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GPUaaS（GPU 即服務）市場報告：趨勢、預測與競爭分析（至 2031 年）

GPU as a Service Market Report: Trends, Forecast and Competitive Analysis to 2031

出版日期: 2025年02月21日 | 出版商:

Lucintel | 英文 150 Pages | 商品交期: 3個工作天內

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簡介目錄

全球 GPUaaS（GPU 即服務）市場前景光明，在醫療、BFSI、製造、IT 和通訊以及汽車應用領域都擁有廣泛的機會。預計到 2031 年全球 GPUaaS（GPU 即服務）市場規模將達到 219 億美元，2025 年至 2031 年的複合年成長率為 26.8%。該市場的關鍵促進因素是對遊戲和設計領域的研發越來越重視，各行業對機器學習和基於人工智慧的應用程式的應用越來越多，以及對高階資料分析的需求不斷成長。

在部署模型類別中，Lucintel 預測私有部署將在預測期間內經歷最高的成長。
按地區分類，北美將在預測期內繼續成為最大的地區。

GPUaaS（GPU 即服務）市場的策略性成長機會

在技術進步和市場需求的推動下，GPUaaS（GPU 即服務）市場的成長機會前景正在各個關鍵應用領域不斷發展。

人工智慧和機器學習：GPUaaS 在人工智慧和機器學習應用中的使用具有巨大的成長潛力，因為這些技術在訓練和推理階段都需要大量運算。
資料分析與巨量資料：隨著大量資料的出現，越來越多的產業（包括金融、醫療保健和零售業）開始轉向 GPUaaS 進行資料處理和運行密集的分析工作負載。
遊戲和虛擬實境：因此，GPUaaS 填補了遊戲和獲取清晰內容所需的空白。
邊緣運算：GPUaaS 與邊緣運算的結合可以增強即時資料處理和分析，為物聯網和智慧城市等垂直領域提供機會。
混合雲端解決方案：GPUaaS 供應商可以透過提供與內部部署或其他雲端基礎設施整合的經濟高效的 GPUaaS 解決方案來促進遷移。
研發：研發投入將逐步增加，以建構新的 GPU 技術和服務模式，為 GPUaaS 開闢新的收益和地理範圍。

GPUaaS 市場預計在各種融合機會中實現成長，包括人工智慧和機器學習、巨量資料和分析、遊戲和虛擬實境、邊緣運算、混合雲端解決方案以及研究和開發。

GPUaaS（GPU 即服務）市場促進因素與挑戰

GPUaaS（GPU 即服務）市場面臨影響其成長和發展的促進因素和挑戰。

推動 GPUaaS 市場發展的因素包括：

對高效能運算的需求不斷成長：人工智慧、機器學習和資料分析對高效能運算的需求不斷成長，推動了對 GPUaaS 的需求不斷成長。
GPU 技術的進步：GPU 技術的持續進步不斷增強 GPUaaS 解決方案並提高其接受度。
擴充性和靈活性：企業可以根據其工作負載量擴充和調整 GPUaaS。
經濟高效：企業可以透過計量收費和預留執行個體模式以低成本存取GPUaaS。
雲端處理的應用日益廣泛：由於雲端處理的使用增加，混合雲的興起推動了 GPUaaS 的成長。

GPUaaS市場面臨的挑戰是：

先進GPU資源高成本：先進GPU和服務的高成本負擔可能會對某些業務造成障礙。
整合複雜性：將 GPUaaS 納入現有的資訊技術系統和應用程式非常困難。
資料安全和隱私問題：確保雲端中的資料安全和隱私是大多數 GPUaaS 供應商面臨的主要挑戰。
效能變化：GPUaaS 解決方案的有效性可能會受到共用雲端資源導致的效能變化的影響。
法規合規性：對於許多 GPUaaS 提供者來說，合規性問題和資料保護條例非常複雜。
技能和專業知識要求：設定和管理 GPUaaS 解決方案可能需要額外的技能和專業知識，這對某些組織來說可能是一個障礙。

對高運算能力的需求不斷增加、GPU 技術的變化、市場擴展能力、降低成本、向雲端解決方案的轉變以及安全性的提高是推動 GPUaaS 市場發展的一些因素。然而，高價格、整合複雜性、安全風險、效能問題、合規風險以及需要專業技能等挑戰仍有待解決，阻礙了進一步發展和廣泛採用。

宏觀經濟趨勢（2019-2024）與預測（2025-2031）
全球 GPUaaS（GPU 即服務）市場趨勢（2019-2024 年）與預測（2025-2031 年）
全球 GPUaaS（GPU 即服務）市場：部署方法
- 私有GPU雲
- 公有 GPU 雲
- 混合 GPU 雲
全球 GPUaaS（GPU 即服務）市場（按應用）
- 醫療
- BFSI
- 製造業
- 資訊科技/通訊
- 車
- 其他

第 4 章區域市場趨勢與預測分析（2019-2031 年）

全球 GPUaaS（GPU 即服務）市場區域分佈
北美 GPUaaS（GPU 即服務）市場
歐洲 GPUaaS（GPU 即服務）市場
亞太地區 GPUaaS（GPU 即服務）市場
世界其他地區的 GPUaaS（GPU 即服務）市場

第5章競爭分析

產品系列分析
營運整合
波特五力分析

第6章成長機會與策略分析

成長機會分析
- 以部署方式分類的全球 GPUaaS（GPU 即服務）市場成長機會
- 全球 GPUaaS（GPU 即服務）市場成長機會（按應用分類）
- 全球 GPUaaS（GPU 即服務）市場按區域分類的成長機會
全球 GPUaaS（GPU 即服務）市場的新趨勢
戰略分析
- 新產品開發
- 全球GPUaaS（GPU即服務）市場容量擴張
- 全球 GPUaaS（GPU 即服務）市場的企業合併
- 認證和許可

第7章主要企業簡介

Alibaba Cloud
Vultr
Linode
Amazon Web Services
Google
IBM
OVH
Lambda
Hewlett Packard Enterprise Development
CoreWeave

簡介目錄

The future of the global GPU as a service market looks promising with opportunities in the healthcare, BFSI, manufacturing, IT & telecommunication, and automotive applications. The global GPU as a service market is expected to reach an estimated $21.9 billion by 2031 with a CAGR of 26.8% from 2025 to 2031. The major drivers for this market are the growing emphasis on research and development within the gaming and design sectors, the escalating adoption of machine learning and AI-based applications among various industries, and the rising demand for advanced data analytics.

Lucintel forecasts that, within the deployment model category, private is expected to witness the highest growth over the forecast period.
In terms of regions, North America will remain the largest region over the forecast period.

Gain valuable insights for your business decision with our comprehensive 150+ page report.

Emerging Trends in the GPU as a Service Market

The changes occurring in the GPU as a Service (GPUaaS) market can be traced to the evolution of technology, the growing need for computational power, and changing customer preferences.

AI and Machine Learning Integration: Experts predict that GPUaaS will be highly utilized to improve AI and machine learning initiatives with the capability to train models faster and process more data in real time.
Edge Computing and IoT: The use of GPUaaS in conjunction with edge computing and IoT devices is improving the quality of real-time data analysis and decision-making.
Hybrid and Multi-Cloud Environments: Organizations are moving towards a hybrid and multi-cloud approach, wherein multiple GPUaaS solutions are deployed on different cloud platforms to enhance performance and minimize costs.
Enhanced Security and Compliance: The growing need for security and compliance, including data protection legislation, poses challenges for providers in delivering such services.
Customizable and Scalable Solutions: There is also rising interest in GPUaaS offerings that are dynamic in nature and adaptable to various use cases and business requirements.
Increased Focus on Cost Efficiency: Service providers are structuring their pricing to encourage the use of GPUaaS and its variants, including pay-as-you-go and reserved instance pricing.

Recent trends in the GPUaaS market include deeper synergies with artificial intelligence and machine learning, the use of edge computing and IoT, hybrid and multi-cloud environments, improved security, flexible offerings, and greater cost efficiency-all responding to advancing technologies and customer needs.

Recent Developments in the GPU as a Service Market

Recent developments in the GPU as a Service (GPUaaS) market focus on advancing new technologies, expanding service offerings, and growing subscriber bases in various sectors.

New Advanced GPU Models: Major players in the cloud computing market have been releasing new high-computation task-optimized GPU models, including those for AI and machine learning.
Cloud Provider Offerings Expansion: Prominent GPUaaS providers, such as AWS, Azure, and Google Cloud, have expanded their GPUaaS portfolios beyond merely assembling GPUs into boxes and offering them with limited configurations.
Data Security Measures Enhancement: Service providers are developing advanced protective measures to help maintain data safety and legal compliance.
Growth of GPUaaS in Emerging Economies: The expansion of GPUaaS in developing markets, such as India and China, addresses the desire for computational resources across various industries.
Development of Hybrid and Multi-Cloud Solutions: The integration of GPU as a Service (GPUaaS) in hybrid and multi-cloud models is helping with performance optimization and efficient cost management within organizations.
Investment in Research and Development: High levels of research and development activities are creating new, innovative technologies and GPU models, improving the efficiency of the GPU as a Service model.

Other recent changes in the GPUaaS market include the deployment of new GPU models, an expanding portfolio of services, increasing security measures in various regions, the development of hybrid and multi-cloud solutions, and rising research and development expenditures indicating continuous improvements in the marketplace.

Strategic Growth Opportunities for GPU as a Service Market

The landscape of growing opportunities in the GPU as a Service (GPUaaS) market is evolving across various critical applications due to technological advancements and market needs.

AI and Machine Learning: Tapping into GPUaaS for artificial intelligence and machine learning applications presents immense growth potential, as these technologies are computationally intensive during both training and inference stages.
Data Analytics and Big Data: With the availability of vast amounts of data, many industries are increasingly relying on GPUaaS for data processing and executing intensive analytic workloads in finance, healthcare, and retail.
Gaming and Virtual Reality: The gaming and virtual reality sectors constantly require efficient GPUs; therefore, GPUaaS fills the gap needed for game creation and vivid content acquisition.
Edge Computing: The combination of GPUaaS and edge computing can enhance real-time data processing and analysis, providing opportunities in verticals such as the Internet of Things and smart cities.
Hybrid Cloud Solutions: GPUaaS providers can facilitate transitions by offering cost-effective GPUaaS solutions that integrate with on-premise and other cloud infrastructures.
Research and Development: A gradual increase in investment in research and development to build new GPU technologies and service models opens new revenue and geographical horizons for GPUaaS.

The GPUaaS market is poised for growth in various complex opportunities, including AI and machine learning, big data and analytics, gaming and virtual reality, edge computing, hybrid cloud solutions, and research and development.

GPU as a Service Market Driver and Challenges

The GPU as a Service (GPUaaS) market faces both driving factors and challenges that impact its growth and development.

The factors driving the GPUaaS market include:

Growing Demand for High-Performance Computing: The increasing need for high-performance computing for AI, machine learning, and data analysis contributes to rising demands for GPUaaS.
Advancements in GPU Technologies: Ongoing advancements in GPU technologies continue to enhance GPUaaS solutions and improve their acceptance.
Scalability and Flexibility: Businesses can enter and adjust GPUaaS based on the volume of their workloads.
Cost Efficiency: Businesses can access GPUaaS at lower costs through pay-as-you-go and reserved instance models.
Increased Adoption of Cloud Computing: The expansion of hybrid clouds is boosting the growth of GPUaaS due to the increasing use of cloud computing.

Challenges in the GPUaaS market include:

High Cost of Advanced GPU Resources: The major cost burden of advanced GPUs and services can be a dealbreaker for certain enterprises.
Complexity of Integration: Incorporating GPUaaS into existing information technology systems and applications can be challenging.
Data Security and Privacy Concerns: Ensuring security and privacy for data in the cloud presents a significant challenge for most GPUaaS providers.
Performance Variability: The efficacy of GPUaaS solutions can be affected by performance variability due to shared cloud resources.
Regulatory Compliance: Navigating compliance issues and data protection regulations can be complicated for many GPUaaS providers.
Skill and Expertise Requirements: Setting up and managing GPUaaS solutions may require additional skills and expertise, which can be a hurdle for some organizations.

The growing need for high computing power, changes in GPU technology, the ability to expand the market, low costs, the transition to cloud solutions, and improved security are driving the GPUaaS market. However, challenges such as high prices, complexity of integration, security risks, performance issues, compliance risks, and the need for specialized skills remain unresolved, hindering further development and adoption.

List of GPU as a Service Companies

Companies in the market compete on the basis of product quality offered. Major players in this market focus on expanding their manufacturing facilities, R&D investments, infrastructural development, and leverage integration opportunities across the value chain. Through these strategies GPU as a service companies cater increasing demand, ensure competitive effectiveness, develop innovative products & technologies, reduce production costs, and expand their customer base. Some of the GPU as a service companies profiled in this report include-

Alibaba Cloud
Vultr
Linode
Amazon Web Services
Google
IBM
OVH
Lambda
Hewlett Packard Enterprise Development
CoreWeave

GPU as a Service by Segment

The study includes a forecast for the global GPU as a service market by deployment model, application, and region.

GPU as a Service Market by Deployment Model [Analysis by Value from 2019 to 2031]:

Private GPU Cloud
Public GPU Cloud
Hybrid GPU Cloud

GPU as a Service Market by Application [Analysis by Value from 2019 to 2031]:

Healthcare
BFSI
Manufacturing
IT & Telecommunication
Automotive
Others

GPU as a Service Market by Region [Analysis by Value from 2019 to 2031]:

North America
Europe
Asia Pacific
The Rest of the World

Country Wise Outlook for the GPU as a Service Market

Major players in the GPUaaS market are expanding operations and forming strategic partnerships to strengthen their positions. Recent developments by major GPUs as a service producer in key regions include the USA, China, India, and Japan.

USA: The GPU as a Service (GPUaaS) market in the USA is rising due to improvements in cloud computing and artificial intelligence (AI). Companies such as Amazon Web Services, Microsoft Azure, and Google Cloud have added GPUaaS capabilities, offering high scalability and speedy GPU devices for machine learning, data analysis, video rendering, and more. NVIDIA has also released new generations of GPUs specifically designed for use in cloud services, expected to elevate the level of GPUaaS. The GPUaaS market in the US is rapidly being adopted by both tech startups and large corporations for heavy computing workloads.
China: The GPUaaS market potential in China is growing rapidly, driven by policies that increasingly embrace cloud computing and AI investments. Companies including Alibaba Cloud and Tencent Cloud are leaders in the GPUaaS industry, providing solutions for finance, healthcare, entertainment, and other sectors. Current prospects in this field include offering more powerful GPUs and upgrading infrastructure to accommodate high computational processes in the cloud. Government policies aimed at innovation and technology development are further advancing GPUaaS, focusing on building reusable infrastructure for AI and big data ecosystems.
India: The GPUaaS market in India is supporting businesses and emerging companies as more organizations turn to cloud-based solutions for computing tasks. Early adopters of this service, including AWS and Microsoft Azure, have introduced GPUaaS offerings in sectors like finance, e-commerce, and technology. The Indian government's initiatives toward digitalization and innovation adoption have increased the consumption of GPUaaS. Specifically, Indian IT companies and research institutions are harnessing GPUaaS for AI and R&D, leading to greater availability of high-performance computing in the market and subsequently driving growth in the GPUaaS sector.
Japan: The rising application areas of robotics, gaming, and AI are driving growth in the GPUaaS market in Japan. Companies like NEC and Fujitsu are exploring diverse scenarios by proposing GPUaaS solutions to enhance their cloud service offerings. Recent developments include GPU-offload solutions and global cloud partnerships aimed at expanding GPUaaS capacity. The Japanese government is also working on integrating GPUaaS and other high-performance computing features as part of a national communications and information structure policy to foster innovation and maintain global market leadership in technology.

Features of the Global GPU as a Service Market

Market Size Estimates: GPU as a service market size estimation in terms of value ($B).

Trend and Forecast Analysis: Market trends (2019 to 2024) and forecast (2025 to 2031) by various segments and regions.

Segmentation Analysis: GPU as a service market size by deployment model, application, and region in terms of value ($B).

Regional Analysis: GPU as a service market breakdown by North America, Europe, Asia Pacific, and Rest of the World.

Growth Opportunities: Analysis of growth opportunities in different deployment models, applications, and regions for the GPU as a service market.

Strategic Analysis: This includes M&A, new product development, and competitive landscape of the GPU as a service market.

Analysis of competitive intensity of the industry based on Porter's Five Forces model.

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This report answers following 11 key questions:

Q.1. What are some of the most promising, high-growth opportunities for the GPU as a service market by deployment model (private GPU cloud, public GPU cloud, and hybrid GPU cloud), application (healthcare, BFSI, manufacturing, IT & telecommunication, automotive, and others), and region (North America, Europe, Asia Pacific, and the Rest of the World)?
Q.2. Which segments will grow at a faster pace and why?
Q.3. Which region will grow at a faster pace and why?
Q.4. What are the key factors affecting market dynamics? What are the key challenges and business risks in this market?
Q.5. What are the business risks and competitive threats in this market?
Q.6. What are the emerging trends in this market and the reasons behind them?
Q.7. What are some of the changing demands of customers in the market?
Q.8. What are the new developments in the market? Which companies are leading these developments?
Q.9. Who are the major players in this market? What strategic initiatives are key players pursuing for business growth?
Q.10. What are some of the competing products in this market and how big of a threat do they pose for loss of market share by material or product substitution?
Q.11. What M&A activity has occurred in the last 5 years and what has its impact been on the industry?

1. Executive Summary

2. Global GPU as a Service Market : Market Dynamics

2.1: Introduction, Background, and Classifications
2.2: Supply Chain
2.3: Industry Drivers and Challenges

3. Market Trends and Forecast Analysis from 2019 to 2031

3.1. Macroeconomic Trends (2019-2024) and Forecast (2025-2031)
3.2. Global GPU as a Service Market Trends (2019-2024) and Forecast (2025-2031)
3.3: Global GPU as a Service Market by Deployment Model
- 3.3.1: Private GPU Cloud
- 3.3.2: Public GPU Cloud
- 3.3.3: Hybrid GPU Cloud
3.4: Global GPU as a Service Market by Application
- 3.4.1: Healthcare
- 3.4.2: BFSI
- 3.4.3: Manufacturing
- 3.4.4: IT & Telecommunication
- 3.4.5: Automotive
- 3.4.6: Others

4. Market Trends and Forecast Analysis by Region from 2019 to 2031

4.1: Global GPU as a Service Market by Region
4.2: North American GPU as a Service Market
- 4.2.1: North American Market by Deployment Model: Private GPU Cloud, Public GPU Cloud, and Hybrid GPU Cloud
- 4.2.2: North American Market by Application: Healthcare, BFSI, Manufacturing, IT & Telecommunication, Automotive, and Others
4.3: European GPU as a Service Market
- 4.3.1: European Market by Deployment Model: Private GPU Cloud, Public GPU Cloud, and Hybrid GPU Cloud
- 4.3.2: European Market by Application: Healthcare, BFSI, Manufacturing, IT & Telecommunication, Automotive, and Others
4.4: APAC GPU as a Service Market
- 4.4.1: APAC Market by Deployment Model: Private GPU Cloud, Public GPU Cloud, and Hybrid GPU Cloud
- 4.4.2: APAC Market by Application: Healthcare, BFSI, Manufacturing, IT & Telecommunication, Automotive, and Others
4.5: ROW GPU as a Service Market
- 4.5.1: ROW Market by Deployment Model: Private GPU Cloud, Public GPU Cloud, and Hybrid GPU Cloud
- 4.5.2: ROW Market by Application: Healthcare, BFSI, Manufacturing, IT & Telecommunication, Automotive, and Others

5. Competitor Analysis

5.1: Product Portfolio Analysis
5.2: Operational Integration
5.3: Porter's Five Forces Analysis

6. Growth Opportunities and Strategic Analysis

6.1: Growth Opportunity Analysis
- 6.1.1: Growth Opportunities for the Global GPU as a Service Market by Deployment Model
- 6.1.2: Growth Opportunities for the Global GPU as a Service Market by Application
- 6.1.3: Growth Opportunities for the Global GPU as a Service Market by Region
6.2: Emerging Trends in the Global GPU as a Service Market
6.3: Strategic Analysis
- 6.3.1: New Product Development
- 6.3.2: Capacity Expansion of the Global GPU as a Service Market
- 6.3.3: Mergers, Acquisitions, and Joint Ventures in the Global GPU as a Service Market
- 6.3.4: Certification and Licensing