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Computing and AI for Data Centers: Global Market 2027-2040

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    Report

  • 315 Pages
  • September 2026
  • Region: Global
  • Future Markets, Inc
  • ID: 6232806
The market for computing and AI silicon in data centers covers the processors that do the work inside AI and cloud infrastructure: discrete GPUs, custom AI ASICs, server CPUs and data center FPGAs. What has changed since 2023 is not simply scale but structure. The server CPU, which accounted for the clear majority of this market in 2021, now represents a small fraction of it, while the GPU has moved from a minority position to dominance - the fastest reversal of category leadership in semiconductor history.

Recent activity has been defined by three developments. Custom silicon has moved from experiment to volume: Google's TPU, AWS Trainium, Meta's MTIA and Microsoft's MAIA together now ship millions of accelerators annually, and OpenAI's own programme is expected in volume from 2027. Merchant vendors have responded by selling systems rather than chips, with rack-scale platforms integrating 72 to 144 accelerators behind a single coherent fabric - a shift that raises the barrier to competing from designing a chip to delivering an entire rack, along with its power delivery, liquid cooling and system software. And the binding constraint has migrated from silicon to electricity: after packaging shortages in 2023 and high-bandwidth memory shortages through 2024 and 2025, grid interconnection and electrical equipment lead times now govern how quickly capacity can be commissioned.

The outlook to 2040 is for continued growth at a materially slower rate than the 2023-2027 period. Three findings shape that trajectory. Revenue keeps growing after units stop: accelerator shipments peak around 2032 while average selling prices rise more than five-fold across the period, meaning capacity sized against the revenue curve will be overbuilt. AI ASICs overtake GPUs on unit shipments in 2028 but never on revenue, because custom silicon displaces volume at the lower-value inference end while frontier training remains merchant territory. And the cost reductions driving demand come predominantly from model efficiency and serving software rather than from process scaling - meaning much of the value created accrues above the silicon layer.

Value in this chain is determined by position more than by execution. The constrained layers - leading-edge foundry, high-bandwidth memory, advanced packaging and custom silicon co-design - combine growth with genuine defensibility, while system assembly and the merchant accelerator start-up cohort face structurally weaker economics. Risks are concentrated rather than diffuse: power availability, packaging capacity, memory supply, and whether enterprise AI adoption converts from pilot to production at the rate the buildout assumes.

Computing and AI for Data Centers: Global Market 2027-2040 is a comprehensive market intelligence report on the semiconductors powering global AI and cloud infrastructure. The report covers chip designers, foundries, memory suppliers, packaging houses, equipment vendors, hyperscalers, model developers, systems manufacturers and infrastructure suppliers across the United States, Taiwan, South Korea, Japan, China and Europe.

Report contents include:

  • Executive summary and market definition
  • Global AI infrastructure investment and hyperscaler capital expenditure
  • Data center power constraints and regional capacity buildout
  • Export controls and the US-China technology divide
  • Processor market revenue forecasts to 2040: GPU, AI ASIC, server CPU, FPGA
  • Average selling price and unit volume forecasts by vendor and programme
  • Wafer, die and advanced packaging demand forecasts
  • Server tray and rack architecture forecasts
  • Cost of AI inference and training, and the token cost roadmap
  • Demand drivers: agentic AI, physical AI, recommendation, coding, search
  • Capital expenditure versus operating expenditure economics
  • Ecosystem, supply chain and co-designer relationship maps
  • Market share by revenue, units and deployment volume
  • Financial analysis of the leading chip designers
  • AI semiconductor start-up funding landscape
  • Mainland China market, manufacturers and supply chain
  • CPU, GPU and AI ASIC technology and roadmap analysis
  • HBM, advanced packaging and rack bill of materials
  • Emerging architectures: photonics, neuromorphic, quantum
  • Bull, base and bear scenarios to 2040, risks and investment outlook
  • 81 company profiles spanning the full data center supply chain

Table of Contents

1 EXECUTIVE SUMMARY
1.1 Global AI Infrastructure and Investment Landscape
1.2 Capital formation and the venture channel
1.3 US and Chinese Hyperscaler CapEx Trends and Projections
1.4 Power as the binding constraint
1.5 AI Regulatory Landscape and Export Controls
1.6 The US-China Technology Divide
2 MARKET FORECASTS
2.1 Processor Revenue Forecast
2.2 Average Selling Price (ASP) Forecast
2.3 Processor Volume Forecast
2.4 Wafer Forecast
2.5 Server Tray Volume Forecast
2.6 AI server rack architecture
2.7 CPU Focus
2.8 The Arm ramp
2.9 GPU & AI ASIC Focus
3 MARKET TRENDS
3.1 Cost of Generative AI Inference and Training
3.2 Why training costs what it does
3.3 From Agentic AI to Physical AI
3.4 Physical AI
3.5 Recommendation Models for Social Networks
3.6 Coding Assistants
3.7 Search Engine vs. LLM
3.8 OpenClaw
3.9 CapEx vs. OpEx in the Era of Generative AI
3.10 Is the Future of AI Data Centers in Space?
4 MARKET SHARE & SUPPLY CHAIN
4.1 Data Center Ecosystem Map
4.2 Foundation Models Ecosystem Map
4.3 U.S. vs. China Tech War - Timeline
4.4 Financial Metrics of Data Center Chip Designers
4.5 AI semiconductor start-up fundraising
4.6 Case Study: OpenAI Revenue and Gigawatt
4.7 Market Share: CPU, GPU, AI ASIC & XPU Co-Designers
4.8 Focus on China
5 TECHNOLOGY ANALYSIS
5.1 CPU Technology Trends
5.2 GPU Technology Trends
5.3 AI ASIC Technology Trends
5.4 GPU vs. AI ASIC: Comparative Analysis
5.5 Advanced Packaging and HBM Memory
5.6 Emerging Computing Architectures
6 OUTLOOK & SCENARIOS
6.1 Market Outlook 2026-2040
6.2 Technology Outlook 2026-2040
6.3 Key Risks and Opportunities
6.4 Strategic Recommendations
7 COMPANY PROFILES (81 company profiles)
8 REPORT METHODOLOGY
8.1 Objective of the report
8.2 Scope of this report
9 GLOSSARY OF TERMS AND ABBREVIATIONS10 REFERENCES
LIST OF TABLES
Table 1. Global AI Infrastructure Investment by Category, 2021-2040 ($B)
Table 2. US Early-Stage Venture Deployment in AI and Adjacent Technologies, 2016-2026 YTD
Table 3. Early-stage round size and investor concentration, 2026 YTD
Table 4. US vs. Chinese Hyperscaler CapEx, 2021-2040 ($B)
Table 5. Data Center Installed IT Load by Workload Type, 2024-2040 (GW)
Table 6. Data Center Processor Market Revenue Summary, 2021-2040 ($B)
Table 7. Revenue Breakdown by Processor Type (CPU, GPU, AI ASIC, FPGA), 2021-2040
Table 8. GPU Revenue by Vendor, 2021-2040 ($B)
Table 9. Nvidia GPU Revenue by Product Generation, 2021-2028 ($B)
Table 10. AMD GPU Revenue by Product Generation, 2021-2028 ($B)
Table 11. AI ASIC Revenue by Hyperscaler, 2021-2040 ($B)
Table 12. Server CPU Revenue by Vendor, 2021-2040 ($B)
Table 13. FPGA Data Center Revenue Forecast, 2021-2040 ($M)
Table 14. GPU ASP by Product Tier, 2021-2040 ($K per unit)
Table 15. AI ASIC ASP by Hyperscaler, 2021-2040 ($K per unit)
Table 16. Server CPU ASP Trends - Intel Xeon vs. AMD EPYC, 2021-2040 ($)
Table 17. GPU Unit Shipments by Vendor, 2021-2040 (K units)
Table 18. Nvidia GPU Unit Shipments by Product Generation, 2021-2028 (K units)
Table 19. AMD GPU Unit Shipments by Product Generation, 2021-2028 (K units)
Table 20. AI ASIC Unit Shipments by Hyperscaler, 2021-2040 (K units)
Table 21. CPU Unit Shipments by Vendor, 2021-2040 (M units)
Table 22. Hyperscaler Custom CPU Unit Adoption, 2022-2040 (M units)
Table 23. GPU & AI ASIC Wafer Starts by Node and Foundry, 2021-2040 (KWPM, 300mm equivalent)
Table 24. Average Die Size Trend - GPU vs. AI ASIC, 2021-2040 (mm2)
Table 25. HBM Revenue Separated from GPU & AI ASIC Total, 2021-2040 ($B)
Table 26. AI Server vs. General-Purpose Server Tray Volume, 2021-2040 (M units)
Table 27. AI Server Rack Configuration and Architecture, 2025-2040
Table 28. CPU Market Share by Revenue: Intel vs. AMD vs. Arm-based, 2021-2040
Table 29. Hyperscaler Arm CPU Deployment Ramp, 2022-2040
Table 30. CPU Processor Roadmap Summary - Major Vendors, 2024-2030
Table 31. GPU Market Share by Revenue, 2021-2040 (%)
Table 32. AI ASIC Market Share by Deployment Volume, 2021-2040 (%)
Table 33. GPU & AI ASIC Split by Technology Node, 2021-2040
Table 34. GPU & AI ASIC Product Roadmap Summary, 2024-2030
Table 35. Cost per Token Trend: Training and Inference, 2021-2040 ($/M tokens)
Table 36. Cost per Token by Model Size and Hardware Configuration, 2024-2040 ($/M output tokens)
Table 37. Cost per Token Trend: Training and Inference, 2021-2040 ($/M tokens)
Table 38. Inference Cost Breakdown by Infrastructure Component, 2025 (%)
Table 39. AI Model Parameter Count vs. Hardware Requirements, 2020-2028
Table 40. Agentic AI Use Cases by Industry and Hardware Requirements
Table 41. AI Agent Deployment Forecast by Sector, 2025-2040 (M concurrently deployed agents)
Table 42. Physical AI Hardware Requirements vs. Generative AI, 2025-2040
Table 43. Robotics Semiconductor Market Forecast, 2024-2040 ($B)
Table 44. Recommendation Model Architecture Evolution, 2018-2028
Table 45. Recommendation Model Compute Demand by Platform, 2024-2040 ($B)
Table 46. AI-Powered Coding Assistant Market Share, 2024-2028 (%)
Table 47. Coding Assistant Market Share and Underlying Infrastructure
Table 48. Coding AI GPU Compute Demand, 2024-2040 ($B)
Table 49. LLM vs. Traditional Search: Query Volume Forecast, 2022-2040 (B queries/day)
Table 50. AI Search Compute Infrastructure Requirements, 2024-2040
Table 51. CapEx Cycle: US Hyperscalers, 2015-2040 ($B)
Table 52. CapEx-to-Revenue Ratio: Major Hyperscalers, 2020-2040 (%)
Table 53. AI Infrastructure OpEx vs. CapEx Split, 2024-2040
Table 54. Cloud AI Chip Rental vs. Ownership Economics, 2025-2040
Table 55. Low Earth Orbit Latency and Bandwidth Projections, 2025-2035
Table 56. AI Chip Supply Chain: From Silicon to Hyperscaler
Table 57. Foundation Model Training Infrastructure by Developer
Table 58. Chinese AI Chip Import Replacement Progress, 2022-2028 (%)
Table 59. Sanctioned vs. Unsanctioned Chinese AI Chip Revenues, 2022-2028 ($B)
Table 60. Financial Metrics: Top 10 Data Center Chip Designers, 2021-2025
Table 61. Gross Margin Comparison: Nvidia vs. AMD vs. Intel, 2020-2025 (%)
Table 62. R&D Spend as % of Revenue: Key Chip Designers, 2020-2025
Table 63. US and Chinese Hyperscaler CapEx Summary, 2021-2026 ($B)
Table 64. AI Semiconductor Start-Up Fundraising, 2019-Q1 2026 ($M)
Table 65. AI Semiconductor Start-Up Fundraising Database, 2019-Q1 2026
Table 66. OpenAI Revenue Forecast, 2023-2030 ($B)
Table 67. OpenAI Compute Demand (Gigawatt), 2023-2030
Table 68. OpenAI GPU Procurement Forecast by Generation, 2023-2028 (K units)
Table 69. GPU Market Share Summary by Revenue and Units, 2021-2025
Table 70. Nvidia, AMD, Google, AWS GPU/ASIC Unit Split, 2021-2028 (K units)
Table 71. AI ASIC Market Share by Hyperscaler, 2021-2025 (%)
Table 72. AI ASIC Specifications: Google, AWS, Microsoft, Meta, 2024-2026
Table 73. CPU Market Share by Revenue: Intel vs. AMD vs. Arm, 2021-2025 (%)
Table 74. Hyperscaler Custom CPU Market Share Evolution, 2022-2028
Table 75. Co-Designer Revenue Share, 2021-2026 (%)
Table 76. China Data Center Processor Market by Type, 2021-2030 ($B)
Table 77. Chinese Hyperscaler Processor Demand, 2021-2028 ($B)
Table 78. Domestic Chinese AI Chip Makers: Unit Share, 2022-2028 (%)
Table 79. Chinese AI Chip Makers: Product Specifications and Capabilities
Table 80. China Data Center Semiconductor Supply Chain Map
Table 81. CPU Architecture Comparison: x86, Arm, RISC-V for the Data Center
Table 82. CPU Specifications: Intel, AMD, AWS, Google, Microsoft, Huawei, Nvidia, 2024-2026
Table 83. Arm Server CPU Shipment Forecast, 2022-2040 (M units)
Table 84. RISC-V Data Center Adoption Forecast, 2025-2040
Table 85. CPU Specialization for AI Inference Workloads
Table 86. GPU Specifications: Nvidia Blackwell, Rubin; AMD MI350X, MI450, 2024-2026
Table 87. GPU Die Size Evolution and Chiplet Transition, 2020-2030 (mm2)
Table 88. Rack-Scale GPU Architecture: NVL72 and Next-Generation Platforms
Table 89. GPU Memory Bandwidth Trend: HBM Generations, 2020-2030 (TB/s)
Table 90. NVLink and Interconnect Bandwidth Evolution, 2020-2030
Table 91. AI ASIC Technology Specification Database
Table 92. GPU vs. AI ASIC: Performance per Watt Comparison, 2022-2026
Table 93. GPU vs. AI ASIC: Training vs. Inference Suitability Matrix
Table 94. GPU vs. AI ASIC: Total Cost of Ownership Analysis
Table 95. HBM Specification Comparison: HBM2E, HBM3, HBM3E, HBM4
Table 96. CoWoS Capacity Expansion Roadmap: TSMC, 2022-2028 (KWPM)
Table 97. Advanced Packaging Market Share: CoWoS, SoIC, Others, 2024-2028 (%)
Table 98. AI Server Rack BoM: Itemized Cost Breakdown, 2025 ($K)
Table 99. AI Rack BoM Cost Evolution, 2023-2028 ($K)
Table 100. Silicon Photonics Market Forecast in Data Centers, 2024-2040 ($B)
Table 101. Neuromorphic Computing Roadmap, 2024-2040
Table 102. Quantum Computing Timeline to Commercial Viability, 2025-2040
Table 103. Emerging Computing Technology Readiness Assessment
Table 104. Market Forecast Summary: Bull / Base / Bear Scenarios, 2026-2040 ($B)
Table 105. Bull, Base, Bear Case Revenue Scenarios by Processor Type, 2040
Table 106. Technology Roadmap Summary: CPU, GPU, AI ASIC, 2026-2040
Table 107. Key Risk Register: Probability and Impact Assessment
Table 108. Investment Opportunity Map: Data Center Semiconductor Ecosystem
LIST OF FIGURES
Figure 1. Global AI Infrastructure Investment Forecast, 2021-2040 ($B)
Figure 2. US vs. Chinese Hyperscaler CapEx, 2021-2040 ($B)
Figure 3. Data Center Power Consumption Forecast, 2024-2040 (GW installed IT load)
Figure 4. AI-Related Data Center Construction Starts by Region, 2022-2028 (GW of IT capacity)
Figure 5. US Export Controls on AI Chips: Key Milestones, 2019-2026
Figure 6. US-China Technology Decoupling Timeline, 2018-2026
Figure 7. Total Data Center Processor Market Revenue Forecast, 2021-2040 ($B)
Figure 8. Revenue Breakdown by Processor Type (CPU, GPU, AI ASIC, FPGA), 2021-2040
Figure 9. Data Center Processor CAGR by Category, 2025-2040 (%)
Figure 10. GPU Market Revenue Forecast, 2021-2040 ($B)
Figure 11. GPU Revenue Split by Vendor (Nvidia, AMD, Others), 2021-2040
Figure 12. Nvidia GPU Revenue by Product Generation, 2021-2028 ($B)
Figure 13. AMD GPU Revenue by Product Generation, 2021-2028 ($B)
Figure 14. AI ASIC Market Revenue Forecast, 2021-2040 ($B)
Figure 15. AI ASIC Revenue Split by Hyperscaler, 2021-2040
Figure 16. Server CPU Market Revenue Forecast, 2021-2040 ($B)
Figure 17. Server CPU Revenue Split by Architecture (x86 vs. Arm), 2021-2040
Figure 18. FPGA Data Center Revenue Forecast, 2021-2040 ($M)
Figure 19. GPU ASP Evolution by Product Tier, 2021-2040 ($K)
Figure 20. AI ASIC ASP Trends by Hyperscaler, 2021-2040 ($K)
Figure 21. Server CPU ASP Trends - Intel Xeon vs. AMD EPYC, 2021-2040 ($)
Figure 22. GPU Unit Shipments by Vendor, 2021-2040 (K units)
Figure 23. Nvidia GPU Unit Shipments by Product Generation, 2021-2028 (K units)
Figure 24. AMD GPU Unit Shipments by Product Generation, 2021-2028 (K units)
Figure 25. AI ASIC Unit Shipments by Hyperscaler, 2021-2040 (K units)
Figure 26. Google TPU Unit Deployment Forecast, 2021-2040 (K units)
Figure 27. AWS Trainium & Inferentia Unit Forecast, 2021-2040 (K units)
Figure 28. Microsoft MAIA Unit Forecast, 2021-2040 (K units)
Figure 29. CPU Unit Shipments - Data Center, 2021-2040 (M units)
Figure 30. Intel vs. AMD CPU Market Share in Unit Terms, 2021-2040 (%)
Figure 31. Hyperscaler Custom CPU Unit Adoption, 2022-2040 (M units)
Figure 32. GPU & AI ASIC Wafer Starts by Technology Node, 2021-2040 (KWPM)
Figure 33. Wafer Consumption Split: Advanced Nodes, 2021-2040
Figure 34. GPU & AI ASIC Wafer Starts by Foundry, 2021-2040
Figure 35. TSMC Advanced Node Capacity Forecast, 2024-2040 (KWPM)
Figure 36. GPU & AI ASIC Compute Die Forecast, 2021-2040
Figure 37. Average Die Size Trend - GPU vs. AI ASIC, 2021-2040 (mm2)
Figure 38. HBM Revenue Separated from GPU & AI ASIC Total, 2021-2040 ($B)
Figure 39. AI Server vs. General-Purpose Server Tray Volume, 2021-2040 (M units)
Figure 40. AI Server Rack Configuration and Architecture, 2025-2040
Figure 41. CPU Market Share by Revenue: Intel vs. AMD vs. Arm-based, 2021-2040
Figure 42. Hyperscaler Arm CPU Deployment Ramp, 2022-2040
Figure 43. CPU Product Roadmap: Intel, AMD, Arm, Google, AWS, Nvidia, 2024-2030
Figure 44. GPU Market Share by Revenue, 2021-2040 (%)
Figure 45. AI ASIC Market Share by Deployment Volume, 2021-2040 (%)
Figure 46. GPU & AI ASIC Split by Technology Node, 2021-2040
Figure 47. Cost per Token Trend: Training and Inference, 2021-2040 ($/M tokens)
Figure 48. Training Compute Requirements by Model Type, 2020-2028 (FLOPs)
Figure 49. Inference Cost Breakdown by Infrastructure Component, 2025 (%)
Figure 50. Token Cost Reduction Roadmap, 2025-2040
Figure 51. AI Model Parameter Count vs. Hardware Requirements, 2020-2028
Figure 52. Agentic AI Market Taxonomy and Use Cases
Figure 53. AI Agent Deployment Forecast by Sector, 2025-2040 (M concurrently deployed agents)
Figure 54. Physical AI Hardware Requirements vs. Generative AI, 2025-2040
Figure 55. Robotics Semiconductor Market Forecast, 2024-2040 ($B)
Figure 56. Recommendation Model Architecture Evolution, 2018-2028
Figure 57. Recommendation Model Compute Demand by Platform, 2024-2040 ($B)
Figure 58. AI-Powered Coding Assistant Market Share, 2024-2028 (%)
Figure 59. Coding AI GPU Compute Demand, 2024-2040 ($B)
Figure 60. LLM vs. Traditional Search: Query Volume Forecast, 2022-2040 (B queries/day)
Figure 61. AI Search Compute Infrastructure Requirements, 2024-2040
Figure 62. CapEx Cycle: US Hyperscalers, 2015-2040 ($B)
Figure 63. CapEx-to-Revenue Ratio: Major Hyperscalers, 2020-2040 (%)
Figure 64. AI Infrastructure OpEx vs. CapEx Split, 2024-2040
Figure 65. Cloud AI Chip Rental vs. Ownership Economics, 2025-2040
Figure 66. Space-Based Data Center Conceptual Architecture
Figure 67. Low Earth Orbit Latency and Bandwidth Projections, 2025-2035
Figure 68. Global Data Center Processor Ecosystem Map
Figure 69. AI Chip Supply Chain: From Silicon to Hyperscaler
Figure 70. Co-Designer and Hyperscaler Relationship Map
Figure 71. OSAT and Advanced Packaging Supply Chain Map
Figure 72. Foundation Models Ecosystem Map: Developers and Infrastructure
Figure 73. Open vs. Closed Source AI Model Landscape, 2024
Figure 74. Foundation Model Training Infrastructure by Developer
Figure 75. US Export Control Timeline: Semiconductors, 2018-2026
Figure 76. Chinese AI Chip Import Replacement Progress, 2022-2028 (%)
Figure 77. Sanctioned vs. Unsanctioned Chinese AI Chip Revenues, 2022-2028 ($B)
Figure 78. Comparative Revenue: Data Center Chip Designers, 2021-2025 ($B)
Figure 79. Gross Margin Comparison: Nvidia vs. AMD vs. Intel, 2020-2025 (%)
Figure 80. R&D Spend as % of Revenue: Key Chip Designers, 2020-2025
Figure 81. AI Semiconductor Start-Up Fundraising, 2019-Q1 2026 ($M)
Figure 82. OpenAI Revenue Forecast, 2023-2030 ($B)
Figure 83. OpenAI Compute Demand (Gigawatt), 2023-2030
Figure 84. OpenAI GPU Procurement Forecast by Generation, 2023-2028 (K units)
Figure 85. GPU Market Share by Revenue, 2021-2025 (%)
Figure 86. GPU Market Share by Units, 2021-2025 (%)
Figure 87. Nvidia, AMD, Google, AWS GPU/ASIC Unit Split, 2021-2028 (K units)
Figure 88. AI ASIC Market Share by Hyperscaler, 2021-2025 (%)
Figure 89. CPU Market Share by Revenue: Intel vs. AMD vs. Arm, 2021-2025 (%)
Figure 90. Hyperscaler Custom CPU Market Share Evolution, 2022-2028
Figure 91. XPU Co-Designer Revenue, 2023-2026 ($B)
Figure 92. XPU Co-Designer Revenue Share, 2021-2026 (%)
Figure 93. China Data Center Processor Market Size, 2021-2025 ($B)
Figure 94. Chinese Hyperscaler Processor Demand, 2021-2028 ($B)
Figure 95. Domestic Chinese AI Chip Makers: Unit Share, 2022-2028 (%)
Figure 96. HiSilicon, Cambricon, Baidu Kunlun, Hygon Roadmap, 2024-2028
Figure 97. China Data Center Semiconductor Supply Chain Map
Figure 98. CPU Architecture Comparison: x86, Arm, RISC-V for the Data Center
Figure 99. Arm Server CPU Shipment Forecast, 2022-2040 (M units)
Figure 100. RISC-V Data Center Adoption Forecast, 2025-2040
Figure 101. CPU Specialization for AI Inference Workloads
Figure 102. GPU Process Node Roadmap: Nvidia, AMD, 2020-2030
Figure 103. GPU Die Size Evolution and Chiplet Transition, 2020-2030 (mm2)
Figure 104. Rack-Scale GPU Architecture: NVL72 and Next-Generation Platforms
Figure 105. GPU Memory Bandwidth Trend: HBM Generations, 2020-2030 (TB/s)
Figure 106. NVLink and Interconnect Bandwidth Evolution, 2020-2030
Figure 107. Hyperscaler ASIC Roadmap Comparison: Google, AWS, Microsoft, Meta
Figure 108. AI ASIC Start-Up Landscape by Funding Stage, 2024
Figure 109. AI ASIC Technology Specification Matrix
Figure 110. Disaggregated Inference Architecture Diagram
Figure 111. GPU vs. AI ASIC: Performance per Watt Comparison, 2022-2026
Figure 112. GPU vs. AI ASIC: Training vs. Inference Suitability Matrix
Figure 113. GPU vs. AI ASIC: Total Cost of Ownership Analysis
Figure 114. HBM Technology Roadmap: HBM2E to HBM4, 2020-2028
Figure 115. HBM Bandwidth and Capacity per Stack by Generation, 2020-2028
Figure 116. CoWoS Capacity Expansion Roadmap: TSMC, 2022-2028 (KWPM)
Figure 117. Advanced Packaging Market Share: CoWoS, SoIC, Others, 2024-2028 (%)
Figure 118. Custom HBM Co-Design Relationships Map
Figure 119. AI Server Rack Bill of Materials: Component Breakdown, 2025 ($K)
Figure 120. AI Rack BoM Cost Evolution, 2023-2028 ($K)
Figure 121. Silicon Photonics Market Forecast in Data Centers, 2024-2040 ($B)
Figure 122. Neuromorphic Computing Roadmap, 2024-2040
Figure 123. Quantum Computing Timeline to Commercial Viability, 2025-2040
Figure 124. Data Center Processor Market Scenario Analysis, 2026-2040 ($B)
Figure 125. Bull, Base, Bear Case Revenue Scenarios by Processor Type, 2040
Figure 126. Technology Roadmap Summary: CPU, GPU, AI ASIC, 2026-2040
Figure 127. Competitive Landscape Risk Matrix, 2026-2040
Figure 128. Investment Opportunity Map: Data Center Semiconductor Ecosystem

Companies Mentioned (Partial List)

A selection of companies mentioned in this report includes, but is not limited to:

  • Advanced Micro Devices (AMD)
  • Alchip Technologies
  • Alibaba (T-Head Semiconductor)
  • Alphawave Semi
  • Amazon Web Services (Annapurna Labs)
  • Amkor Technology
  • Ampere Computing
  • Analog Devices
  • Applied Materials
  • Arm Holdings
  • ASE Technology Holding
  • ASML Holding
  • Astera Labs
  • Axelera AI
  • Baidu (Kunlun)
  • Biren Technology
  • Broadcom
  • Cadence Design Systems
  • Cambricon Technologies
  • Celestica
  • Cerebras Systems
  • Cisco Systems
  • Coherent Corp
  • CoreWeave
  • Credo Technology Group
  • ChangXin Memory Technologies (CXMT)
  • d-Matrix
  • Delta Electronics
  • Dell Technologies
  • Eaton Corporation
  • Enflame Technology
  • Etched
  • Foxconn (Hon Hai Precision Industry)
  • FuriosaAI
  • GlobalFoundries
  • Google (Alphabet)
  • Groq
  • Global Unichip Corporation (GUC)
  • Hewlett Packard Enterprise
  • Hygon Information Technology
  • Ibiden
  • Iluvatar CoreX
  • Infineon Technologies
  • Innolight Technology
  • Intel Corporation
  • JCET Group
  • KLA Corporation
  • Lam Research
  • Lightmatter
  • Lumentum Holdings
  • Marvell Technology
  • MediaTek
  • Meta Platforms
  • Micron Technology
  • Microsoft
  • Monolithic Power Systems
  • Moore Threads
  • Nebius Group
  • NVIDIA Corporation
  • onsemi
  • OpenAI
  • Powertech Technology
  • Quanta Computer
  • Rambus
  • Rebellions
  • Renesas Electronics
  • Samsung Electronics
  • SambaNova Systems
  • Schneider Electric
  • Shinko Electric Industries
  • SiPearl
  • SK Hynix
  • Semiconductor Manufacturing International Corporation (SMIC)
  • Super Micro Computer
  • Synopsys
  • Tenstorrent
  • Tokyo Electron
  • Taiwan Semiconductor Manufacturing Company (TSMC)
  • Unimicron Technology
  • Vertiv Holdings
  • Wistron Corporation