한글목차

세계 GPUaaS(GPU as a Service) 시장의 미래는 의료, 은행/금융서비스/보험(BFSI), 제조, IT 및 통신, 자동차 용도의 기회로 유망시되고 있습니다. 세계 GPUaaS(GPU as a Service) 시장은 2025년부터 2031년까지의 CAGR이 26.8%로 2031년까지 219억 달러에 이를 것으로 추정됩니다. 이 시장의 주요 추진 요인은 게임 및 디자인 분야에서 R&D의 중요성이 높아지고, 다양한 산업에서 머신러닝 및 AI 기반 용도 채택 확대, 고급 데이터 분석에 대한 수요 증가입니다.

• Lucintel의 예측에서는 배포 모델의 범주에서 개인 유형이 예측 기간 동안 가장 높은 성장을 이룰 것으로 예상됩니다.
• 지역별로는 북미가 예측 기간 동안 가장 규모가 큰 지역이 될 것으로 예상됩니다.

GPUaaS(GPU as a Service) 시장의 전략적 성장 기회

GPUaaS(GPU as a Service) 시장에서의 성장 기회 전망은 기술의 진보와 시장의 요구에 따라 다양한 중요한 용도으로 진화하고 있습니다.

• 인공지능 및 머신러닝 : 인공지능 및 머신러닝 응용 분야에서 GPUaaS를 활용하는 것은 이러한 기술이 학습과 추론의 두 단계에서 계산 집약적이기 때문에 엄청난 성장 가능성을 나타냅니다.
• 데이터 분석 및 빅데이터 : 방대한 양의 데이터를 사용할 수 있게 됨으로써 금융, 의료, 소매업 등에서는 데이터 처리 및 집중적인 분석 워크로드 실행에 GPUaaS를 이용하는 업계가 증가하고 있습니다.
• 게임 및 가상현실 : 그러므로 GPUaaS는 게임 제작과 선명한 컨텐츠 획득에 필요한 격차를 메워줍니다.
• 에지 컴퓨팅 : GPUaaS와 에지 컴퓨팅의 조합은 실시간 데이터 처리 및 분석을 강화할 수 있으며 사물 인터넷 및 스마트 시티와 같은 수직 분야에서 기회를 제공합니다.
• 하이브리드 클라우드 솔루션 : GPUaaS 제공업체는 온프레미스 및 기타 클라우드 인프라와 통합하는 비용 효율적인 GPUaaS 솔루션을 제공함으로써 마이그레이션을 가속화할 수 있습니다.
• R&D : 새로운 GPU 기술과 서비스 모델을 구축하기 위한 R&D 투자가 점차 증가하고 GPUaaS의 새로운 수익과 지리적 수평이 열립니다.

GPUaaS(GPU as a Service) 시장은 AI와 머신러닝, 빅데이터와 분석, 게임과 가상현실, 엣지컴퓨팅, 하이브리드 클라우드 솔루션, R&D 등 다양한 복합 기회에서 성장하는 태세가 갖추어지고 있습니다.

GPUaaS(GPU as a Service) 시장 성장 촉진요인 및 과제

GPUaaS(GPU as a Service) 시장은 성장과 개척에 영향을 미치는 촉진요인과 문제에 직면해 있습니다.

GPUaaS(GPU as a Service) 시장을 견인하는 요인은 다음과 같습니다.

• 고성능 컴퓨팅에 대한 수요 증가 : 인공지능, 머신러닝 및 데이터 분석을 위한 고성능 컴퓨팅에 대한 수요 증가는 GPUaaS에 대한 수요 증가에 기여합니다.
• GPU 기술의 진보 : GPU 기술의 지속적인 발전으로 GPUaaS 솔루션이 강화되고 그 수용성이 계속 향상되고 있습니다.
• 확장성과 유연성 : 기업은 워크로드의 양에 따라 GPUaaS에 진입하고 조정할 수 있습니다.
• 비용 효율성 : 기업은 종량 청구 모델 및 예약 인스턴스 모델을 통해 저비용으로 GPUaaS에 액세스할 수 있습니다.
• 클라우드 컴퓨팅 채택 확대 : 하이브리드 클라우드의 확대는 클라우드 컴퓨팅 사용 증가로 GPUaaS의 성장을 뒷받침하고 있습니다.

GPUaaS(GPU as a Service) 시장의 과제는 다음과 같습니다.

• 고급 GPU 리소스의 고비용 : 고급 GPU와 서비스에 소요되는 비용 부담은 특정 기업의 장벽이 될 수 있습니다.
• 통합 복잡성 : GPUaaS를 기존의 정보 기술 시스템과 용도에 통합하는 것은 어렵습니다.
• 데이터 보안 및 개인 정보 보호에 대한 우려 : 클라우드에서 데이터 보안 및 개인 정보 보호를 보장하는 것은 대부분의 GPUaaS 제공업체에게 중요한 과제입니다.
• 성능 편차 : GPUaaS 솔루션의 효율성은 공유 클라우드 리소스의 성능 편차에 영향을 받을 수 있습니다.
• 규정 준수 : 많은 GPUaaS 제공업체의 경우 규정 준수 문제와 데이터 보호 규정에 대한 대응이 복잡합니다.
• 기술 및 전문 지식 요구 사항 : GPUaaS 솔루션을 설정하고 관리하려면 추가 기술과 전문 지식이 필요할 수 있으며 일부 조직에서는 장애물이 될 수 있습니다.

높은 연산 능력에 대한 요구 증가, GPU 기술의 변화, 시장 확대 능력, 저비용, 클라우드 솔루션으로의 이행, 보안의 향상 등이 GPUaaS(GPU as a Service) 시장을 견인하고 있습니다. 그러나 고가, 통합 복잡성, 보안 리스크, 성능 문제, 컴플라이언스 리스크, 전문 기술의 필요성 등의 과제는 여전히 해결되지 않았으며 추가 개발과 보급을 방해하고 있습니다.

목차

제1장 주요 요약

제2장 세계의 GPUaaS(GPU as a Service) 시장 : 시장 역학

• 서론, 배경, 분류
• 공급망
• 업계의 성장 촉진요인과 과제

제3장 시장 동향과 예측 분석(2019-2031년)

• 거시경제 동향(2019-2024년)과 예측(2025-2031년)
• 세계의 GPUaaS(GPU as a Service) 시장 동향(2019-2024년)과 예측(2025-2031년)
• 세계의 GPUaaS(GPU as a Service) 시장 : 배포 모델별
  • 프라이빗 GPU 클라우드
  • 퍼블릭 GPU 클라우드
  • 하이브리드 GPU 클라우드
• 세계의 GPUaaS(GPU as a Service) 시장 : 용도별
  • 의료
  • BFSI
  • 제조업
  • IT 및 통신
  • 자동차
  • 기타

제4장 지역별 시장 동향과 예측 분석(2019-2031년)

• 세계의 GPUaaS(GPU as a Service) 시장 : 지역별
• 북미의 GPUaaS(GPU as a Service) 시장
• 유럽의 GPUaaS(GPU as a Service) 시장
• 아시아태평양의 GPUaaS(GPU as a Service) 시장
• 기타 지역의 GPUaaS(GPU as a Service) 시장

제5장 경쟁 분석

• 제품 포트폴리오 분석
• 운영 통합
• Porter's Five Forces 분석

제6장 성장 기회와 전략 분석

• 성장 기회 분석
  • 세계의 GPUaaS(GPU as a Service) 시장 성장 기회 : 배포 모델별
  • 세계의 GPUaaS(GPU as a Service) 시장 성장 기회 : 용도별
  • 세계의 GPUaaS(GPU as a Service) 시장 성장 기회 : 지역별
• 세계 GPUaaS(GPU as a Service) 시장의 새로운 동향
• 전략적 분석
  • 신제품 개발
  • 세계의 GPUaaS(GPU as a Service) 시장 생산 능력 확대
  • 세계의 GPUaaS(GPU as a Service) 시장 기업 합병·인수(M&A), 합작 사업
  • 인증 및 라이선싱

제7장 주요 기업 프로파일

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

영문목차

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.

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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?

Table of Contents

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

7. Company Profiles of Leading Players

• 7.1: Alibaba Cloud
• 7.2: Vultr
• 7.3: Linode
• 7.4: Amazon Web Services
• 7.5: Google
• 7.6: IBM
• 7.7: OVH
• 7.8: Lambda
• 7.9: Hewlett Packard Enterprise Development
• 7.10: CoreWeave