM4-Ready 2.5D/3D Packaging Platforms for Memory-Bound AI Workloads
  • Growth Opportunity 3: Optical UCIe Chiplets for Energy-Efficient Disaggregated AI Fabrics

Appendix

  • Technology Readiness Levels (TRL): Explanation

Next Steps

  • Benefits and Impacts of Growth Opportunities
  • Next Steps
  • Legal Disclaimer