The Global Data Center GPU Market size is expected to reach $114.2 billion by 2030, rising at a market growth of 32.3% CAGR during the forecast period.
Cloud service providers offering GPU instances in Canada will likely see increased demand as AI initiatives progress. Organizations looking to leverage AI technologies without investing heavily in on-premises infrastructure often turn to cloud-based GPU resources for scalability and flexibility. Therefore, the North America region generated a revenue of $5,044.6 million in 2022. With its advanced scientific research facilities and industries, North America witnessed increased demand for GPUs to power simulations, scientific research, and data analytics in data centers. Some of the factors affecting the market are increasing adoption of artificial intelligence and machine learning, growth in data analytics and big data processing and high initial cost of data center GPUS.
GPUs are designed with a highly parallel architecture, consisting of thousands of cores that can handle multiple tasks simultaneously. This parallelism is particularly beneficial for AI and ML workloads, which involve processing large datasets through parallel operations. AI and ML algorithms, especially deep learning models, heavily rely on matrix operations and linear algebra computations. These factors will help expand the data center GPU market. Moreover, Big data analytics involves performing complex computations on vast datasets. GPUs are designed with thousands of cores that can execute multiple tasks simultaneously, making them highly efficient for parallel processing. Parallelism facilitates the simultaneous completion of data processing duties, substantially reducing the time needed for analysis. These factors will drive the demand for data center GPU market.
Furthermore, Smaller enterprises often operate on tighter budgets compared to larger organizations. The high upfront cost of GPUs can pose a considerable challenge for these businesses, limiting their ability to invest in advanced GPU infrastructure for data center applications. The significant upfront investment required for GPU infrastructure can strain IT budgets for organizations of all sizes. This strain may lead to trade-offs between adopting GPU technology and allocating resources to other critical IT initiatives or operational needs. These aspects can limit the future expansion of the data center GPU market.
The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Acquisitions, and Partnerships Collaborations.
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The market research report covers the analysis of key stakeholders of the market. Key companies profiled in the report include NVIDIA Corporation, Intel Corporation, Advanced Micro Devices, Inc., Samsung Electronics Co., Ltd. (Samsung Group), Micron Technology, Inc., Qualcomm Incorporated (Qualcomm Technologies, Inc.), IBM Corporation, Google LLC (Alphabet Inc.), Microsoft Corporation, Imagination Technologies Limited.
Cloud service providers offering GPU instances in Canada will likely see increased demand as AI initiatives progress. Organizations looking to leverage AI technologies without investing heavily in on-premises infrastructure often turn to cloud-based GPU resources for scalability and flexibility. Therefore, the North America region generated a revenue of $5,044.6 million in 2022. With its advanced scientific research facilities and industries, North America witnessed increased demand for GPUs to power simulations, scientific research, and data analytics in data centers. Some of the factors affecting the market are increasing adoption of artificial intelligence and machine learning, growth in data analytics and big data processing and high initial cost of data center GPUS.
GPUs are designed with a highly parallel architecture, consisting of thousands of cores that can handle multiple tasks simultaneously. This parallelism is particularly beneficial for AI and ML workloads, which involve processing large datasets through parallel operations. AI and ML algorithms, especially deep learning models, heavily rely on matrix operations and linear algebra computations. These factors will help expand the data center GPU market. Moreover, Big data analytics involves performing complex computations on vast datasets. GPUs are designed with thousands of cores that can execute multiple tasks simultaneously, making them highly efficient for parallel processing. Parallelism facilitates the simultaneous completion of data processing duties, substantially reducing the time needed for analysis. These factors will drive the demand for data center GPU market.
Furthermore, Smaller enterprises often operate on tighter budgets compared to larger organizations. The high upfront cost of GPUs can pose a considerable challenge for these businesses, limiting their ability to invest in advanced GPU infrastructure for data center applications. The significant upfront investment required for GPU infrastructure can strain IT budgets for organizations of all sizes. This strain may lead to trade-offs between adopting GPU technology and allocating resources to other critical IT initiatives or operational needs. These aspects can limit the future expansion of the data center GPU market.
The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Acquisitions, and Partnerships Collaborations.
Deployment Type Outlook
Based on deployment type, the market is segmented into on-premises and cloud. In 2022, the cloud segment garnered a significant revenue share in the market. The overall growth of cloud services has been a major driver for the increased deployment of GPUs in cloud data centers. Cloud service providers offer scalable and on-demand computing resources, making it easier for organizations to access GPU-accelerated capabilities without significant upfront investments. Therefore, the segment is expected to grow rapidly in the coming years."data-center-gpu-market-share.jpg" title="Data Center GPU Market Share and Industry Analysis Report 2022"/>
Function Outlook
On the basis of function, the market is divided into training and inference. The training segment recorded the maximum revenue share in the data center GPU market in 2022. As AI models become more sophisticated and complex, the computational requirements for training these models also escalate. Modern neural networks with millions or even billions of parameters demand powerful hardware acceleration to reduce training times. GPUs provide the parallel processing capabilities required to handle the increased complexity of these networks. As a result, there will be increased demand in the segment.End User Outlook
Based on end user, the market is segmented into cloud service providers, enterprises, and government. In 2022, the cloud service providers segment witnessed the maximum revenue share in the market. GPU virtualization technologies enable multiple users or workloads to share GPU resources efficiently. Cloud providers have implemented GPU virtualization, allowing customers to run diverse GPU-accelerated workloads on the same physical GPU hardware. This enhances resource utilization and provides a cost-effective solution for users with varying computational requirements. As a result, the segment will witness increased growth in the segment.Regional Outlook
By region, the market is segmented into North America, Europe, Asia Pacific, and LAMEA. In 2022, the Europe segment acquired a considerable revenue share in the market. Expanding cloud computing services in Europe may increase demand for data center GPUs. Cloud service providers often utilize GPU acceleration to enhance the performance of their services, attracting businesses looking to leverage cloud-based GPU resources. Europe has been involved in various high-performance computing initiatives, particularly in scientific research and academia. If there is continued investment in HPC infrastructure, it could lead to increased demand for data center GPUs. These aspects will fuel the growth of the Europe segment.The market research report covers the analysis of key stakeholders of the market. Key companies profiled in the report include NVIDIA Corporation, Intel Corporation, Advanced Micro Devices, Inc., Samsung Electronics Co., Ltd. (Samsung Group), Micron Technology, Inc., Qualcomm Incorporated (Qualcomm Technologies, Inc.), IBM Corporation, Google LLC (Alphabet Inc.), Microsoft Corporation, Imagination Technologies Limited.
Scope of the Study
Market Segments Covered in the Report:
By End User
- Cloud Service Providers
- Enterprises
- Government
By Deployment Type
- On-premises
- Cloud
By Function
- Training
- Inference
By Geography
- North America
- US
- Canada
- Mexico
- Rest of North America
- Europe
- Germany
- UK
- France
- Russia
- Spain
- Italy
- Rest of Europe
- Asia Pacific
- China
- Japan
- India
- South Korea
- Singapore
- Malaysia
- Rest of Asia Pacific
- LAMEA
- Brazil
- Argentina
- UAE
- Saudi Arabia
- South Africa
- Nigeria
- Rest of LAMEA
Key Market Players
List of Companies Profiled in the Report:
- NVIDIA Corporation
- Intel Corporation
- Advanced Micro Devices, Inc.
- Samsung Electronics Co., Ltd. (Samsung Group)
- Micron Technology, Inc.
- Qualcomm Incorporated (Qualcomm Technologies, Inc.)
- IBM Corporation
- Google LLC (Alphabet Inc.)
- Microsoft Corporation
- Imagination Technologies Limited
Unique Offerings
- Exhaustive coverage
- The highest number of Market tables and figures
- Subscription-based model available
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- Assured post sales research support with 10% customization free
Table of Contents
Chapter 1. Market Scope & Methodology
Chapter 2. Market at a Glance
Chapter 3. Market Overview
Chapter 4. Competition Analysis - Global
Chapter 5. Global Data Center GPU Market, By End User
Chapter 6. Global Data Center GPU Market, By Deployment Type
Chapter 7. Global Data Center GPU Market, By Function
Chapter 8. Global Data Center GPU Market, By Region
Chapter 9. Company Profiles
Companies Mentioned
- NVIDIA Corporation
- Intel Corporation
- Advanced Micro Devices, Inc.
- Samsung Electronics Co., Ltd. (Samsung Group)
- Micron Technology, Inc.
- Qualcomm Incorporated (Qualcomm Technologies, Inc.)
- IBM Corporation
- Google LLC (Alphabet Inc.)
- Microsoft Corporation
- Imagination Technologies Limited
Methodology
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