시장보고서
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2060316

CPO(Co-Packaged Optics) 시장(2027-2037년)

The Global Co-Packaged Optics Market 2027-2037

발행일: | 리서치사: 구분자 Future Markets, Inc. | 페이지 정보: 영문 470 Pages, 240 Tables, 50 Figures | 배송안내 : 즉시배송

    
    
    



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※ 본 상품은 영문 자료로 한글과 영문 목차에 불일치하는 내용이 있을 경우 영문을 우선합니다. 정확한 검토를 위해 영문 목차를 참고해주시기 바랍니다.

CPO(Co-Packaged Optics)는 지난 수십 년 동안 광 인터커넥트에 대한 가장 근본적인 재구상을 구현한 것으로, 광 엔진을 스위치의 전면판에서 스위치나 가속기의 실리콘 바로 옆으로 배치하는 기술입니다. 고속 전기 경로를 센티미터 단위에서 밀리미터 단위로 단축함으로써, CPO는 ‘상호 연결의 장벽’을 극복합니다. 이 ‘벽’이란 스위치에서는 대략 2년마다 두 배로 증가하고, 모델 파라미터에서는 더욱 급속히 증가하는 AI의 대역폭 수요와, 레인당 광속(약 4년마다 두 배로 증가할 뿐) 사이에 벌어지는 격차를 의미합니다. 이 기술은 플러그인 방식의 트랜시버에 비해 전력 효율이 대폭 개선되고 지연 시간도 크게 단축되므로, AI 데이터센터의 전력, 밀도 및 비트당 비용과 같은 제약 사항을 해결합니다.

시장은 스케일아웃형 CPO(네트워크 스위치용 광 엔진)와 스케일업형 CPO(GPU 및 AI 가속기용 광 I/O)로 나뉘어 있으며, 2020년대 말 무렵에는 스케일업형이 스케일아웃형을 추월한 뒤, 이후 주요 부문으로 자리 잡을 전망입니다. 이 기술은 플러그인 방식 모듈이 물리적 및 경제적 한계에 도달한 최고 대역폭의 네트워크 스위치에서 시작되어, 차세대 GPU 플랫폼의 보급에 따라 AI 가속기의 광 I/O로 확대될 것입니다.

최근 동향은 결정적인 국면을 맞이하고 있습니다. NVIDIA는 Coherent 및 Lumentum에 대한 대규모 전략적 투자를 통해 레이저 공급망 진출을 확고히 하고, Quantum-X 및 Spectrum-X Photonics CPO 스위치의 양산 단계로 넘어갔습니다. TSMC는 COUPE 로드맵을 확정했습니다. 이는 2026년에 양산을 시작할 예정인 200Gbps 마이크로링 변조기로, 2030년까지 4Tbps/mm의 대역폭 밀도를 목표로 하고 있습니다. 한편, GlobalFoundries는 OCI-MSA를 준수하는 SCALE 플랫폼을 발표하고, 8λ 및 16λ에 대한 실증 테스트를 진행했습니다. Ayar Labs는 시리즈 E 자금 조달을 마친 후 NVIDIA의 NVLink Fusion 생태계에 합류했습니다. Marvell은 Celestial AI 인수를 완료했으며, Fabrinet은 Raytek Semiconductor에 투자했습니다. OCI-MSA(AMD, Broadcom, Meta, Microsoft, NVIDIA, OpenAI)가 사실상 스케일업용 상호 연결 표준으로 부상했습니다.

이러한 추세와는 달리, NVIDIA의 CPO(칩 온 패키지) 대량 생산은 시스템 엔지니어링상의 이유(유지보수성, 신뢰성, 제조·테스트 수율)으로 인해 2028년 2029년으로 연기될 가능성이 있으며, 이에 따라 니어 패키지 옵틱스(NPO)가 현실적인 중간 대안으로 주목받으면서 광통신 관련주 전반에 걸쳐 급격한 매도 주문이 쇄도했습니다. 연간 약 100만 대에서 수천만 대로 테스트 및 생산 규모를 확대하는 것은 현재 제약 요인으로 간주되고 있으며, 자동화된 전기·광 듀얼 도메인 테스트 셀과 표준화된 광 커넥터가 요구되고 있습니다. CPO(코패키지드 옵틱스)의 발전 방향은 이미 정해졌다는 것이 일반적인 견해이며, 그 도입 속도가 주요 변수로 작용하고 있습니다. 이러한 속도는 수율의 성숙도, 실제 환경에서의 신뢰성, 그리고 하이퍼스케일러의 인증이 스케일업 및 스케일아웃 네트워크 전반에 걸친 양산 전개로 전환되는 속도에 따라 좌우됩니다.

'Global Co-Packaged Optics Market 2027-2037'은 AI 데이터센터, 하이퍼스케일 및 고성능 컴퓨팅(HPC) 애플리케이션 분야의 코패키지드 옵틱스(CPO)에 대한 포괄적인 시장 및 기술 평가 보고서입니다. 구리선 및 플러그인형 광모듈이 물리적·경제적 한계에 도달함에 따라 CPO는 스케일업 및 스케일아웃 AI 네트워크의 기반이 되는 상호 연결 기술로 부상하고 있습니다. 이 보고서는 이러한 전환을 성공적으로 이겨내기 위해 필요한 데이터, 기술 분석 및 경쟁사 정보를 제공합니다.

이 보고서에서는 2026-2037년까지의 시장을 용도별(스위치 CPO 및 XPU 광 I/O), 스위치 대역폭 세대별(51.2T, 102.4T, 204.8T+), 통합 기술(2D, 2.5D 실리콘/유기/유리, 3D 마이크로 범프 및 하이브리드 본딩), 구성 요소, 지역(북미, 아시아태평양, 유럽, 기타 지역)별로 시장을 분석하고 있습니다. 이 보고서에는 확률적 평가를 반영한 강세·중립·약세 시나리오, 출하 대수 및 가격 추이, 플러그인 방식 모듈과의 비용 비교 분석, 그리고 총 소유 비용(TCO) 모델링이 포함되어 있습니다.

기술적 측면에서, 이 보고서는 포토닉 집적회로 및 실리콘 포토닉스, 광 엔진 아키텍처, 지연 시간, 전력 소비, 데이터 전송 속도 측면에서 CPO의 장점, 레인당 200G로의 전환, 변조기 소재(실리콘 마이크로링, TFLN, BTO, 인듐 인화물), 파장 분할 다중화(WDM) 및 ‘비치프론트’ 광섬유 수 제약, 채널 수 확장, 종단 간 광 링크 예산; 첨단 패키징(실리콘, 유기, 유리 인터포저, TSV, 하이브리드 본딩); EIC/PIC 통합; 레이저 광원 및 외부 레이저 아키텍처; 파이버 어레이 유닛 및 탈착식 커넥터; 표준(OIF, OCI-MSA, UCIe, XPO, Open CPX); 그리고 CPO의 테스트 및 제조 규모 확대. 또한 최근 업계 재편과 NVIDIA의 공급망 투자를 포함하여 산업 생태계와 공급망 전반에 대해서도 분석하고 있습니다.

보고서의 내용은 다음과 같습니다. :

  • 요약, 주요 조사 결과, 시장 촉진요인과 제약 요인, 그리고 2026년까지의 최근 동향
  • 최신 AI 데이터센터 아키텍처, 스위치 ASIC 및 SerDes의 진화, 그리고 상호 연결의 장벽
  • 미래 AI 시스템의 과제와 해결책
  • CPO 도입: PIC, 광학 엔진, 3가지 기본 개념, 장점, 향후 과제 및 규격
  • CPO용 패키징: 2.5D 실리콘/유기/유리, 3D 범프 및 하이브리드 본딩, EIC/PIC 통합 옵션
  • CPO 시장 분석: 정의, 시장 규모, 스위치 및 XPU 부문, 가격, 지역별 동향, TAM, 도입 곡선, 경쟁 구도 및 시나리오 분석
  • 데이터 통신, 하이퍼스케일, 엣지 분야의 세계 동향 및 기술 동향(패키징, UCIe, 레이저)
  • 시장 전망: 하이브리드·플러그형에서 CPO로의 전환, 스케일아웃 및 스케일업로드맵, 고밀도 커넥터, 공급망 동향
  • 기업 개요(Advantest, Alphawave Semi, AMD, Amkor Technology, ASE Technology Holdings, Astera Labs, Avicena, AXT, Ayar Labs, Broadcom, CEA-Leti, Celestial AI, Cisco, Coherent, Corning, Credo, DenseLight, EFFECT Photonics, EVG, Fabrinet, FOCI(Fiber Optical Communication Inc.), FormFactor, Foxconn, Furukawa Electric, GlobalFoundries, Henkel, Hewlett Packard Enterprise, Hisense Broadband Multimedia Technologies, IBM Corporation, imec, Intel, JCET Group, Kyocera Corporation, Lightmatter, LightSpeed Photonics, LioniX International, Lumentum 등)

목차

제1장 개요

제2장 미래 AI 시스템의 과제와 해결책

제3장 CPO(Co-Packaged Optics)의 개요

제4장 CPO(Co-Packaged Optics)의 패키징

제5장 복합 패키지 광학 기기 시장 분석

제6장 데이터 통신에서 세계 시장 동향

제7장 시장 전망

제8장 기업 개요(68 기업 개요)

제9장 부록

제10장 참고 문헌

KSA 26.06.24

Co-packaged optics (CPO) represents the most fundamental rethinking of optical interconnect in decades, moving the optical engine from the switch faceplate to a position immediately adjacent to the switch or accelerator silicon. By collapsing the high-speed electrical path from centimetres to millimetres, CPO overcomes the "interconnect wall" - the widening gap between AI bandwidth demand, which doubles roughly every two years at the switch and far faster for model parameters, and per-lane optical speed, which doubles only about every four years. The technology delivers materially better power efficiency and substantially lower latency than pluggable transceivers, addressing the binding power, density and cost-per-bit constraints of AI data centres.

The market divides into scale-out CPO (network-switch optical engines) and scale-up CPO (GPU and AI-accelerator optical I/O), with scale-up overtaking scale-out toward the end of the decade and becoming the dominant segment thereafter. Adoption begins in the highest-bandwidth network switches, where pluggable modules hit physical and economic limits, and extends into AI-accelerator optical I/O as next-generation GPU platforms ramp.

Recent developments have been decisive. NVIDIA committed to the laser supply chain with major strategic investments in Coherent and Lumentum, and moved its Quantum-X and Spectrum-X Photonics CPO switches toward production. TSMC firmed its COUPE roadmap - a 200 Gbps micro-ring modulator in production in 2026, targeting 4 Tbps/mm bandwidth density by 2030 - while GlobalFoundries launched the OCI-MSA-aligned SCALE platform with 8λ and 16λ demonstrated. Ayar Labs joined NVIDIA's NVLink Fusion ecosystem after a Series E raise; Marvell completed its Celestial AI acquisition; and Fabrinet invested in Raytek Semiconductor. The OCI-MSA (AMD, Broadcom, Meta, Microsoft, NVIDIA, OpenAI) emerged as the de facto scale-up interconnect standard.

Counterbalancing the momentum, large-scale NVIDIA CPO production could slip to 2028–2029 on systems-engineering grounds - serviceability, reliability and manufacturing-test yield - elevating near-package optics (NPO) as a pragmatic intermediate and triggering a sharp sell-off across optical equities. Test and manufacturing scale-up, from roughly one million to tens of millions of units annually, is now seen as the binding constraint, demanding automated, dual-domain electrical-and-optical test cells and standardised optical connectors. The consensus is that CPO's direction is settled; its rate of adoption is the central variable, shaped by yield maturation, field reliability and the pace at which hyperscaler qualification converts into volume deployment across scale-up and scale-out networks.

The Global Co-Packaged Optics Market 2027-2037 is a comprehensive market and technology assessment of co-packaged optics across AI data-centre, hyperscale and high-performance-computing applications. As copper and pluggable optics reach fundamental physical and economic limits, CPO is emerging as the foundational interconnect technology for scale-up and scale-out AI networks. This report provides the data, technology analysis and competitive intelligence needed to navigate the transition.

The report assesses the market from 2026 through 2037, segmented by application (switch CPO and XPU optical I/O), by switch bandwidth generation (51.2T, 102.4T, 204.8T+), by integration technology (2D, 2.5D silicon/organic/glass, 3D micro-bump and hybrid bonding), by component, and by region (North America, Asia-Pacific, Europe, Rest of World). It includes bull, base and bear scenarios with probability assessments, unit-volume and pricing trajectories, cost-parity analysis versus pluggables, and total-cost-of-ownership modelling.

Technically, the report covers photonic integrated circuits and silicon photonics; optical-engine architecture; the benefits of CPO in latency, power and data rate; the 200G-per-lane transition; modulator materials (silicon micro-ring, TFLN, BTO, indium phosphide); wavelength-division multiplexing and the "beachfront" fibre-count constraint; channel-count scaling; the end-to-end optical link budget; advanced packaging (silicon, organic and glass interposers, TSV, hybrid bonding); EIC/PIC integration; laser sources and external-laser architectures; fibre array units and detachable connectors; standards (OIF, OCI-MSA, UCIe, XPO, Open CPX); and CPO test and manufacturing scale-up. It also analyses the full industrial ecosystem and supply chain, including recent consolidation and NVIDIA's supply-chain investments.

Report contents include:

  • Executive summary, key findings, market drivers and restraints, and 2026 recent developments
  • Modern AI data-centre architecture, switch ASIC and SerDes evolution, and the interconnect wall
  • Challenges and solutions for future AI systems
  • Introduction to CPO: PICs, optical engines, three core concepts, benefits, future challenges, and standards
  • Packaging for CPO: 2.5D silicon/organic/glass, 3D bumping and hybrid bonding, EIC/PIC integration options
  • CPO market analysis: definitions, sizing, switch and XPU segments, pricing, regional dynamics, TAM, adoption curves, competitive landscape and scenario analysis
  • Global market trends in DATACOM, hyperscale and edge, plus technology trends (packaging, UCIe, lasers)
  • Market outlook: hybrid pluggable-to-CPO transition, scale-out and scale-up roadmaps, high-density connectors, supply-chain dynamics
  • Company profiles including Advantest, Alphawave Semi, AMD, Amkor Technology, ASE Technology Holdings, Astera Labs, Avicena, AXT, Ayar Labs, Broadcom, CEA-Leti, Celestial AI, Cisco, Coherent, Corning, Credo, DenseLight, EFFECT Photonics, EVG, Fabrinet, FOCI (Fiber Optical Communication Inc.), FormFactor, Foxconn, Furukawa Electric, GlobalFoundries, Henkel, Hewlett Packard Enterprise, Hisense Broadband Multimedia Technologies, IBM Corporation, imec, Intel, JCET Group, Kyocera Corporation, Lightmatter, LightSpeed Photonics, LioniX International, Lumentum and more....

Table of Contents

1 EXECUTIVE SUMMARY

  • 1.1 Report Overview and Key Findings
  • 1.2 Key Developments in
  • 1.3 Market Definition and Scope
    • 1.3.1 Definition of Co-Packaged Optics (CPO)
    • 1.3.2 Scope of This Report
  • 1.4 Key Market Drivers and Restraints
  • 1.5 Modern High-Performance AI Data Centre Architecture
    • 1.5.1 Physical Infrastructure Hierarchy
    • 1.5.2 Network Architecture
    • 1.5.3 Power and Cooling Considerations
  • 1.6 Switches: Key Components in Modern Data Centres
    • 1.6.1 Switch Architecture Evolution
    • 1.6.2 Switch ASIC Technology
    • 1.6.3 Optical Transceiver Requirements
  • 1.7 Advancements in Switch IC Bandwidth and the Need for CPO Technology
    • 1.7.1 Historical Bandwidth Scaling
    • 1.7.2 SerDes Technology Evolution
    • 1.7.3 Electrical Signalling Limits
    • 1.7.4 Front-Panel Density Constraints
    • 1.7.5 Power Consumption Trajectory
    • 1.7.6 The Interconnect Wall
  • 1.8 Overview of Key Challenges in Data Centre Architectures
    • 1.8.1 Thermal Management
    • 1.8.2 Power Delivery
    • 1.8.3 Cable Management
    • 1.8.4 Reliability and Serviceability
    • 1.8.5 Standards and Interoperability
  • 1.9 Key Trend of Optical Transceivers in High-End Data Centres
    • 1.9.1 Historical Evolution
    • 1.9.2 Technology Migration Path
  • 1.10 Design Decisions: CPO vs. Pluggables Comparison
    • 1.10.1 Performance Comparison
    • 1.10.2 Operational Comparison
    • 1.10.3 Economic Comparison
  • 1.11 What is an Optical Engine (OE)?
    • 1.11.1 Functional Description
    • 1.11.2 Optical Engine Components
    • 1.11.3 Performance Parameters
  • 1.12 Heterogeneous Integration and Co-Packaged Optics
    • 1.12.1 The Heterogeneous Integration Imperative
    • 1.12.2 Integration Approaches for CPO
    • 1.12.3 TSMC's Role in Heterogeneous Integration
  • 1.15 Overview of Interconnection Techniques in Semiconductor Packaging
    • 1.15.1 Wire Bonding
    • 1.15.2 Flip-Chip Bumping
    • 1.15.3 Micro-Bumping
    • 1.15.4 Through-Silicon Via (TSV)
    • 1.15.5 Hybrid Bonding
    • 1.15.6 Redistribution Layer (RDL)
  • 1.16 Key CPO Applications: Network Switch and Computing Optical I/O
    • 1.16.1 Scale-Out Network Switching
    • 1.16.2 Scale-Up Computing Optical I/O
  • 1.17 EIC/PIC Integration by Advanced Interconnect Techniques
    • 1.17.1 Integration Requirements
  • 1.18 2D to 3D EIC/PIC Integration Options
    • 1.18.1 2D Integration Architecture
    • 1.18.2 2.5D Integration Architecture
    • 1.18.3 3D Integration Architecture
  • 1.19 Benchmark of Different Packaging Technologies for EIC/PIC
  • 1.20 Examples of Packaging a 3D Optical Engine with an IC
    • 1.20.1 Configuration 1: EIC-on-PIC with Micro-Bumps
    • 1.20.2 Configuration 2: PIC-on-EIC with Through-Silicon Vias
    • 1.20.3 Configuration 3: 3D SoIC with Hybrid Bonding
  • 1.21 Types of CPO + XPU/Switch ASIC Packaging Structures
    • 1.21.1 Type I: Optical Engines on Package Periphery
    • 1.21.2 Type II: Optical Engines Co-Located with ASIC on Interposer
    • 1.21.3 Type III: 3D Stacked Optical Engines
  • 1.22 Challenges and Future Potential of CPO Technology
    • 1.22.1 Technical Challenges
    • 1.22.2 Commercial Challenges
      • 1.22.2.1 Future Potential
  • 1.23 NVIDIA vs. Broadcom: Strategic Comparison in AI Infrastructure and CPO
    • 1.23.1 NVIDIA's CPO Strategy: Vertical Integration
    • 1.23.2 Broadcom's CPO Strategy: Open Ecosystem
    • 1.23.3 Competitive Dynamics
    • 1.23.4 CPO Product Benchmark: NVIDIA vs. Broadcom
    • 1.23.5 NVIDIA and Broadcom: Divergent CPO Ecosystems
  • 1.24 Current AI System Architecture
    • 1.24.1 NVIDIA DGX/HGX Architecture
  • 1.25 Future AI Architecture
  • 1.26 Co-packaged optics market map
  • 1.27 Market Forecasts
    • 1.27.1 Server Boards, CPUs, and GPUs/Accelerators
    • 1.27.2 Optical I/O for AI Interconnect CPO Forecast (Units Shipped)
    • 1.27.3 Optical I/O for AI Interconnect CPO Forecast (Revenue/Market Size)
    • 1.27.4 CPO Network Switches for AI Accelerators Forecast (Units Shipped)
    • 1.27.5 CPO Network Switches for AI Accelerators Forecast (Market Size and Revenue)
    • 1.27.6 Total CPO Market Overview
    • 1.27.7 Total CPO by Different EIC/PIC Integration Technology (Unit Shipments)
    • 1.27.8 System Integration of Network Switches by Packaging Technologies
    • 1.27.9 System Integration of Optical I/O Forecast by Packaging Technologies
  • 1.28 Co-packaged optics (CPO) industrial ecosystem
    • 1.28.1 PIC Design Segment
    • 1.28.2 ASIC and xPU Design Segment
    • 1.28.3 Laser Sources Segment
    • 1.28.4 SOI Wafer and Epi-Wafer Segment
    • 1.28.5 EIC, Retimers, SerDes, and PHY Segment
    • 1.28.6 Connectors and Fibers Segment
    • 1.28.7 Foundries Segment
    • 1.28.8 Packaging, Assembling, and Testing Segment
    • 1.28.9 System and Equipment Segment
    • 1.28.10 End Customers (Hyperscalers) Segment
    • 1.28.11 Ecosystem Interdependencies and Strategic Implications

2 CHALLENGES AND SOLUTIONS FOR FUTURE AI SYSTEMS

  • 2.1 The Rise and Challenges of Large Language Models (LLMs)
    • 2.1.1 The Explosive Growth of AI and Generative AI
      • 2.1.1.1 Historical Context and Acceleration
      • 2.1.1.2 Compute Demand Scaling
      • 2.1.1.3 Generative AI Market Expansion
    • 2.1.2 Modern High-Performance AI Data Centre Requirements
      • 2.1.2.1 Compute Density Requirements
      • 2.1.2.2 Network Topology Requirements
      • 2.1.2.3 Availability and Reliability Requirements
    • 2.1.3 NVIDIA's State-of-the-Art AI Systems
      • 2.1.3.1 DGX H100 and HGX H100
    • 2.1.4 Switches: Key Components in Modern Data Centres
      • 2.1.4.1 Switch Hierarchy in AI Data Centres
  • 2.2 Scale-Up, Scale-Out, and Scale-Across Networks
    • 2.2.1 Scale-Up Networks: GPU-to-GPU Interconnects
      • 2.2.1.1 NVIDIA NVLink Implementation
      • 2.2.1.2 CPO Value Proposition for Scale-Up
    • 2.2.2 Scale-Out Networks: Rack-to-Rack Communications
      • 2.2.2.1 Ethernet-Based Scale-Out
      • 2.2.2.2 InfiniBand for AI
      • 2.2.2.3 CPO Value Proposition for Scale-Out
    • 2.2.3 Scale-Up, Scale-Out, and Scale-Across Comparison
  • 2.3 Challenges in Network Switch Interconnects for High-End Data Centres
    • 2.3.1 Roadmap of Interconnect Technology for Network Switches in High-End Data Centres
      • 2.3.1.1 Technology Generations
    • 2.3.2 SerDes Bottleneck in High-Bandwidth Systems
      • 2.3.2.1 SerDes Function
      • 2.3.2.2 Channel Loss Challenges
    • 2.3.3 Solutions to SerDes Bottlenecks in High-Bandwidth Systems
      • 2.3.3.1 Linear-Drive Electronics
      • 2.3.3.2 Near-Package Optics
      • 2.3.3.3 Co-Packaged Optics
    • 2.3.4 Pluggable Optics: Current Bottlenecks and Limitations
      • 2.3.4.1 Form Factor Constraints
      • 2.3.4.2 Electrical Interface Limitations
      • 2.3.4.3 Thermal Management Challenges
      • 2.3.4.4 Serviceability Trade-offs
    • 2.3.5 On-Board Optics (OBO)
    • 2.3.6 Co-Packaged Optics (CPO)
      • 2.3.6.1 CPO Architecture
      • 2.3.6.2 Key Enabling Technologies
      • 2.3.6.3 Performance Benefits
      • 2.3.6.4 Implementation Challenges
    • 2.3.7 Transmission Losses in Pluggable Optical Transceiver Connections
      • 2.3.7.1 Total Path Loss
    • 2.3.8 Pluggable Optics vs. CPO
    • 2.3.9 Design Decisions for CPO Compared to Pluggables
    • 2.3.10 Advancements in Switch IC Bandwidth and the Need for CPO Technology
      • 2.3.10.1 Bandwidth Scaling Trajectory
      • 2.3.10.2 Physical Constraints at Scale
    • 2.3.11 L2 Frontside Network Architecture Diagram: CPO vs. Non-CPO
  • 2.4 Challenges in Compute Switch Interconnects (Optical I/O) for High-End Data Centres
    • 2.4.1 Number of Copper Wires in Current AI System Interconnects
      • 2.4.1.1 NVLink Copper Cable Count
      • 2.4.1.2 SuperPOD Cable Complexity
    • 2.4.2 Limitations of Current Copper Systems in AI
    • 2.4.3 NVIDIA's Connectivity Choices: Copper vs. Optical for High-Bandwidth Systems
      • 2.4.3.1 Current Generation: Copper-Centric
      • 2.4.3.2 Transition Generation: Hybrid Approach
      • 2.4.3.3 Future Generation: Optical-First
      • 2.4.3.4 Strategic Implications
    • 2.4.4 Copper vs. Optical for High-Bandwidth Systems: Benchmark
    • 2.4.5 Migration from Copper to Optical Interconnects for High-End AI Systems
    • 2.4.6 Current AI System Architecture
    • 2.4.7 L1 Backside Compute Architecture with Copper Systems
    • 2.4.8 L1 Backside Compute Architecture with Optical Interconnect: Co-Packaged Optics (CPO)
    • 2.4.9 Opportunities for Swapping Copper to Optical
  • 2.5 Future AI Systems in High-End Data Centres
    • 2.5.1 Power Efficiency Comparison: CPO vs. Pluggable Optics vs. Copper Interconnects
      • 2.5.1.1 Power Consumption Breakdown
    • 2.5.2 Latency of 60cm Data Transmission Technology Benchmark
    • 2.5.3 Future AI Architecture (Short to Mid-Term)
    • 2.5.4 Future AI Architecture (Long-Term)

3 INTRODUCTION TO CO-PACKAGED OPTICS (CPO)

  • 3.1 Photonic Integrated Circuits (PICs) Key Concepts
    • 3.1.1 What are Photonic Integrated Circuits (PICs)?
      • 3.1.1.1 Fundamental Definition
      • 3.1.1.2 Material Platforms
      • 3.1.1.3 Integration Levels
    • 3.1.2 PICs vs. Silicon Photonics: What are the Differences?
      • 3.1.2.1 Silicon Photonics: A Specific Implementation
      • 3.1.2.2 Why Silicon Photonics Dominates CPO
    • 3.1.3 PIC Architecture
      • 3.1.3.1 Transmit Path Architecture
      • 3.1.3.2 Receive Path Architecture
      • 3.1.3.3 Supporting Functions
    • 3.1.4 Advantages and Challenges of PICs
  • 3.2 Optical Engine (OE)
    • 3.2.1 What is an Optical Engine?
      • 3.2.1.1 Optical Engine Composition
      • 3.2.1.2 Optical Engine vs. Pluggable Transceiver
    • 3.2.2 How an Optical Engine Works
      • 3.2.2.1 Transmit Path Operation
      • 3.2.2.2 Receive Path Operation
      • 3.2.2.3 Critical Performance Parameters
    • 3.2.3 Optical Power Supplies
      • 3.2.3.1 Why External Laser Sources?
      • 3.2.3.2 External Laser Source Architectures
      • 3.2.3.3 Optical Power Delivery
  • 3.3 Co-Packaged Optics
    • 3.3.1 Three Key Concepts in Co-Packaged Optics (CPO)
      • 3.3.1.1 Concept 1: Proximity Integration
      • 3.3.1.2 Concept 2: Functional Partitioning
      • 3.3.1.3 Concept 3: Coherent Ecosystem Development
    • 3.3.2 Key Technology Building Blocks for CPO
      • 3.3.2.1 Silicon Photonics PIC
      • 3.3.2.2 Electronic IC (EIC)
      • 3.3.2.3 EIC-PIC Integration
      • 3.3.2.4 Fibre Array Units (FAUs)
      • 3.3.2.5 External Laser Source
      • 3.3.2.6 Advanced Packaging Platform
    • 3.3.3 Benefits of CPO: Latency Reduction
      • 3.3.3.1 Sources of Latency in Optical Interconnects
      • 3.3.3.2 CPO Latency Advantages
    • 3.3.4 Benefits of CPO: Power Consumption Reduction
      • 3.3.4.1 Power Consumption Breakdown
      • 3.3.4.2 Why CPO Consumes Less Power
    • 3.3.5 Benefits of CPO: Data Rate Improvements
      • 3.3.5.1 Pluggable Scaling Limitations
      • 3.3.5.2 CPO Scaling Advantages
      • 3.3.5.3 Data Rate Scaling Roadmap
      • 3.3.5.4 The 200G-per-Lane Transition and Silicon Photonics
      • 3.3.5.5 Modulator Technology Roadmap and Emerging Materials
      • 3.3.5.6 Technology Trends in CPO Driven by Rising Data Rates
      • 3.3.5.7 Applicability of Wavelength-Division Multiplexing (WDM)
      • 3.3.5.8 Physical Limits on Fibre Count: The Beachfront (Shoreline) Constraint
      • 3.3.5.9 Increasing the Number of WDM Channels: Technical Challenges
      • 3.3.5.10 The End-to-End Optical Link Budget
    • 3.3.6 Overview of Value Proposition of CPO
      • 3.3.6.1 Value for Hyperscale Data Centre Operators
      • 3.3.6.2 Value for Network Equipment Vendors
      • 3.3.6.3 Value for the Technology Ecosystem
    • 3.3.7 Future Challenges in CPO
      • 3.3.7.1 Manufacturing and Yield Challenges
      • 3.3.7.2 Thermal Management Challenges
      • 3.3.7.3 Serviceability and Reliability Challenges
      • 3.3.7.4 Ecosystem and Standardisation Challenges
      • 3.3.7.5 Cost Challenges
      • 3.3.7.6 Test and Manufacturing Scale-Up
  • 3.4 CPO Standards
    • 3.4.1 OIF Co-Packaging Framework
    • 3.4.2 OCI-MSA (Optical Compute Interconnect Multi-Source Agreement)
    • 3.4.3 OIF Standards for 1.6T and 3.2T CPO Module
    • 3.4.4 External Laser Small Form Pluggable (ELSFP) Implementation Agreement
    • 3.4.5 Telemetry and Management
    • 3.4.6 OIF's CEI-112G XSR / XSR+ PAM4
    • 3.4.7 UCIe Standard and Its Relationship to CPO
    • 3.4.8 The CPO Standards Process in China
    • 3.4.9 XPO and Open CPX Initiatives
    • 3.4.10 Near-Package Optics (NPO) as an Intermediate Path

4 PACKAGING FOR CO-PACKAGED OPTICS (CPO)

  • 4.1 Introduction to CPO Packaging
    • 4.1.1 Key Components to be Packaged in an Optical Transceiver
      • 4.1.1.1 Photonic Integrated Circuit (PIC)
      • 4.1.1.2 Electronic Integrated Circuit (EIC)
      • 4.1.1.3 Laser Source Interface
      • 4.1.1.4 Fibre Array Unit (FAU)
      • 4.1.1.5 Host ASIC Interface
    • 4.1.2 Heterogeneous Integration and Co-Packaged Photonics
      • 4.1.2.1 Why Heterogeneous Integration for CPO?
      • 4.1.2.2 Heterogeneous Integration Approaches for CPO
      • 4.1.2.3 Integration Hierarchy for CPO
    • 4.1.3 CPO for Network Switch: Packaging Concept
      • 4.1.3.1 Switch Architecture with CPO
      • 4.1.3.2 Package Configuration Options
      • 4.1.3.3 Packaging Requirements for Switch CPO
    • 4.1.4 1.6 Tbps Co-Packaged Optics for Network Switch
      • 4.1.4.1 Integration Approach
    • 4.1.5 CPO as Optical I/O for XPUs: Packaging Concept
      • 4.1.5.1 The Scale-Up Interconnect Challenge
      • 4.1.5.2 XPU-CPO Packaging Concept
      • 4.1.5.3 Implementation Approaches
      • 4.1.5.4 NVIDIA's Approach to XPU Optical I/O
      • 4.1.5.5 Packaging Implications for XPU Optical I/O
      • 4.1.5.6 System Architecture Evolution
    • 4.1.6 CPO Integration for Compute Silicon
      • 4.1.6.1 System Configuration
      • 4.1.6.2 Integration Architecture
      • 4.1.6.3 Thermal Partitioning
      • 4.1.6.4 Enabled Architectures
    • 4.1.7 Overview of CPO Packaging Technologies
  • 4.2 Overview and Development Roadmap of 2.5D and 3D Advanced Semiconductor Packaging Technologies
    • 4.2.1 Evolution Roadmap of Semiconductor Packaging
    • 4.2.2 Semiconductor Packaging Overview
    • 4.2.3 Key Metrics for Advanced Semiconductor Packaging Performance
    • 4.2.4 Overview of Interconnection Techniques in Semiconductor Packaging
    • 4.2.5 Overview of 2.5D Packaging Structure
    • 4.2.6 2.5D Package Components
    • 4.2.7 Benefits for CPO
    • 4.2.8 Challenges for CPO
  • 4.3 2.5D Silicon-Based Packaging Technologies
    • 4.3.1 2.5D Packaging Involving Silicon as Interconnect
    • 4.3.2 Silicon Interposer Technology
    • 4.3.3 Silicon Bridge Technology
    • 4.3.4 CPO Implications
    • 4.3.5 Through-Silicon Via (TSV): Current State and Future
      • 4.3.5.1 TSV Fabrication Process
      • 4.3.5.2 TSV Technology Generations
      • 4.3.5.3 TSV Challenges for CPO
      • 4.3.5.4 Future TSV Development
    • 4.3.6 Development Trends for 2.5D Silicon-Based Packaging
      • 4.3.6.1 Interposer Size Scaling
      • 4.3.6.2 Routing Density Advancement
      • 4.3.6.3 Cost Reduction Initiatives
      • 4.3.6.4 Integration with Advanced Features
    • 4.3.7 Silicon Interposer vs. Silicon Bridge Benchmark
      • 4.3.7.1 Implications for CPO
  • 4.4 2.5D Organic-Based Packaging Technologies
    • 4.4.1 2.5D Packaging: High-Density Fan-Out (FO) Packaging
      • 4.4.1.1 Fan-Out Technology Concept
      • 4.4.1.2 High-Density Fan-Out Variants
      • 4.4.1.3 Advantages for CPO
      • 4.4.1.4 Challenges for CPO
    • 4.4.2 Redistribution Layer (RDL)
      • 4.4.2.1 RDL Fabrication Process
      • 4.4.2.2 RDL Design Considerations for CPO
    • 4.4.3 Electronic Interconnects: SiO2 vs. Organic Dielectric
    • 4.4.4 Panel Level Fab-Out
      • 4.4.4.1 Panel-Level Processing
      • 4.4.4.2 Advantages for CPO
      • 4.4.4.3 Challenges for CPO
    • 4.4.5 Wafer Level Fan-Out
      • 4.4.5.1 Wafer-Level Processing
      • 4.4.5.2 Advantages for WLFO
      • 4.4.5.3 Challenges for WLFO
    • 4.4.6 Wafer-Level Fan-Out vs. Panel-Level Fan-Out
      • 4.4.6.1 Selection Criteria for CPO
    • 4.4.7 Key Trends in Fan-Out Packaging
    • 4.4.8 Challenges in Future Fan-Out Processes
      • 4.4.8.1 Die Shift and Placement Accuracy
      • 4.4.8.2 Warpage Control
      • 4.4.8.3 Yield and Cost
      • 4.4.8.4 High-Frequency Performance
  • 4.5 2.5D Glass-Based Packaging Technologies
    • 4.5.1 Roles of Glass in Semiconductor Packaging
      • 4.5.1.1 Glass Properties Relevant to Packaging
      • 4.5.1.2 Applications in Packaging
      • 4.5.1.3 Glass Core as Interposer for Advanced Semiconductor Packaging
    • 4.5.2 Overcoming Limitations of Silicon Interposers with Glass
      • 4.5.2.1 Size Limitation
      • 4.5.2.2 Optical Opacity
      • 4.5.2.3 Dielectric Loss
      • 4.5.2.4 Cost Structure
      • 4.5.2.5 Remaining Silicon Advantages
    • 4.5.3 Glass vs. Molding Compound
      • 4.5.3.1 Implications for CPO
    • 4.5.4 Glass Core (Interposer) Package: Process Flow
    • 4.5.5 Challenges of Glass Packaging
      • 4.5.5.1 Handling and Breakage
      • 4.5.5.2 Via Formation and Metallisation
      • 4.5.5.3 Thermal Conductivity
      • 4.5.5.4 RDL Adhesion
      • 4.5.5.5 Warpage Control
  • 4.6 3D Advanced Semiconductor Packaging Technologies
    • 4.6.1 Evolution of Bumping Technologies
      • 4.6.1.1 Solder Bumps (C4)
      • 4.6.1.2 Copper Pillar Bumps
      • 4.6.1.3 Micro-Bumps
      • 4.6.1.4 Hybrid Bonding (Bumpless)
    • 4.6.2 Challenges in Scaling Bumps
      • 4.6.2.1 Mechanical Challenges
      • 4.6.2.2 Electrical Challenges
      • 4.6.2.3 Manufacturing Challenges
      • 4.6.2.4 Implications for CPO
    • 4.6.3 Micro-Bump for Advanced Semiconductor Packaging
      • 4.6.3.1 Micro-Bump Structure
    • 4.6.4 Bumpless Cu-Cu Hybrid Bonding
      • 4.6.4.1 Hybrid Bonding Concept
      • 4.6.4.2 Process Fundamentals
      • 4.6.4.3 Key Characteristics
      • 4.6.4.4 Benefits for CPO
    • 4.6.5 Three Ways of Cu-Cu Hybrid Bonding: Benchmark
      • 4.6.5.1 Die-to-Die (D2D)
      • 4.6.5.2 Die-to-Wafer (D2W)
      • 4.6.5.3 Wafer-to-Wafer (W2W)
    • 4.6.6 Challenges in Cu-Cu Hybrid Bonding Manufacturing Process
  • 4.7 CPO Packaging: EIC and PIC Integration
    • 4.7.1 EIC/PIC Integration by Conventional Interconnect Techniques
      • 4.7.1.1 Wire Bond Integration
      • 4.7.1.2 Flip-Chip Integration (2D)
    • 4.7.2 EIC/PIC Integration by Emerging Interconnect Techniques
      • 4.7.2.1 2.5D Interposer Integration
      • 4.7.2.2 3D Micro-Bump Stacking
      • 4.7.2.3 3D Hybrid Bonding
    • 4.7.3 2D to 3D EIC/PIC Integration Options
      • 4.7.3.1 Technology Transition Drivers
      • 4.7.3.2 2D to 3D Integration Evolution
    • 4.7.4 Integration Roadmap by CPO Segment
    • 4.7.5 Benchmarking of Different Packaging Technologies for EIC/PIC
    • 4.7.6 Pros and Cons of 2D Integration of EIC/PIC
    • 4.7.7 Pros and Cons of 2.5D Integration of EIC/PIC
    • 4.7.8 Pros and Cons of 3D Hybrid Integration of EIC/PIC
    • 4.7.9 Pros and Cons of 3D Monolithic Integration of EIC/PIC
  • 4.8 TSV for EIC/PIC Integration
    • 4.8.1 TSV for EIC/PIC Integration in CPO
      • 4.8.1.1 TSV Configurations for EIC/PIC
      • 4.8.1.2 Design Considerations
    • 4.8.2 Benefits of TSV for PIC/EIC Integration
    • 4.8.3 Cisco Packaging Architectures of Optical Engine Over Generations
    • 4.8.4 Cisco: 2.5D Chip-on-Chip (CoC) Packaging Architecture for EIC/PIC Integration
      • 4.8.4.1 Architecture Description
      • 4.8.4.2 Manufacturing Considerations
    • 4.8.5 Cisco: 3D TSV for PIC/EIC Integration
      • 4.8.5.1 Architecture Description
      • 4.8.5.2 Benefits of TSV Integration
      • 4.8.5.3 Manufacturing Considerations
    • 4.8.6 Key TSV Fabrication Steps and Challenges in CPO
      • 4.8.6.1 Fabrication Process Flow
    • 4.8.7 Packaging Options for Silicon Photonics
    • 4.8.8 Pros and Cons of 2.5D Si Interposer for EIC/PIC Integration
  • 4.9 Fan-Out for EIC/PIC Integration
    • 4.9.1 ASE's Proposed Fan-Out Solution for CPO Packaging
      • 4.9.1.1 ASE Fan-Out CPO Concept
    • 4.9.2 FOPOP from ASE: Process
    • 4.9.3 Analysis of FOPOP vs. Wire Bond Packaging for CPO
    • 4.9.4 Optical Packaging Process Considerations for Silicon Photonics - ASE
    • 4.9.5 SPIL's Fan-Out Embedded Bridge (FOEB) Structure for PIC/EIC Integration in CPO
    • 4.9.6 Process Flow of Integrating PIC and EIC in a FOEB Structure
    • 4.9.7 Process Challenges in Packaging Optical Engines
    • 4.9.8 Challenges of Using Fan-Out for EIC/PIC Integration
  • 4.10 Glass-Based CPO Packaging Technologies
    • 4.10.1 Glass-Based Co-Packaged Optics
      • 4.10.1.1 Corning's Glass CPO Vision
    • 4.10.2 Glass CPO Package Architecture
    • 4.10.3 Glass-Based CPO Process Development
      • 4.10.3.1 Corning's 102.4 Tb/s Test Vehicle Demonstration
    • 4.10.4 3D Heterogeneous Integration of EIC/PIC on a Glass Interposer
      • 4.10.4.1 Architecture Rationale
      • 4.10.4.2 Package Architecture
      • 4.10.4.3 Process Flow
      • 4.10.4.4 Representative Switch Module Example
      • 4.10.4.5 Market Trajectory
  • 4.11 Hybrid Bonding for EIC/PIC Integration
    • 4.11.1 TSMC: Integrated HPC Technology Platform for AI
    • 4.11.2 iOIS: Integrated Optical Interconnection System from TSMC
    • 4.11.3 Combining EIC and PIC with 3D SoIC Bond
    • 4.11.4 Roadmap of Bond Pitch Scaling
  • 4.12 System Integration of Optical Engine and ASIC/XPU
    • 4.12.1 Co-Packaging vs. Co-Packaged Optics (CPO)
    • 4.12.2 Three Types of CPO + XPU/Switch ASIC Packaging Structures
      • 4.12.2.1 Type 1: 2D/2.5D Peripheral Integration
      • 4.12.2.2 Type 2: 2.5D with Embedded Bridge
      • 4.12.2.3 Type 3: 3D Stacked Integration
  • 4.13 Future 3D-CPO Structure
    • 4.13.1 Future 3D-CPO Architecture Vision
    • 4.13.2 NVIDIA's 3D Integration of SoC, HBM, EIC, and PIC on Co-Packaged Substrates
        • 4.13.2.1.1 Architecture Overview
        • 4.13.2.1.2 Integration Approach
        • 4.13.2.1.3 Key Innovations
  • 4.14 Optical Alignment and Laser Integration
    • 4.14.1 How CPO is Built and the Bottleneck
    • 4.14.2 The fibre attach bottleneck
    • 4.14.3 Interface Between Coupler and FAU
    • 4.14.4 Grating vs. Edge Couplers: Challenges in High-Density Optical I/O for Silicon Photonics
    • 4.14.5 Challenges in High-Density Optical I/O for Silicon Photonics
  • 4.15 Fiber Array Unit (FAU)
    • 4.15.1 Optical Alignment Challenges and Solutions
    • 4.15.2 Two Alignment Approaches
    • 4.15.3 Reducing Optical Fiber Packaging Complexity
    • 4.15.4 Key Technical Challenges
      • 4.15.4.1 The Size Mismatch Between Silicon Waveguides and Planar Optical Fibers
    • 4.15.5 Fiber Attach Methods
    • 4.15.6 Key Players in FAU for CPO
    • 4.15.7 Benchmark of Optical Fiber Alignment Structure Variations
    • 4.15.8 Suppliers of Other Optical Components in CPO
  • 4.16 Suppliers of Other Optical Components in CPO
  • 4.17 Laser Integration
    • 4.17.1 Laser sources for CPO
    • 4.17.2 On-Chip Light Source Integration Methods
    • 4.17.3 External Lasers for CPO
    • 4.17.4 Laser Attach Technology Benchmark
    • 4.17.5 Benchmark of Different Laser Integration Technologies

5 CO-PACKAGED OPTICS MARKET ANALYSIS

  • 5.1 CPO Market Definition and Scope
  • 5.2 CPO Market Size and Growth Projections
  • 5.3 Switch CPO Market Analysis
    • 5.3.1 Market Overview and Drivers
    • 5.3.2 Deployment Timeline and Adoption Phases
    • 5.3.3 Volume Projections and Market Sizing
    • 5.3.4 Market Concentration and Regional Distribution
    • 5.3.5 Pricing Trajectory and Cost Dynamics
  • 5.4 XPU Optical I/O Market Analysis
    • 5.4.1 Market Drivers and Value Proposition
    • 5.4.2 Adoption Timeline and Platform Evolution
    • 5.4.3 Volume and Revenue Projections
    • 5.4.4 Market Segmentation by Platform
    • 5.4.5 Technology Requirements and Differentiation
  • 5.5 CPO Pricing and Cost Analysis
    • 5.5.1 Current Pricing Landscape
    • 5.5.2 Cost Trajectory and Reduction Drivers
    • 5.5.3 Cost Parity Timeline and Dynamics
    • 5.5.4 Pricing Strategy Implications
  • 5.6 Regional Market Dynamics
    • 5.6.1 North America
    • 5.6.2 Asia-Pacific
    • 5.6.3 Europe
    • 5.6.4 Rest of World
  • 5.7 Total Addressable Market Analysis
    • 5.7.1 Core TAM Segments
    • 5.7.2 Serviceable Addressable Market (SAM)
  • 5.8 Market Forecast by Component
  • 5.9 Market Forecast by Technology Generation
    • 5.9.1 Optical Engine Bandwidth Evolution
    • 5.9.2 Generation Lifecycle Analysis
  • 5.10 Market Restraints and Barriers
    • 5.10.1 Manufacturing Yield and Cost
    • 5.10.2 Serviceability and Field Replacement Concerns
    • 5.10.3 Standards Maturity and Interoperability
    • 5.10.4 Supply Chain Capacity Constraints
    • 5.10.5 Competitive Alternatives
  • 5.11 Adoption Curve Analysis
    • 5.11.1 Technology Adoption Framework
      • 5.11.1.1 Innovators (2024-2026)
      • 5.11.1.2 Early Adopters (2026-2028)
      • 5.11.1.3 Early Majority (2028-2031)
      • 5.11.1.4 Late Majority (2031-2034)
      • 5.11.1.5 Laggards (2034+)
    • 5.11.2 Segment-Specific Adoption Curves
  • 5.12 Adoption Accelerators and Inhibitors
    • 5.12.1 Adoption Curve Implications
  • 5.13 Competitive Landscape Evolution
    • 5.13.1 Current Competitive Positioning
    • 5.13.2 Integrated Device Manufacturers (IDMs)
    • 5.13.3 Silicon Photonics Specialists
    • 5.13.4 Foundry/OSAT Providers
    • 5.13.5 System Vendors
    • 5.13.6 Laser Suppliers
    • 5.13.7 Competitive Dynamics and Market Structure Evolution
      • 5.13.7.1 Near-Term Dynamics (2025-2028)
        • 5.13.7.1.1 Expected Evolution (2028)
      • 5.13.7.2 Mid-Term Dynamics (2028-2032)
        • 5.13.7.2.1 Expected Evolution (2032)
      • 5.13.7.3 Long-Term Dynamics (2032-2036)
        • 5.13.7.3.1 Expected Evolution (2036)
    • 5.13.8 Vertical Integration Trends
      • 5.13.8.1 Integration Strategy Framework
        • 5.13.8.1.1 Full Vertical Integration (Broadcom, Intel Model)
        • 5.13.8.1.2 Partial Integration (Cisco, NVIDIA Model)
        • 5.13.8.1.3 Fabless/Assembly-Light (Ayar Labs, Ranovus Model)
        • 5.13.8.1.4 Platform Provider (TSMC Model)
      • 5.13.8.2 Strategic Implications of Integration Trends
    • 5.13.9 Recent Developments - Q1
    • 5.13.10 Recent Developments - Q2
  • 5.14 Scenario Analysis
    • 5.14.1 Scenario Framework
    • 5.14.2 Scenario Definitions
    • 5.14.3 Bull Case Scenario
    • 5.14.4 Base Case Scenario
    • 5.14.5 Bear Case Scenario
    • 5.14.6 Optical transceiver market
    • 5.14.7 Scenario Comparison and Key Variables

6 GLOBAL MARKET TRENDS IN DATACOM

  • 6.1 Introduction to DATACOM Market Dynamics
    • 6.1.1 Overview of the Data Communications Market
      • 6.1.1.1 Market Definition and Scope
      • 6.1.1.2 Market Size and Growth
    • 6.1.2 Key Market Drivers
      • 6.1.2.1 Artificial Intelligence and Machine Learning
      • 6.1.2.2 Cloud Computing Growth
      • 6.1.2.3 Data Growth
      • 6.1.2.4 Power and Sustainability Pressures
    • 6.1.3 The Optical Transceiver Market Context
  • 6.2 Application Trends
    • 6.2.1 AI and Machine Learning Workload Growth
      • 6.2.1.1 The AI Training Revolution
      • 6.2.1.2 Training Cluster Architecture Evolution
      • 6.2.1.3 AI Inference Deployment
      • 6.2.1.4 Market Quantification
      • 6.2.1.5 Implications for CPO
    • 6.2.2 Hyperscale Data Centre Expansion
      • 6.2.2.1 Defining Hyperscale
    • 6.2.3 Global Hyperscale Capacity
    • 6.2.4 Regional Distribution
    • 6.2.5 Hyperscaler Investment Trends
      • 6.2.5.1 Capital expenditure acceleration
      • 6.2.5.2 AI-Specific Infrastructure
      • 6.2.5.3 Implications for CPO
    • 6.2.6 Edge Computing and Distributed AI
      • 6.2.6.1 Market Growth
    • 6.2.7 Edge AI Applications
    • 6.2.8 Edge Network Architecture
  • 6.3 Technology Trends
    • 6.3.1 Technology Trends Overview
      • 6.3.1.1 Key Technology Vectors
      • 6.3.1.2 Technology Interdependencies
    • 6.3.2 Technology Trends: Packaging
    • 6.3.3 Universal Chiplet Interconnect Express (UCIe)
    • 6.3.4 Laser Sources for CPO
    • 6.3.5 External vs. Integrated Laser
    • 6.3.6 Silicon Photonics Share of Datacom

7 MARKET OUTLOOK

  • 7.1 Hybrid Pluggable-to-CPO Transition, 2026–2030
  • 7.2 Scale-Out Outlook
    • 7.2.1 Scale-Out CPO Market Evolution
      • 7.2.1.1 Scale-Out Market Drivers
      • 7.2.1.2 Market Evolution Phases
      • 7.2.1.3 Scale-Out CPO Market Forecast
    • 7.2.2 Scale-Out Technology Roadmap
      • 7.2.2.1 Technology Generation Evolution
      • 7.2.2.2 Technology Enablers by Generation
    • 7.2.3 Scale-Out Key Players and Competitive Landscape
  • 7.3 Scale-Up Outlook
    • 7.3.1 Scale-Up CPO Market Evolution
    • 7.3.2 Copper to Optical Transition
    • 7.3.3 Optical I/O Solution
    • 7.3.4 Scale-Up CPO Market Forecast
    • 7.3.5 Market Evolution Phases
    • 7.3.6 Scale-Up Technology Roadmap
      • 7.3.6.1 NVIDIA Optical I/O Evolution
      • 7.3.6.2 AMD Optical I/O Evolution
      • 7.3.6.3 Custom Silicon Optical I/O
    • 7.3.7 Scale-Up Key Players and Competitive Landscape
      • 7.3.7.1 Competitive Landscape Overview
  • 7.4 High-Density Connectors
    • 7.4.1 High-Density Connectors vs. CPO
      • 7.4.1.1 Scenario 1: Connectors Enable Extended Pluggable (Low CPO Impact)
      • 7.4.1.2 Scenario 2: Connectors Complement CPO (Moderate Impact)
      • 7.4.1.3 Scenario 3: Connectors Enable "Near-Packaged" Optics (Moderate CPO Impact)
      • 7.4.1.4 Scenario 4: Connector Development Delays (Positive CPO Impact)
    • 7.4.2 Detachable connectors
  • 7.5 Emerging Supply Chain Dynamics
    • 7.5.1 Geographic Concentration in CPO Supply Chains
    • 7.5.2 Laser and component supply chain
  • 7.6 Third-Party Suppliers and Systems Integrators
    • 7.6.1 Multi-Tier Supply Chain Architecture
      • 7.6.1.1 Tier 1: Silicon Photonics Platform
      • 7.6.1.2 Tier 2: CPO Assembly (OSAT)
      • 7.6.1.3 Tier 3: Fiber Array Unit (FAU) Suppliers
      • 7.6.1.4 Tier 4: External Laser Source (ELS) Suppliers
      • 7.6.1.5 Tier 5: Optical Fiber Supply
      • 7.6.1.6 Tier 6: Optical Sub-Assembly Integration
    • 7.6.2 Strategic Implications for Supply Chain Participants

8 COMPANY PROFILES (68 company profiles)

9 APPENDIX

  • 9.1 Research Methodology and Data Sources

10 REFERENCES

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