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市場調查報告書
商品編碼
2099414

GPU網路：市佔率分析、產業趨勢與統計、成長預測（2026-2031年）

GPU Networking - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2026 - 2031)
出版日期: | 出版商: Mordor Intelligence | 英文 167 Pages | 商品交期: 2-3個工作天內

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簡介目錄

根據 Mordor Intelligence 預測，GPU 網路市場預計將從 2025 年的 476 億美元成長到 2026 年的 735 億美元，到 2031 年達到 2,273 億美元，2026 年至 2031 年的複合年成長率預計為 25.33%。

GPU 網路市場-IMG1

本報告按交付方式（硬體、軟體、服務）、網路類型（乙太網路、InfiniBand、可擴展GPU互連）、部署模式（本地AI叢集、雲端、超大規模GPU架構等）、最終用戶（雲端服務供應商、企業、政府和國防機構、研究和學術機構等）以及地區進行細分。市場預測以價值（美元）表示。

全球GPU網路市場趨勢與洞察

人工智慧集群密度的不斷提高，正推動後端網路發揮主導作用。

隨著人工智慧叢集密度成長速度遠超以往任何網路基礎架構週期，GPU網路市場正吸引著來自超大規模資料中心的更多資金。人工智慧加速器機架的功耗已從網路服務時代的少於20千瓦成長到超過150千瓦，目前已發布的藍圖顯示，小型叢集系統的功耗將接近1兆瓦。這種密度的提升迫使營運商在更小的安裝空間內部署更多GPU，從而導致整個後端架構對東西向頻寬的需求激增。因此，GPU網路市場如今已成為人工智慧基礎設施規劃的核心，因為架構容量不足會導致昂貴的運算資源在資料傳輸過程中被佔用。採購重點正轉向高速交換、光纖通訊和高密度互連設計，以維持大規模訓練叢集的負載平衡。這也解釋了為何即使買家已經在加速器和儲存方面投入了巨額預算，GPU網路市場仍能持續吸引投資。

快速向 400G 和 800G 過渡正在推動乙太網路切換器。

與大多數其他企業基礎設施領域相比，GPU網路市場正受益於更快的乙太網路速度升級。 400G於2024年成為主流，800G於2025年投入量產，而1.6Tbps平台則在2026年透過新產品發表開始出現在市場上。 2026年6月，Arista發布了7060XE7系列，該系列採用224G SerDes和博通Tomahawk 6晶片，每個平台的總交換容量為100Tbps。隨後，Celestica於2026年4月開始訂單，並將此速度等級引入ODM通路。隨著每一代速度的提升，升級週期都在縮短，目前部署800G的用戶已經在計畫向1.6TbE遷移。遵守標準也在影響購買決策，因為對 OCP ESUN 和 UEC 規範的支援在 GPU 網路市場變得越來越重要。

高資本密集度導致超大規模業者集中進入市場。

GPU網路市場仍然涉及高昂的前期成本，這決定了哪些企業能夠大規模部署生產級網路架構。建構完整的AI網路環境需要交換器、網路卡、分散式處理器（DPU）、收發器、線纜、軟體以及整合工作，這使得其支出門檻遠高於傳統資料中心升級。這有利於能夠大量談判並將固定工程成本分攤到超大規模部署的超大規模營運商。另一方面，由於採購規模和整合團隊規模較小，企業客戶和小規模雲端服務供應商往往需要承擔更高的單GPU網路成本。因此，在依賴私有建置和區域基礎設施項目的GPU網路市場中，其普及速度較為小規模。這種成本壁壘也促使人們對檢驗的架構和服務主導的部署模型產生興趣，這些模型可以降低小規模買家的執行風險。

細分市場分析

硬體仍然是GPU網路市場中最大的組成部分，預計到2025年將佔銷售額的92.11%。這種集中度反映了實體基礎設施的高成本，尤其是交換器、網路卡、DPU、線纜和光收發器。交換平台構成了最大的硬體板塊，因為800G乙太網路和InfiniBand系統是AI叢集設計的核心。隨著買家將網路卸載、遙測和流量管理轉移到伺服器堆疊中的專用晶片上，網路卡和DPU的重要性也隨之增加。這種商品搭售趨勢使得整個GPU網路市場的運算和網路採購更加相互依存。

線纜和收發器仍是第三大重要的硬體支柱，其供應狀況持續影響GPU網路市場的部署計畫。即使買家獲得了加速器和交換平台，叢集的運作仍然取決於光纖通訊基礎設施和認證互連設備的可用性。預計到2031年，軟體將以26.21%的複合年成長率成長，成為GPU網路市場中成長最快的細分領域。隨著叢集規模的擴大，網路編配、自適應路由、遙測和擁塞控制正從可選工具轉變為運行必需功能。服務的重要性也日益凸顯，因為企業和政府機構通常需要部署支援、整合協助和持續運維的專業知識，才能大規模運作GPU網路架構。

到2025年，乙太網路在GPU網路市場中佔據47.33%的銷售額，按網路類型分類，乙太網路在該市場中領先。這一主導地位反映了乙太網路在橫向擴展AI後端網路、前端管理層和儲存流量中的重要作用。支援RoCE的乙太網路已成為許多AI訓練環境的事實預設選項，這些環境需要開放標準和廣泛的採購選擇。 Ultra Ethernet Consortium於2025年6月發布的UEC 1.0進一步鞏固了乙太網路的地位，擴展了乙太網路的功能以滿足AI群集的需求。雖然標準乙太網路在支援流量方面仍然很重要，但高效能的RoCE部署現在已佔據GPU網路市場訓練工作負載的很大一部分。

在某些應用場景中，InfiniBand憑藉其確定性的性能和極低的延遲優勢，仍然佔據著至關重要的地位，其優勢甚至超過了廣泛的互通性。同時，預計到2031年，可擴展GPU互連將以26.62%的複合年成長率成長，成為GPU網路市場中成長最快的網路類型。這主要歸因於其架構，因為人工智慧系統現在不僅需要在節點之間處理更多流量，還需要處理運算單元內部的流量。 NVIDIA的Vera Rubin NVL144和AMD的Infinity Fabric體現了Terabit特級叢集內頻寬日益成長的重要性。此外，UALink 1.0擴展了開放式可擴展架構的設計可能性，鞏固了該領域在GPU網路市場的戰略地位。

區域分析

北美仍是GPU網路市場最大的區域市場，在2025年佔了38.44%的銷售額。該地區受益於美國領先的超大規模資料中心業者的資本投資計劃，這些計劃持續影響著全球對交換器、收發器和互連晶片的需求。 NVIDIA透過Spectrum-X在乙太網路交換領域確立的領導地位，顯示在該地區，運算和網路決策的連結非常緊密。 Google、亞馬遜、微軟和Meta等雲端服務供應商已宣布了2025年和2026年的多年人工智慧基礎設施擴展計劃，這將持續給800G和1.6T供應鏈帶來壓力。此外，美國仍然是許多白盒和ODM計畫的關鍵設計和採購中心，這意味著美國做出的決策會迅速波及亞洲的製造生態系統。由於電力供應充足且接近性美國雲端基礎設施，加拿大和墨西哥加強了對區域部署的支援。

歐洲仍是GPU網路領域的第二大市場，在各國主導的人工智慧政策、超大規模資料中心業者的擴張以及數位基礎設施項目的推動下，市場持續成長。德國電信和英偉達於2026年2月在慕尼黑啟動了“德國工業人工智慧雲”，投資10億歐元（約10.9億美元）並部署了1萬塊英偉達Blackwell GPU。英國也在2026年初獲得了英偉達、微軟和谷歌超過400億英鎊（約500億美元）的投資承諾。其中包括英偉達計畫在2026年底前在英國資料中心部署12萬塊Blackwell GPU。歐盟委員會的「人工智慧超級工廠」計畫預計將利用高達200億歐元的公共資金建設五座新的設施，從而擴大機架級網路的未來計畫儲備。

預計到2031年，亞太地區將以26.42%的複合年成長率成長，成為GPU網路市場成長最快的地區。中國、日本、韓國和印度在公共雲端、自主人工智慧、電信和工業領域的需求模式各不相同。中國主要網際網路公司持續大力投資擴大資料中心，其優先採購國內產品的政策也推動了本地GPU網路的發展。日本分佈式光子網路也初見成效。 2026年3月，NTT東日本利用IOWN全光電網路完成了東京至福岡之間的概念驗證（PoC），在1000公里的距離上實現了平均13.26毫秒的往返延遲。 2026年4月，NTT宣布計畫在2033年將其資料中心IT電力容量從300兆瓦擴展到1吉瓦，並將人工智慧網路作為核心發展方向。東南亞、南美、中東和非洲正在成為GPU網路市場的新需求來源，因為主權財富基金和數位經濟計畫正在推動區域GPU雲端和託管設施的發展。

其他好處：

  • Excel格式的市場預測（ME）表
  • 3個月的分析師支持

目錄

第1章：引言

  • 研究假設和市場定義
  • 調查範圍

第2章：調查方法

第3章執行摘要

第4章 市場狀況

  • 市場概覽
  • 宏觀經濟因素對市場的影響
  • 市場促進因素
    • 提高超大規模資料中心的人工智慧集群密度
    • 快速遷移到 400G 和 800G 網路升級
    • 在GPU架構中擴大無損乙太網路的應用
    • InfiniBand 在訓練大規模模型方面的應用正在加速發展。
    • 在高速GPU架構中採用共封裝光元件
    • 基於白盒和ODM的AI網路建構的需求不斷成長。
  • 市場限制因素
    • GPU網路基礎設施的高資本密集度
    • 整個架構堆疊的互通性以及供應商鎖定風險。
    • 人工智慧設施的電力、冷卻和機架密度限制
    • 高速開關所需的矽和光學元件供不應求
  • 產業價值鏈分析
  • 供應鏈分析
  • 監理情勢
  • 技術展望
  • 波特五力分析

第5章 市場規模與成長預測

  • 報價
    • 硬體
      • 轉變
      • 網路介面卡和DPU
      • 電纜和收發器
    • 軟體
      • 網路編配與管理軟體
      • 監控和遙測軟體
    • 服務
      • 整合和配置服務
      • 支援和維護服務
  • 依網路類型
    • 乙太網路
      • 標準乙太網路
      • 符合 RoCE 標準的以太網
    • InfiniBand
    • 可擴展的GPU互連
      • NVLink／NVSwitch
      • Infinity Fabric
      • UALink 和其他新興互連技術
  • 按部署模式
    • 本地部署的人工智慧叢集
    • 雲端和超大規模 GPU 架構
    • 透過 GPU 雲端和託管進行部署
  • 最終用戶
    • 雲端服務供應商
    • 公司
    • 政府/國防
    • 研究與學術
    • 電信服務供應商
  • 按地區
    • 北美洲
      • 美國
      • 加拿大
      • 墨西哥
    • 歐洲
      • 德國
      • 英國
      • 法國
      • 義大利
      • 其他歐洲國家
    • 亞太地區
      • 中國
      • 日本
      • 韓國
      • 印度
      • 東南亞
      • 其他亞太國家
    • 南美洲
    • 中東和非洲

第6章 競爭情勢

  • 市場集中度
  • 策略趨勢
  • 市佔率分析
  • 公司簡介
    • NVIDIA Corporation
    • Broadcom Inc.
    • Arista Networks, Inc.
    • Cisco Systems, Inc.
    • Celestica Inc.
    • HPE
    • Juniper Networks, Inc.
    • Dell Technologies Inc.
    • Intel Corporation
    • Marvell Technology, Inc.
    • Astera Labs, Inc.
    • Credo Technology Group Holding Ltd
    • Coherent Corp.
    • Lumentum Holdings Inc.
    • Ciena Corporation
    • Nokia Corporation
    • Huawei Technologies Co., Ltd.
    • Ericsson AB
    • Hewlett Packard Enterprise Development LP
    • Super Micro Computer, Inc.

第7章 市場機會與未來展望

簡介目錄
Product Code: 100176

According to Mordor Intelligence, the GPU networking market size is expected to increase from USD 47.6 billion in 2025 to USD 73.5 billion in 2026 and reach USD 227.3 billion by 2031, growing at a CAGR of 25.33% over 2026-2031.

GPU Networking - Market - IMG1

This report is Segmented by Offering (Hardware, Software, and Services), Network Type (Ethernet, Infiniband, Scale-Up GPU Interconnects), Deployment Model (On-Premises AI Clusters, Cloud and Hyperscale GPU Fabrics, and More), End User (Cloud Service Providers, Enterprises, Government and Defense, Research and Academia, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Global GPU Networking Market Trends and Insights

Rising AI Cluster Density Pushes Back-End Network to Center Stage

The GPU networking market is drawing more capital from hyperscale data centers because AI cluster density is rising faster than earlier web infrastructure cycles. AI accelerator rack power moved from below 20 kW in the web-services era to above 150 kW, and public roadmaps now point to pod-scale systems nearing 1 MW. That density forces operators to place more GPUs into tighter footprints, which raises east-west bandwidth demand across the back-end fabric. As a result, the GPU networking market now sits closer to the center of AI infrastructure planning, because underbuilt fabrics can leave expensive compute capacity waiting on data movement. Procurement priorities have shifted toward high-speed switching, optics, and dense interconnect designs that can keep large training clusters balanced. This also explains why the GPU networking market is attracting sustained spending even when buyers are already committing very large budgets to accelerators and storage.

Rapid Shift to 400G and 800G Fuels Ethernet Switch Revenue

The GPU networking market is benefiting from a faster Ethernet speed transition than most enterprise infrastructure categories have seen. 400G became mainstream in 2024, 800G entered production in 2025, and 1.6 Tbps platforms began reaching the market in 2026 through new product launches. Arista introduced the 7060XE7 Series in June 2026 with 100 Tbps aggregate switching capacity per platform using 224G SerDes and Broadcom Tomahawk 6 silicon. Celestica then made its DS6000-series 1.6 TbE switches available to order in April 2026, which brought the same speed class into the ODM channel. Each speed generation is shortening the upgrade cycle, so buyers that are deploying 800G today are already planning migration paths to 1.6T. Standards alignment is also shaping purchase decisions, since support for OCP ESUN and UEC specifications is becoming more important in the GPU networking market.

High Capital Intensity Concentrates Market Access Among Hyperscale Operators

The GPU networking market still carries a large upfront cost burden, and that burden shapes who can deploy production-grade fabrics at scale. A full AI networking build requires switches, NICs, DPUs, transceivers, cabling, software, and integration work, so the spending threshold is far higher than in conventional data center upgrades. This favors hyperscale buyers that can negotiate at volume and spread fixed engineering costs across very large deployments. Enterprise buyers and smaller cloud operators often face a much steeper per-GPU networking cost because their procurement scale is lower and their integration teams are smaller. The result is slower adoption in parts of the GPU networking market that depend on private builds or regional infrastructure programs. This cost barrier is also increasing interest in validated architectures and service-led deployment models that reduce execution risk for smaller buyers.

Other drivers and restraints analyzed in the detailed report include:

  1. Lossless Ethernet for GPU Fabrics Displaces InfiniBand as the Scale-Out Default
  2. InfiniBand Maintains Dominance for Frontier-Scale Model Training
  3. Interoperability Fragmentation Introduces Strategic Risk Across Fabric Stacks

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Hardware accounted for 92.11% of 2025 revenue and remained the largest component of the GPU networking market. That concentration reflects the high cost of physical infrastructure, especially switches, NICs, DPUs, cables, and optical transceivers. Switching platforms formed the largest hardware block because 800G Ethernet and InfiniBand systems are central to AI cluster design. NICs and DPUs also gained weight as buyers moved network offload, telemetry, and traffic management onto dedicated silicon inside the server stack. This bundling trend is making compute and networking procurement more interdependent across the GPU networking market.

Cables and transceivers remained the third major hardware pillar, and their availability still affected deployment schedules in the GPU networking market. Buyers could secure accelerators and switch platforms, but cluster turn-up still depended on optical readiness and qualified interconnect inventory. Software is projected to expand at a 26.21% CAGR through 2031, which makes it the fastest-growing offering in the GPU networking market. Network orchestration, adaptive routing, telemetry, and congestion control are moving from optional tools to operating requirements as cluster sizes increase. Services are also becoming more important because enterprise and sovereign operators often need deployment support, integration help, and ongoing operations expertise to run GPU fabrics at scale.

Ethernet held 47.33% of 2025 revenue and led the GPU networking market by network type. That lead reflects Ethernet's role in scale-out AI back-end networks, front-end management layers, and storage traffic. RoCE-enabled Ethernet has become the practical default for many AI training environments where buyers want open standards and broader sourcing. The Ultra Ethernet Consortium's UEC 1.0 release in June 2025 strengthened that position by extending Ethernet behavior for AI cluster requirements. Standard Ethernet still mattered for support traffic, while higher-performance RoCE deployments carried more of the training workload inside the GPU networking market.

InfiniBand remained critical where deterministic performance and very low latency outweighed the benefits of broader interoperability. At the same time, Scale-Up GPU Interconnects are forecast to grow at a 26.62% CAGR through 2031, making them the fastest-growing network type in the GPU networking market. The main reason is architectural, because AI systems are now pushing more traffic inside the compute pod rather than only between nodes. NVIDIA's Vera Rubin NVL144 direction and AMD's Infinity Fabric reflect the rising importance of terabit-class intra-cluster bandwidth. UALink 1.0 also widened the design path for open scale-up fabrics, which keeps this part of the GPU networking market strategically important.

Complete Report Scope:

  • By Offering
    • Hardware
      • Switches
      • Network Interface Cards and DPUs
      • Cables and Transceivers
    • Software
      • Network Orchestration and Management Software
      • Monitoring and Telemetry Software
    • Services
      • Integration and Deployment Services
      • Support and Maintenance Services
  • By Network Type
    • Ethernet
      • Standard Ethernet
      • RoCE-enabled Ethernet
    • InfiniBand
    • Scale-Up GPU Interconnects
      • NVLink/NVSwitch
      • Infinity Fabric
      • UALink and Other Emerging Interconnects
  • By Deployment Model
    • On-Premises AI Clusters
    • Cloud and Hyperscale GPU Fabrics
    • GPU Cloud and Colocation Deployments
  • By End User
    • Cloud Service Providers
    • Enterprises
    • Government and Defense
    • Research and Academia
    • Telecommunications Service Providers
  • By Geography
    • North America
      • United States
      • Canada
      • Mexico
    • Europe
      • Germany
      • United Kingdom
      • France
      • Italy
      • Rest of Europe
    • Asia-Pacific
      • China
      • Japan
      • South Korea
      • India
      • Southeast Asia
      • Rest of Asia-Pacific
    • South America
    • Middle East and Africa

Geography Analysis

North America held 38.44% of 2025 revenue and remained the largest regional block in the GPU networking market. The region is anchored by the capital programs of major U.S. hyperscalers, which continue to shape global demand for switches, transceivers, and interconnect silicon. NVIDIA's move into Ethernet switching leadership through Spectrum-X showed how tightly compute and networking decisions are now linked in this region. Cloud providers such as Google, Amazon, Microsoft, and Meta announced multiyear AI infrastructure expansions in 2025 and 2026, which kept pressure on 800G and 1.6T supply chains. The United States also remains the main design and procurement center for many white-box and ODM programs, so decisions made there flow quickly through Asian manufacturing ecosystems. Canada and Mexico added supporting capacity where power availability and proximity to U.S. cloud infrastructure made regional deployments practical.

Europe remained the second-largest region in the GPU networking market and continued to advance on the back of sovereign AI policy, hyperscaler expansion, and digital infrastructure programs. Deutsche Telekom and NVIDIA opened Germany's Industrial AI Cloud in Munich in February 2026 with 10,000 NVIDIA Blackwell GPUs and EUR 1 billion (USD 1.09 billion) in investment. The UK also attracted commitments from NVIDIA, Microsoft, and Google that exceeded GBP 40 billion (USD 50 billion) in early 2026, including NVIDIA's plan to install 120,000 Blackwell GPUs in British data centers by end-2026. The European Commission's AI Gigafactory program is expected to add 5 facilities with up to EUR 20 billion in public funding, which extends the future project pipeline for rack-scale networking.

Asia-Pacific is projected to grow at a 26.42% CAGR through 2031, making it the fastest-growing region in the GPU networking market. China, Japan, South Korea, and India are driving different demand patterns across public cloud, sovereign AI, telecom, and industrial deployments. China's large internet companies continue to invest heavily in data center capacity, and domestic procurement priorities are supporting local GPU networking build-outs. Japan is also showing early momentum in distributed photonic networking. NTT East completed a proof of concept between Tokyo and Fukuoka in March 2026 using the IOWN All-Photonics Network and recorded average round-trip latency of 13.26 ms over 1,000 km. NTT said in April 2026 that it plans to increase data center IT power capacity from 300 MW to 1 GW by 2033, with AI networking as a central theme. Southeast Asia, South America, and the Middle East and Africa are emerging demand pools in the GPU networking market as sovereign funds and digital economy programs back regional GPU cloud and colocation builds.

  1. NVIDIA Corporation
  2. Broadcom Inc.
  3. Arista Networks, Inc.
  4. Cisco Systems, Inc.
  5. Celestica Inc.
  6. HPE
  7. Juniper Networks, Inc.
  8. Dell Technologies Inc.
  9. Intel Corporation
  10. Marvell Technology, Inc.
  11. Astera Labs, Inc.
  12. Credo Technology Group Holding Ltd
  13. Coherent Corp.
  14. Lumentum Holdings Inc.
  15. Ciena Corporation
  16. Nokia Corporation
  17. Huawei Technologies Co., Ltd.
  18. Ericsson AB
  19. Hewlett Packard Enterprise Development LP
  20. Super Micro Computer, Inc.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

  • 4.1 Market Overview
  • 4.2 Impact of Macroeconomic Factors on the Market
  • 4.3 Market Drivers
    • 4.3.1 Rising AI Cluster Density in Hyperscale Data Centers
    • 4.3.2 Rapid Shift to 400G and 800G Network Upgrades
    • 4.3.3 Growing Adoption of Lossless Ethernet for GPU Fabrics
    • 4.3.4 Accelerating Use of InfiniBand for Large Model Training
    • 4.3.5 Co-Packaged Optics Adoption in High-Speed GPU Fabrics
    • 4.3.6 Increased Demand for White-Box and ODM-Based AI Network Builds
  • 4.4 Market Restraints
    • 4.4.1 High Capital Intensity of GPU Networking Infrastructure
    • 4.4.2 Interoperability and Vendor Lock-In Risk Across Fabric Stacks
    • 4.4.3 Power, Cooling, and Rack Density Constraints in AI Facilities
    • 4.4.4 Limited Supply of High-Speed Switch Silicon and Optical Components
  • 4.5 Industry Value Chain Analysis
  • 4.6 Supply Chain Analysis
  • 4.7 Regulatory Landscape
  • 4.8 Technological Outlook
  • 4.9 Porter's Five Forces Analysis
    • 4.9.1 Threat of New Entrants
    • 4.9.2 Bargaining Power of Suppliers
    • 4.9.3 Bargaining Power of Buyers
    • 4.9.4 Threat of Substitutes
    • 4.9.5 Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

  • 5.1 By Offering
    • 5.1.1 Hardware
      • 5.1.1.1 Switches
      • 5.1.1.2 Network Interface Cards and DPUs
      • 5.1.1.3 Cables and Transceivers
    • 5.1.2 Software
      • 5.1.2.1 Network Orchestration and Management Software
      • 5.1.2.2 Monitoring and Telemetry Software
    • 5.1.3 Services
      • 5.1.3.1 Integration and Deployment Services
      • 5.1.3.2 Support and Maintenance Services
  • 5.2 By Network Type
    • 5.2.1 Ethernet
      • 5.2.1.1 Standard Ethernet
      • 5.2.1.2 RoCE-enabled Ethernet
    • 5.2.2 InfiniBand
    • 5.2.3 Scale-Up GPU Interconnects
      • 5.2.3.1 NVLink/NVSwitch
      • 5.2.3.2 Infinity Fabric
      • 5.2.3.3 UALink and Other Emerging Interconnects
  • 5.3 By Deployment Model
    • 5.3.1 On-Premises AI Clusters
    • 5.3.2 Cloud and Hyperscale GPU Fabrics
    • 5.3.3 GPU Cloud and Colocation Deployments
  • 5.4 By End User
    • 5.4.1 Cloud Service Providers
    • 5.4.2 Enterprises
    • 5.4.3 Government and Defense
    • 5.4.4 Research and Academia
    • 5.4.5 Telecommunications Service Providers
  • 5.5 By Geography
    • 5.5.1 North America
      • 5.5.1.1 United States
      • 5.5.1.2 Canada
      • 5.5.1.3 Mexico
    • 5.5.2 Europe
      • 5.5.2.1 Germany
      • 5.5.2.2 United Kingdom
      • 5.5.2.3 France
      • 5.5.2.4 Italy
      • 5.5.2.5 Rest of Europe
    • 5.5.3 Asia-Pacific
      • 5.5.3.1 China
      • 5.5.3.2 Japan
      • 5.5.3.3 South Korea
      • 5.5.3.4 India
      • 5.5.3.5 Southeast Asia
      • 5.5.3.6 Rest of Asia-Pacific
    • 5.5.4 South America
    • 5.5.5 Middle East and Africa

6 COMPETITIVE LANDSCAPE

  • 6.1 Market Concentration
  • 6.2 Strategic Moves
  • 6.3 Market Share Analysis
  • 6.4 Company Profiles (includes Global Level Overview, Market Level Overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share, Products and Services, Recent Developments)
    • 6.4.1 NVIDIA Corporation
    • 6.4.2 Broadcom Inc.
    • 6.4.3 Arista Networks, Inc.
    • 6.4.4 Cisco Systems, Inc.
    • 6.4.5 Celestica Inc.
    • 6.4.6 HPE
    • 6.4.7 Juniper Networks, Inc.
    • 6.4.8 Dell Technologies Inc.
    • 6.4.9 Intel Corporation
    • 6.4.10 Marvell Technology, Inc.
    • 6.4.11 Astera Labs, Inc.
    • 6.4.12 Credo Technology Group Holding Ltd
    • 6.4.13 Coherent Corp.
    • 6.4.14 Lumentum Holdings Inc.
    • 6.4.15 Ciena Corporation
    • 6.4.16 Nokia Corporation
    • 6.4.17 Huawei Technologies Co., Ltd.
    • 6.4.18 Ericsson AB
    • 6.4.19 Hewlett Packard Enterprise Development LP
    • 6.4.20 Super Micro Computer, Inc.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

  • 7.1 White-Space and Unmet-Need Assessment