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2149744

資料中心GPU市場預測（2034年）－全球分析（依GPU類型、GPU架構、外形尺寸、散熱方式、功能、部署模式、資料中心類型、記憶體技術、應用、最終用戶與地區分類）

Data Center GPU Market Forecasts To 2034 - Global Analysis By GPU Type, GPU Architecture, Form Factor, Cooling Type, Function, Deployment, Data Center Type, Memory Technology, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

全球資料中心 GPU 市場預計到 2026 年將達到 1,505 億美元，並在預測期內以 28.5% 的複合年成長率成長，到 2034 年將達到 1.1,186 兆美元。

資料中心GPU市場涵蓋專為資料中心高要求應用而開發的圖形處理技術，這些應用包括人工智慧、機器學習、高效能運算、雲端服務、科學運算和分析。這些GPU支援處理大規模資料集和複雜計算模型所需的廣泛平行計算。該市場包括GPU硬體、軟體生態系統、記憶體解決方案、網路技術和相關基礎設施。主要應用包括人工智慧訓練和推理、加速運算、模擬、虛擬化和企業資料處理。競爭格局包括GPU製造商、雲端平台以及提供專業架構和解決方案以滿足高階資料中心運算需求的技術公司。

日益成長的數據處理需求

隨著企業、連網設備、數位服務和軟體應用產生的資料量不斷成長，資料中心對高速處理的需求也日益增加。企業需要分析大量資料集，以支援商業智慧、網路安全、客戶洞察、建議引擎和即時營運決策。 GPU 可同時執行大量資料處理操作，在運算密集分析和處理工作負載方面與 CPU 形成互補。隨著以資料為中心的應用日益普及，企業和基礎設施供應商正在採用高速運算系統來滿足處理需求。因此，高效分析和處理大規模資料集的需求不斷成長，推動了 GPU 技術與資料中心基礎設施的進一步整合。

資料中心GPU高成本

高效能資料中心GPU需要大量投資，這可能會限制其在組織內的部署。 GPU專為人工智慧、機器學習和高效能運算等領域的高要求工作負載而設計，其採購成本通常高於標準運算元件。此外，部署成本不僅限於GPU本身，還包括專用伺服器、進階記憶體、高速網路、溫度控管、電源基礎設施和支援軟體。這些需求會顯著增加基於GPU的運算環境的總支出。對於預算有限的中小型企業和組織而言，大規模部署GPU面臨許多挑戰，尤其是在工作負載利用率不足以支撐所需的大量基礎設施和設備投資的情況下。

GPU與先進網路和記憶體技術的整合

將GPU與先進的記憶體和網路技術結合，為開發更高效能的資料中心運算平台創造了機會。人工智慧和高效能應用涉及處理器、記憶體、儲存和網路元件之間頻繁的大量資訊交換。 GPU製造商可以與記憶體供應商、網路公司、半導體開發商和基礎設施供應商合作，建立整合系統，該系統包含高頻寬記憶體、高速互連、先進網路和最佳化軟體。這些組件之間更有效率的協調能夠實現大規模加速器叢集之間的通訊，並處理高負載任務。這一趨勢促進了策略合作、生態系統發展和整合平台的交付，使技術供應商能夠為資料密集型應用提供全面的加速運算基礎設施。

快速的技術競爭與產品替代

計算和半導體技術的快速創新可能會增加資料中心GPU更換的風險。新型處理器架構、專用AI晶片、客製化加速器、神經形態技術和其他新興解決方案都是為特定運算工作負載而設計的。這些替代技術的進步可能使某些應用程式無需嚴重依賴傳統GPU即可滿足效能要求。因此，資料中心營運商可能會根據工作負載適用性、功耗需求、軟體支援和整體基礎設施成本來比較多種處理器架構。技術的快速變革也可能縮短現有解決方案的有效使用壽命，要求GPU公司在研發、架構開發、軟體平台和持續產品創新方面保持大量投資。

新型冠狀病毒（COVID-19）的影響：

新冠疫情加速了數位化進程，增加了遠距辦公，擴大了雲端運算應用範圍，並提高了對線上平台的依賴，從而對資料中心GPU市場產生了影響。企業和機構紛紛採用雲端基礎設施、虛擬通訊、數位服務和資料密集型應用，這增加了對運算資源和資料中心容量的需求。然而，疫情帶來的限制擾亂了半導體生產、運輸網路、組件採購和硬體交付，阻礙了GPU的供應和基礎設施的擴展。資料中心營運商也因人員短缺和設施限制而面臨營運挑戰。因此，新冠疫情凸顯了先進運算基礎設施的重要性，同時也為GPU製造商和資料中心營運商帶來了供應鏈和部署的難題。

在預測期內，獨立GPU細分市場預計將佔據最大的市場佔有率。

預計在預測期內，獨立GPU將佔據最大的市場佔有率，這主要得益於其專用的處理資源、高效能以及對運算密集型資料中心應用的適用性。與整合解決方案不同，獨立GPU獨立於CPU運行，為人工智慧、機器學習、分析、高效能運算和科學運算等工作負載提供廣泛的平行處理能力。多GPU配置的可擴展性使資料中心能夠有效率地滿足嚴苛的運算需求。對高速處理、高階AI模型、大規模資料集和專用運算基礎設施日益成長的需求，正在推動獨立GPU在高階資料中心環境中的廣泛應用。

在預測期內，生成式人工智慧細分市場預計將呈現最高的複合年成長率。

在預測期內，生成式人工智慧領域預計將呈現最高的成長率，這主要得益於大規模語言模型、多模態系統、人工智慧生成內容以及高階人工智慧應用的日益普及。這些工作負載需要強大的運算能力來進行訓練、模型最佳化、微調和推理，推動了資料中心基礎架構對高效能GPU的需求。雲端服務供應商、科技公司、大型企業和研究機構正在開發加速運算環境，以處理日益複雜的人工智慧模型。生成式人工智慧在軟體開發、客戶支援、內容創作、醫療保健、金融服務和其他應用中的廣泛應用，正在推動對專用GPU基礎設施的投資，以支援高要求、高運算密集的人工智慧工作負載。

市佔率最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率，這得益於其龐大的資料中心生態系統、眾多領先科技公司的聚集以及雲端運算和人工智慧技術的廣泛應用。該地區作為成熟的GPU供應商、半導體製造商、雲端平台和大型資料中心營運商，充分發揮自身優勢。生成式人工智慧、機器學習、高效能運算、分析和其他高要求工作負載的日益普及，正在推動GPU加速基礎設施的使用。超大規模設施的存在以及對先進計算系統的持續投資，進一步增強了該地區的需求。此外，成熟的數位基礎設施、技術專長和完善的技術生態系統也鞏固了北美在市場上的主導地位。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率，這主要得益於資料中心容量的提升、雲端服務的擴展以及人工智慧技術的普及。該地區各國正大力發展超大規模資料中心、人工智慧專用基礎設施和先進的數位平台，從而推動了對GPU加速運算資源的需求成長。生成式人工智慧、機器學習、分析和高效能運算等應用的不斷擴展，正在加速企業採用先進的加速器解決方案。企業和公共部門組織數位轉型的加速也進一步提升了基礎設施需求。此外，技術生態系統的發展以及對半導體製造和資料中心設施的投資，也全部區域GPU的普及創造了有利條件。

免費客製化服務：

所有購買此報告的客戶均可享受以下免費自訂選項之一：

  • 企業概況
    • 對其他市場參與者（最多 3 家公司）進行全面分析
    • 對主要公司進行SWOT分析（最多3家公司）
  • 區域細分
    • 根據客戶的興趣，我們將提供主要國家的市場估算和預測，以及複合年成長率（註：需經可行性確認）。
  • 競爭性標竿分析
    • 根據產品系列、地理覆蓋範圍和策略聯盟對領先公司進行基準分析。

目錄

第1章執行摘要

  • 市場概覽及主要亮點
  • 促進因素、挑戰與機遇
  • 競爭格局概述
  • 戰略洞察與建議

第2章：研究框架

  • 研究目標和範圍
  • 相關人員分析
  • 研究假設和限制
  • 調查方法

第3章 市場動態與趨勢分析

  • 市場定義與結構
  • 主要市場促進因素
  • 市場限制與挑戰
  • 投資成長機會和重點領域
  • 產業威脅與風險評估
  • 技術與創新展望
  • 新興市場/高成長市場
  • 監管和政策環境
  • 新冠疫情的影響及復甦前景

第4章：競爭環境與策略評估

  • 波特五力分析
    • 供應商的議價能力
    • 買方的議價能力
    • 替代品的威脅
    • 新進入者的威脅
    • 競爭公司之間的競爭
  • 主要公司市佔率分析
  • 產品基準評效和效能比較

第5章：全球資料中心GPU市場：依GPU類型分類

  • 獨立顯示卡
  • 整合顯示卡
  • 混合GPU

第6章：全球資料中心GPU市場：依GPU架構分類

  • 基於 CUDA 的架構
  • 基於cDNA的結構
  • 基於氙氣的架構
  • 其他GPU架構

第7章 全球資料中心GPU市場：依外形規格

  • 單槽顯示卡
  • 雙槽顯示卡
  • 多槽顯示卡
  • SXM模組
  • 機架級GPU系統

第8章：全球資料中心GPU市場：以散熱類型分類

  • 空冷式
  • 液冷
  • 浸沒式冷卻

第9章：全球資料中心GPU市場：依功能分類

  • 人工智慧訓練
  • 人工智慧推理
  • 高效能運算
  • 圖形和視覺化
  • 媒體和視訊處理

第10章：全球資料中心GPU市場：依部署方式分類

  • 雲
  • 現場

第11章 全球資料中心GPU市場：依資料中心類型分類

  • 超大規模資料中心
  • 企業資料中心
  • 託管資料中心
  • 邊緣資料中心

第12章 全球資料中心GPU市場：依記憶體技術分類

  • HBM
  • GDDR
  • 其他儲存技術

第13章：全球資料中心GPU市場：按應用領域分類

  • 人工智慧世代
  • 機器學習
  • 資料分析
  • 高效能運算
  • 圖形渲染
  • 媒體處理
  • 虛擬化和虛擬桌面基礎架構 (VDI)

第14章 全球資料中心GPU市場：依最終用戶分類

  • 雲端服務供應商
  • 公司
  • 政府和研究機構

第15章 全球資料中心GPU市場：按地區分類

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 荷蘭
    • 比利時
    • 瑞典
    • 瑞士
    • 波蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 泰國
    • 馬來西亞
    • 新加坡
    • 越南
    • 其他亞太國家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 智利
    • 秘魯
    • 其他南美國家
  • 世界其他地區（RoW）
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 以色列
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲國家

第16章 策略市場資訊

  • 工業價值網路和供應鏈評估
  • 空白區域和機會地圖
  • 產品演進與市場生命週期分析
  • 通路、經銷商和打入市場策略的評估

第17章 產業趨勢與策略舉措

  • 併購
  • 夥伴關係、聯盟和合資企業
  • 新產品發布和認證
  • 擴大生產能力和投資
  • 其他策略舉措

第18章：公司簡介

  • Intel Corporation
  • Advanced Micro Devices, Inc.
  • NVIDIA Corporation
  • Huawei Technologies Co., Ltd.
  • Biren Technology
  • Moore Threads Technology Co., Ltd.
  • Iluvatar CoreX
  • Cambricon Technologies Corporation Limited
  • Jingjia Microelectronics Co., Ltd.
  • Enflame Technology Co., Ltd.
  • MetaX Integrated Circuits Co., Ltd.
  • Alibaba Group Holding Limited
  • Baidu, Inc.
  • Fujitsu Limited
  • IBM Corporation
  • Lenovo Group Limited
  • Inspur Group
  • Foxconn Industrial Internet Co., Ltd.
Product Code: SMRC40146

According to Stratistics MRC, the Global Data Center GPU Market is accounted for $150.5 billion in 2026 and is expected to reach $1118.6 billion by 2034 growing at a CAGR of 28.5% during the forecast period. The Data Center GPU Market covers graphics processing technologies developed for intensive data center applications, including artificial intelligence, machine learning, high-performance computing, cloud services, scientific workloads, and analytics. These GPUs enable extensive parallel computation for processing large datasets and complex computational models. The market incorporates GPU hardware, software ecosystems, memory solutions, networking technologies, and related infrastructure. Major applications include AI training and inference, accelerated computing, simulation, virtualization, and enterprise data processing. The competitive landscape includes GPU manufacturers, cloud platforms, and technology companies offering specialized architectures and solutions for advanced data center computing requirements.

Market Dynamics:

Driver:

Increasing Data Processing Requirements

The expanding quantity of data produced by businesses, connected devices, digital services, and software applications is increasing the need for accelerated processing within data centers. Companies must analyze extensive datasets to support business intelligence, cybersecurity, customer insights, recommendation engines, and real-time operational decisions. GPUs can perform large numbers of data-processing operations concurrently, complementing CPUs in computationally intensive analytics and processing workloads. As data-centric applications become increasingly widespread, enterprises and infrastructure providers are adopting accelerated computing systems to address processing requirements. The growing necessity for efficient analysis and handling of large datasets is consequently supporting greater integration of GPU technologies into data center infrastructure.

Restraint:

High Cost of Data Center GPUs

The substantial investment required for sophisticated data center GPUs can limit their adoption across organizations. GPUs designed for intensive AI, machine learning, and high-performance computing workloads generally involve higher procurement costs than standard computing components. Deployment expenses can also extend beyond the GPU itself, encompassing specialized servers, advanced memory, high-speed networking, thermal management, electricity infrastructure, and supporting software. These requirements can significantly increase the overall expenditure associated with GPU-based computing environments. Small and medium-sized businesses or organizations operating with constrained budgets may find large GPU deployments challenging, especially when their workloads do not provide sufficient utilization to justify the considerable infrastructure and equipment investment required.

Opportunity:

Integration of GPUs with Advanced Networking and Memory Technologies

Combining GPUs with advanced memory and networking technologies creates opportunities for developing more capable data center computing platforms. AI and high-performance applications frequently transfer substantial quantities of information among processors, memory, storage, and networking components. GPU manufacturers can work with memory suppliers, networking companies, semiconductor developers, and infrastructure providers to create integrated systems incorporating high-bandwidth memory, fast interconnects, advanced networking, and optimized software. Improved coordination among these components can support communication across large accelerator clusters and demanding workloads. This trend can encourage strategic collaboration, ecosystem development, and integrated platform offerings, allowing technology providers to deliver comprehensive accelerated computing infrastructure for data-intensive applications.

Threat:

Rapid Technological Competition and Product Substitution

Fast innovation across computing and semiconductor technologies can increase substitution risks for data center GPUs. New processor architectures, dedicated AI chips, custom accelerators, neuromorphic technologies, and other emerging solutions are being designed for specialized computational workloads. Advances in these alternatives could enable some applications to meet performance requirements without extensive use of traditional GPUs. Data center operators may consequently compare multiple processor architectures based on workload suitability, power requirements, software support, and total infrastructure costs. Rapid technology cycles can also reduce the effective lifespan of existing solutions, requiring GPU companies to maintain substantial investments in research, architecture development, software platforms, and continuous product innovation.

Covid-19 Impact:

The COVID-19 pandemic affected the Data Center GPU Market through accelerated digitalization, increased remote working, expanded cloud usage, and greater dependence on online platforms. Businesses and institutions adopted cloud-based infrastructure, virtual communication, digital services, and data-intensive applications, increasing requirements for computing resources and data center capacity. However, pandemic-related restrictions disrupted semiconductor production, transportation networks, component sourcing, and hardware deliveries, creating obstacles for GPU availability and infrastructure expansion. Data center operators also encountered operational challenges resulting from workforce limitations and facility restrictions. Consequently, COVID-19 highlighted the importance of advanced computing infrastructure while creating simultaneous supply chain and deployment difficulties for GPU manufacturers and data center operators.

The Discrete GPUs segment is expected to be the largest during the forecast period

The Discrete GPUs segment is expected to account for the largest market share during the forecast period, driven by its dedicated processing resources, high performance, and suitability for computationally intensive data center applications. Unlike integrated solutions, discrete GPUs function separately from CPUs and provide extensive parallel processing capabilities for artificial intelligence, machine learning, analytics, high-performance computing, and scientific workloads. Their ability to scale across multi-GPU configurations allows data centers to address demanding computational requirements efficiently. Growing needs for accelerated processing, sophisticated AI models, extensive datasets, and specialized computing infrastructure are contributing to the increasing deployment of discrete GPUs within advanced data center environments.

The Generative AI segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the Generative AI segment is predicted to witness the highest growth rate, supported by the expanding use of large language models, multimodal systems, AI-generated content, and advanced artificial intelligence applications. These workloads require significant computational capabilities for training, model optimization, fine-tuning, and inference, increasing the need for powerful GPUs within data center infrastructure. Cloud providers, technology companies, enterprises, and research institutions are developing accelerated computing environments to accommodate increasingly complex AI models. The broader integration of generative AI into software development, customer support, content production, healthcare, financial services, and other applications is encouraging investment in specialized GPU infrastructure capable of supporting demanding and computationally intensive AI workloads.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, supported by its extensive data center ecosystem, concentration of leading technology companies, and broad adoption of cloud and artificial intelligence technologies. The region benefits from established GPU suppliers, semiconductor manufacturers, cloud platforms, and large data center operators. Increasing deployment of generative AI, machine learning, high-performance computing, analytics, and other demanding workloads is supporting the use of GPU-accelerated infrastructure. The presence of hyperscale facilities and continued investment in advanced computing systems further strengthens regional demand. In addition, mature digital infrastructure, technical expertise, and established technology ecosystems support North America's prominent position in the market.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, supported by increasing data center capacity, expanding cloud services, and greater adoption of artificial intelligence technologies. Countries throughout the region are developing hyperscale data centers, AI-focused infrastructure, and advanced digital platforms, increasing demand for GPU-accelerated computing resources. Growing applications of generative AI, machine learning, analytics, and high-performance computing are encouraging businesses to adopt sophisticated accelerator solutions. Accelerating digital transformation among enterprises and public-sector organizations is further supporting infrastructure requirements. In addition, developing technology ecosystems and investments in semiconductor manufacturing and data center facilities are creating favorable conditions for expanding GPU deployment across the region.

Key players in the market

Some of the key players in Data Center GPU Market include Intel Corporation, Advanced Micro Devices, Inc., NVIDIA Corporation, Huawei Technologies Co., Ltd., Biren Technology, Moore Threads Technology Co., Ltd., Iluvatar CoreX, Cambricon Technologies Corporation Limited, Jingjia Microelectronics Co., Ltd., Enflame Technology Co., Ltd., MetaX Integrated Circuits Co., Ltd., Alibaba Group Holding Limited, Baidu, Inc., Fujitsu Limited, IBM Corporation, Lenovo Group Limited, Inspur Group and Foxconn Industrial Internet Co., Ltd.

Key Developments:

In July 2026, AMD and Microsoft expanded their long-term strategic partnership, with Microsoft planning to deploy AMD Helios rack-scale systems and next-generation AMD Instinct GPUs on Azure for frontier-model inference and AI services.

In May 2026, NVIDIA and IREN announced a strategic partnership supporting deployment of up to 5 GW of NVIDIA DSX-aligned AI infrastructure across IREN's data-center pipeline, combining NVIDIA accelerated computing with IREN's data-center and infrastructure capabilities.

In April 2026, Intel and Google announced a multiyear collaboration to advance AI and cloud infrastructure, including continued use of Intel Xeon processors and expanded co-development of custom ASIC-based infrastructure processing units (IPUs) for large-scale AI infrastructure.

GPU Types Covered:

  • Discrete GPUs
  • Integrated GPUs
  • Hybrid GPUs

GPU Architectures Covered:

  • CUDA-Based Architectures
  • CDNA-Based Architectures
  • Xe-Based Architectures
  • Other GPU Architectures

Form Factors Covered:

  • Single-Slot GPUs
  • Dual-Slot GPUs
  • Multi-Slot GPUs
  • SXM Modules
  • Rack-Scale GPU Systems

Cooling Types Covered:

  • Air-Cooled
  • Liquid-Cooled
  • Immersion-Cooled

Functions Covered:

  • AI Training
  • AI Inference
  • High-Performance Computing
  • Graphics and Visualization
  • Media and Video Processing

Deployments Covered:

  • Cloud
  • On-Premises

Data Center Types Covered:

  • Hyperscale Data Centers
  • Enterprise Data Centers
  • Colocation Data Centers
  • Edge Data Centers

Memory Technologies Covered:

  • HBM
  • GDDR
  • Other Memory Technologies

Applications Covered:

  • Generative AI
  • Machine Learning
  • Data Analytics
  • High-Performance Computing
  • Graphics Rendering
  • Media Processing
  • Virtualization and VDI

End Users Covered:

  • Cloud Service Providers
  • Enterprises
  • Government and Research Institutions

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global Data Center GPU Market, By GPU Type

  • 5.1 Discrete GPUs
  • 5.2 Integrated GPUs
  • 5.3 Hybrid GPUs

6 Global Data Center GPU Market, By GPU Architecture

  • 6.1 CUDA-Based Architectures
  • 6.2 CDNA-Based Architectures
  • 6.3 Xe-Based Architectures
  • 6.4 Other GPU Architectures

7 Global Data Center GPU Market, By Form Factor

  • 7.1 Single-Slot GPUs
  • 7.2 Dual-Slot GPUs
  • 7.3 Multi-Slot GPUs
  • 7.4 SXM Modules
  • 7.5 Rack-Scale GPU Systems

8 Global Data Center GPU Market, By Cooling Type

  • 8.1 Air-Cooled
  • 8.2 Liquid-Cooled
  • 8.3 Immersion-Cooled

9 Global Data Center GPU Market, By Function

  • 9.1 AI Training
  • 9.2 AI Inference
  • 9.3 High-Performance Computing
  • 9.4 Graphics and Visualization
  • 9.5 Media and Video Processing

10 Global Data Center GPU Market, By Deployment

  • 10.1 Cloud
  • 10.2 On-Premises

11 Global Data Center GPU Market, By Data Center Type

  • 11.1 Hyperscale Data Centers
  • 11.2 Enterprise Data Centers
  • 11.3 Colocation Data Centers
  • 11.4 Edge Data Centers

12 Global Data Center GPU Market, By Memory Technology

  • 12.1 HBM
  • 12.2 GDDR
  • 12.3 Other Memory Technologies

13 Global Data Center GPU Market, By Application

  • 13.1 Generative AI
  • 13.2 Machine Learning
  • 13.3 Data Analytics
  • 13.4 High-Performance Computing
  • 13.5 Graphics Rendering
  • 13.6 Media Processing
  • 13.7 Virtualization and VDI

14 Global Data Center GPU Market, By End User

  • 14.1 Cloud Service Providers
  • 14.2 Enterprises
  • 14.3 Government and Research Institutions

15 Global Data Center GPU Market, By Geography

  • 15.1 North America
    • 15.1.1 United States
    • 15.1.2 Canada
    • 15.1.3 Mexico
  • 15.2 Europe
    • 15.2.1 United Kingdom
    • 15.2.2 Germany
    • 15.2.3 France
    • 15.2.4 Italy
    • 15.2.5 Spain
    • 15.2.6 Netherlands
    • 15.2.7 Belgium
    • 15.2.8 Sweden
    • 15.2.9 Switzerland
    • 15.2.10 Poland
    • 15.2.11 Rest of Europe
  • 15.3 Asia Pacific
    • 15.3.1 China
    • 15.3.2 Japan
    • 15.3.3 India
    • 15.3.4 South Korea
    • 15.3.5 Australia
    • 15.3.6 Indonesia
    • 15.3.7 Thailand
    • 15.3.8 Malaysia
    • 15.3.9 Singapore
    • 15.3.10 Vietnam
    • 15.3.11 Rest of Asia Pacific
  • 15.4 South America
    • 15.4.1 Brazil
    • 15.4.2 Argentina
    • 15.4.3 Colombia
    • 15.4.4 Chile
    • 15.4.5 Peru
    • 15.4.6 Rest of South America
  • 15.5 Rest of the World (RoW)
    • 15.5.1 Middle East
      • 15.5.1.1 Saudi Arabia
      • 15.5.1.2 United Arab Emirates
      • 15.5.1.3 Qatar
      • 15.5.1.4 Israel
      • 15.5.1.5 Rest of Middle East
    • 15.5.2 Africa
      • 15.5.2.1 South Africa
      • 15.5.2.2 Egypt
      • 15.5.2.3 Morocco
      • 15.5.2.4 Rest of Africa

16 Strategic Market Intelligence

  • 16.1 Industry Value Network and Supply Chain Assessment
  • 16.2 White-Space and Opportunity Mapping
  • 16.3 Product Evolution and Market Life Cycle Analysis
  • 16.4 Channel, Distributor, and Go-to-Market Assessment

17 Industry Developments and Strategic Initiatives

  • 17.1 Mergers and Acquisitions
  • 17.2 Partnerships, Alliances, and Joint Ventures
  • 17.3 New Product Launches and Certifications
  • 17.4 Capacity Expansion and Investments
  • 17.5 Other Strategic Initiatives

18 Company Profiles

  • 18.1 Intel Corporation
  • 18.2 Advanced Micro Devices, Inc.
  • 18.3 NVIDIA Corporation
  • 18.4 Huawei Technologies Co., Ltd.
  • 18.5 Biren Technology
  • 18.6 Moore Threads Technology Co., Ltd.
  • 18.7 Iluvatar CoreX
  • 18.8 Cambricon Technologies Corporation Limited
  • 18.9 Jingjia Microelectronics Co., Ltd.
  • 18.10 Enflame Technology Co., Ltd.
  • 18.11 MetaX Integrated Circuits Co., Ltd.
  • 18.12 Alibaba Group Holding Limited
  • 18.13 Baidu, Inc.
  • 18.14 Fujitsu Limited
  • 18.15 IBM Corporation
  • 18.16 Lenovo Group Limited
  • 18.17 Inspur Group
  • 18.18 Foxconn Industrial Internet Co., Ltd.

List of Tables

  • Table 1 Global Data Center GPU Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global Data Center GPU Market Outlook, By GPU Type (2023-2034) ($MN)
  • Table 3 Global Data Center GPU Market Outlook, By Discrete GPUs (2023-2034) ($MN)
  • Table 4 Global Data Center GPU Market Outlook, By Integrated GPUs (2023-2034) ($MN)
  • Table 5 Global Data Center GPU Market Outlook, By Hybrid GPUs (2023-2034) ($MN)
  • Table 6 Global Data Center GPU Market Outlook, By GPU Architecture (2023-2034) ($MN)
  • Table 7 Global Data Center GPU Market Outlook, By CUDA-Based Architectures (2023-2034) ($MN)
  • Table 8 Global Data Center GPU Market Outlook, By CDNA-Based Architectures (2023-2034) ($MN)
  • Table 9 Global Data Center GPU Market Outlook, By Xe-Based Architectures (2023-2034) ($MN)
  • Table 10 Global Data Center GPU Market Outlook, By Other GPU Architectures (2023-2034) ($MN)
  • Table 11 Global Data Center GPU Market Outlook, By Form Factor (2023-2034) ($MN)
  • Table 12 Global Data Center GPU Market Outlook, By Single-Slot GPUs (2023-2034) ($MN)
  • Table 13 Global Data Center GPU Market Outlook, By Dual-Slot GPUs (2023-2034) ($MN)
  • Table 14 Global Data Center GPU Market Outlook, By Multi-Slot GPUs (2023-2034) ($MN)
  • Table 15 Global Data Center GPU Market Outlook, By SXM Modules (2023-2034) ($MN)
  • Table 16 Global Data Center GPU Market Outlook, By Rack-Scale GPU Systems (2023-2034) ($MN)
  • Table 17 Global Data Center GPU Market Outlook, By Cooling Type (2023-2034) ($MN)
  • Table 18 Global Data Center GPU Market Outlook, By Air-Cooled (2023-2034) ($MN)
  • Table 19 Global Data Center GPU Market Outlook, By Liquid-Cooled (2023-2034) ($MN)
  • Table 20 Global Data Center GPU Market Outlook, By Immersion-Cooled (2023-2034) ($MN)
  • Table 21 Global Data Center GPU Market Outlook, By Function (2023-2034) ($MN)
  • Table 22 Global Data Center GPU Market Outlook, By AI Training (2023-2034) ($MN)
  • Table 23 Global Data Center GPU Market Outlook, By AI Inference (2023-2034) ($MN)
  • Table 24 Global Data Center GPU Market Outlook, By High-Performance Computing (2023-2034) ($MN)
  • Table 25 Global Data Center GPU Market Outlook, By Graphics and Visualization (2023-2034) ($MN)
  • Table 26 Global Data Center GPU Market Outlook, By Media and Video Processing (2023-2034) ($MN)
  • Table 27 Global Data Center GPU Market Outlook, By Deployment (2023-2034) ($MN)
  • Table 28 Global Data Center GPU Market Outlook, By Cloud (2023-2034) ($MN)
  • Table 29 Global Data Center GPU Market Outlook, By On-Premises (2023-2034) ($MN)
  • Table 30 Global Data Center GPU Market Outlook, By Data Center Type (2023-2034) ($MN)
  • Table 31 Global Data Center GPU Market Outlook, By Hyperscale Data Centers (2023-2034) ($MN)
  • Table 32 Global Data Center GPU Market Outlook, By Enterprise Data Centers (2023-2034) ($MN)
  • Table 33 Global Data Center GPU Market Outlook, By Colocation Data Centers (2023-2034) ($MN)
  • Table 34 Global Data Center GPU Market Outlook, By Edge Data Centers (2023-2034) ($MN)
  • Table 35 Global Data Center GPU Market Outlook, By Memory Technology (2023-2034) ($MN)
  • Table 36 Global Data Center GPU Market Outlook, By HBM (2023-2034) ($MN)
  • Table 37 Global Data Center GPU Market Outlook, By GDDR (2023-2034) ($MN)
  • Table 38 Global Data Center GPU Market Outlook, By Other Memory Technologies (2023-2034) ($MN)
  • Table 39 Global Data Center GPU Market Outlook, By Application (2023-2034) ($MN)
  • Table 40 Global Data Center GPU Market Outlook, By Generative AI (2023-2034) ($MN)
  • Table 41 Global Data Center GPU Market Outlook, By Machine Learning (2023-2034) ($MN)
  • Table 42 Global Data Center GPU Market Outlook, By Data Analytics (2023-2034) ($MN)
  • Table 43 Global Data Center GPU Market Outlook, By High-Performance Computing (2023-2034) ($MN)
  • Table 44 Global Data Center GPU Market Outlook, By Graphics Rendering (2023-2034) ($MN)
  • Table 45 Global Data Center GPU Market Outlook, By Media Processing (2023-2034) ($MN)
  • Table 46 Global Data Center GPU Market Outlook, By Virtualization and VDI (2023-2034) ($MN)
  • Table 47 Global Data Center GPU Market Outlook, By End User (2023-2034) ($MN)
  • Table 48 Global Data Center GPU Market Outlook, By Cloud Service Providers (2023-2034) ($MN)
  • Table 49 Global Data Center GPU Market Outlook, By Enterprises (2023-2034) ($MN)
  • Table 50 Global Data Center GPU Market Outlook, By Government and Research Institutions (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) Regions are also represented in the same manner as above.