Forecast An analysis and forecast of the server GPU market in relation to AI and semiconductors


An analysis and forecast of the server GPU market in relation to AI and semiconductors

Dublin, Jan. 23, 2024 (GLOBE NEWSWIRE) — The “AI and Semiconductors – A Server GPU Market – A Global and Regional Analysis: Focus on Application, Product, and Region – Analysis and Forecast, 2023-2028” report has been included in’s selection. The global AI and semiconductor – a server GPU market made up $15.4 billion in 2023 and is projected to grow at a CAGR of 31.99% and attain $61.7 billion by 2028. The spread of edge computing, where data processing happens closer to the source of data generation rather than relying solely on centralized cloud servers, is driving the requirement for GPU servers. The increasing trend toward virtualization in data centers and enterprise environments is also a notable driver for GPU servers.

The swift growth of machine learning and artificial intelligence applications is a major driver of this trend. A crucial element of AI and ML is the training of advanced neural networks, which is accelerated largely by GPU servers. Enterprises such as Nvidia, for example, have seen a spike in demand for their GPU products, such as the Nvidia A100 Tensor Core GPU, which is intended particularly for AI tasks. The worldwide AI and semiconductor – server GPU market is growing due to the use of GPU servers by a variety of businesses, including healthcare, finance, and autonomous cars, to process large datasets and enhance the accuracy of AI models.

The end-use application section is a part of the application section for the global AI and semiconductor – server GPU market. Cloud computing (private, public, and hybrid clouds) and HPC applications (scientific research, machine learning, artificial intelligence, and other applications) are included in the end-use application sector. The worldwide AI and Semiconductor – a server GPU market has also been separated into sections based on the type of facility, which includes blockchain mining facilities, HPC clusters, and data centers (including hyperscale, colocation, enterprise, modular, and edge data centers).

According to forecasts, the data center group will have the largest market share in 2022 and will continue to lead the market during the projection period. The trend toward GPU-accelerated computing in data centers is driven by GPU technology advancements that provide enhanced energy efficiency and performance. GPU servers can shift specific computations from traditional CPUs to GPU servers, which elevates overall performance and reduces energy consumption. Therefore, the rising usage of GPU servers in data centers is in harmony with the evolving requirements of corporations and establishments that aspire to manage the sustainability and efficiency of their data center operations while achieving higher levels of processing capability.

The trend toward GPU-accelerated computing in data centers is driven by GPU technology breakthroughs that provide enhanced energy efficiency and performance. GPUs offer an effective approach to strike a balance between processing capability and power consumption, which is something that data center operators are seeking in solutions. GPU servers can shift certain computations from traditional CPUs to GPU servers, which enhances overall performance and reduces energy consumption. As a result, the growing utilization of GPU servers in data centers is aligned with the changing requirements of corporations and institutions aiming to manage the sustainability and efficiency of their data center operations while achieving higher levels of processing capability.

Data center expansion and the growth of cloud computing services have further propelled the demand for GPU servers in North America. Cloud service providers, including industry giants such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud, are investing heavily in GPU infrastructure to provide customers high-performance computing capabilities on a scalable and cost-effective basis. This trend is particularly significant as businesses increasingly depend on cloud-based resources for AI training, simulation, and other GPU-intensive tasks.

Demand – Drivers, Challenges, and Opportunities

Market Drivers:

GPU server producers can capitalize on this need by providing customized cryptocurrency mining solutions, including rigs specifically designed for mining, cloud-based mining services, or GPU-as-a-service platforms. By charging fees, charging subscriptions, or entering into contracts, these systems can make money for the makers, while giving miners access to robust and scalable GPU resources.

The need for data center GPUs derives from their key role in AI model training and execution, which is particularly advantageous for enterprises engaged in computationally demanding tasks like engineering simulations and scientific research. Manufacturers of GPU servers can take advantage of this demand by providing specialized solutions for high-performance computing (HPC) applications, such as GPU-as-a-service platforms, cloud-based GPU services, and dedicated GPU servers. In addition to giving businesses scalable GPU resources, these customized services bring in revenue for the manufacturers through fees, subscriptions, or contracts.

Market Challenges:

The economies of scale provided by GPU manufacturers, most notably Nvidia, create a significant barrier to entry for manufacturers of data center GPU servers wishing to integrate backward. A company trying to backward integrate into the GPU production process, for example, would find it difficult to achieve equivalent economies of scale. This has an impact on the business’s capacity to maintain overall competitiveness, engage in research and development, and match prices. As a result, it might be difficult for producers of data center GPU servers to achieve comparable economies of scale, which could limit their efficacy in the extremely competitive market. In addition, a recurring issue for manufacturers of data center GPU servers is the constant innovation by GPU manufacturers, demonstrated by the continual development of GPUs, CPUs, and data processing units (DPUs).

Market Opportunities:

OpenAI’s GPT-4, the latest and largest language model, is one particular real-time example of how GPU servers may assist HPC and AI. It necessitated a significant amount of processing power to train on a vast dataset with over 1 trillion words. GPU servers, more specifically Nvidia H100 Tensor Core GPUs, played a significant role in speeding up the training process up to 60 times faster than CPUs alone. This acceleration was achieved using mixed-precision training to optimize both computing performance and memory usage. Thanks to this, GPT-4 could be trained in a few short weeks and achieve exceptional results in challenges involving natural language processing.

Artificial intelligence (AI) and advanced analytics play a vital role in smart cities as they optimize resource allocation, enhance public safety, and improve overall quality of life. Due to their suitability for AI and analytics workloads, GPU servers are becoming an essential part of the infrastructure for the development of smart cities.

Market Segmentation:

Segmentation by Application (End User)

  • Cloud Computing
  • HPC Application

Segmentation by Product (Configuration Type)

  • Single GPU
  • Dual to Quad GPU
  • High-Density GPU

Segmentation by Region

  • North America – U.S. and Rest-of-North America
  • Europe – Germany, France, Netherlands, Italy, Ireland, U.K., and Rest-of-Europe
  • Asia-Pacific – Japan, China, India, Australia, Singapore, and Rest-of-Asia-Pacific
  • Rest-of-the-World – Middle East and Africa and Latin America

Some prominent names established in this market are:

GPU Manufacturers

  • Nvidia Corporation (Nvidia)
  • Advanced Micro Devices, Inc. (AMD)
  • Intel Corporation (Intel)

Server GPU Manufacturers

  • Dell Inc.
  • Penguin Computing, Inc.
  • Exxact Corporation

Key Attributes:

Report Attribute Details
No. of Pages 127
Forecast Period 2023 – 2028
Estimated Market Value (USD) in 2023 $15.4 Billion
Forecasted Market Value (USD) by 2028 $61.7 Billion
Compound Annual Growth Rate 31.9%
Regions Covered Global

Key Topics Covered:

1 Market
1.1 Industry Outlook
1.1.1 Ongoing Trends Timeline of GPU and Server Design Upgrades Data Center Capacities: Current and Future Data Center Power Consumption Scenario Other Industrial Trends HPC Cluster Developments Blockchain Initiatives Super Computing 5G and 6G Developments Impact of Server/Rack Density
1.1.2 Equipment Upgrades and Process Improvements
1.1.3 Adaptive Cooling Solutions for Evolving Server Capacities Traditional Cooling Techniques Hot and Cold Aisle Containment Free Cooling and Economization Liquid Cooling Systems
1.1.4 Budget and Procurement Model of Data Center End Users
1.1.5 Stakeholder Analysis
1.1.6 Ecosystem/Ongoing Programs
1.2 Business Dynamics
1.2.1 Business Drivers Surging Demand for Cryptocurrency Mining Rising Enterprise Adoption of Data Center GPUs for High-Performance Computing Applications
1.2.2 Business Challenges High Bargaining Power of GPU Manufacturers
1.2.3 Market Strategies and Developments
1.2.4 Business Opportunities Technological Advancement in High-Performing Computing (HPC) Government Support for Smart City Development and Digitalization
1.3 Global Data Center GPU Market
1.3.1 Market Size and Forecast Data Center GPU Market (by Application and Product)

2 Application
2.1 Global AI and Semiconductors – A Server GPU Market (by Application)
2.1.1 Global Server GPU Market (by End-Use Application)
2.1.2 Global Server GPU Market (by Facility Type)

3 Products
3.1 Global AI and Semiconductors – A Server GPU Market (by Product)
3.1.1 Server GPU Market (by Configuration Type)
3.1.2 Server GPU Market (by Form Factor)
3.2 Pricing Analysis
3.3 Patent Analysis

4 Region
4.1 Global AI and Semiconductor – A Server GPU Market (by Region)

5 Markets – Competitive Benchmarking & Company Profiles
5.1 Competitive Benchmarking
5.2 Market Share Analysis
5.2.1 By GPU Manufacturer
5.2.2 By GPU Server Manufacturer
5.3 Company Profiles

  • Nvidia Corporation
  • Advanced Micro Devices
  • Intel
  • Qualcomm Technologies
  • Imagination Technologies
  • ASUSTeK Computer
  • Huawei Technologies
  • Super Micro Computer
  • GIGA-BYTE Technology
  • Penguin Computing
  • Advantech
  • Fujitsu
  • Dell Inc.
  • Exxact

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  • Global AI and Semiconductors Market

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