GPUaaS(GPU as a Service) - 시장 점유율 분석, 산업 동향 및 통계, 성장 예측(2024-2029년)

The GPU As A Service Market size is estimated at USD 5.05 billion in 2024, and is expected to reach USD 18.20 billion by 2029, growing at a CAGR of 29.20% during the forecast period (2024-2029).

Key Highlights

• The global graphics processing unit market is primarily driven by the growing demand for specialized processors to manage complex mathematical calculations related to 2D and 3D graphics. The augmenting use of processors to support graphics applications and 3D content in several industry verticals, including manufacturing, automotive, real estate, and healthcare, is also increasing market growth. For instance, to encourage manufacturing and design applications in the automotive sector, CAD and simulation software support graphic processing units to generate photorealistic images or animations.
• GPUaaS companies offer virtualized GPUs that can be rented for a wide range of applications, eliminating the need for businesses to invest in costly computing infrastructure. Artificial intelligence and machine learning (ML) require large amounts of code and algorithms that run across thousands of pages. As a result, robust systems like GPUs are required to perform tasks that cannot be done using CPUs.
• In addition, new automotive models and machinery are becoming more advanced. With the advent of EV segments, a growing demand for data analysis and visualization using GPUs drives market growth. GPUs help to enable these operations without using equipment, making tasks possible across many industries.
• The GPUaaS industry has proven resilient and innovative, with continuous enhancements in performance and efficiencies, driving its growth across various industries. GPU as a Service (GPUaaS) has several advantages, including low costs, cloud service provider support, and on-demand scaling. The SaaS service model is projected to develop because of the end user's widespread adoption of cloud-based GPU solutions. The GPU market players increasingly focus on providing clients with SaaS-based solutions.
• Machine learning and artificial intelligence are emerging technologies in various sectors like healthcare, finance, manufacturing, and supply chain. Machine learning and artificial intelligence are utilized in image recognition and natural language processing. With the rapid training and interference times, AI and ML carry more extensive databases for analyzing and processing that can be computationally intensive. The graphic processing unit emerges as the primary technology in artificial intelligence and machine learning due to its parallel processing, which can handle the processing of large datasets.
• A few factors are preventing the GPU as a Service industry from growing. One of them is the high cost of implementation, which is expected to impede the market growth in the future. Further, the need to become more aware of advanced technologies and understand the benefits of GPU as a Service restricts the market growth.
• The outbreak and aftereffects of COVID-19 increased the usage of data. Moreover, it presented new opportunities for growing data generation due to increased remote working environments. The remote working environment is leading to the growth in hyper-scale data centers, creating a need for efficient networking.
• Various data center vendors consistently invest in new data centers that align with the insatiable need for data. According to the National Association of Software and Service Companies (NASSCOM), India's data center market investment is expected to reach USD 4.6 billion in 2025. India's higher cost efficiency in development and operation is its most significant advantage compared to more mature markets. India's data centers are mainly Mumbai, Bengaluru, Chennai, Delhi (NCR), Hyderabad, and Pune. Calcutta, Kerala, and Ahmedabad are the upcoming data center hubs. These growing data center market investments drive the demand in India's market.

GPU as a Service Market Trends

Automotive is Expected to Witness Remarkable Growth During Forecast Period

• GPUs solidify the graphics on the entertainment systems and dashboard instruments, allowing a smooth and reactive user interface. GPUs also support high-end vehicles with features like real-time ray tracing for a better immersive experience and deep learning super sampling to upscale images for sharp visuals without preceding performance.
• As ADAS and AVs increasingly rely on analyzing real-time sensor data (camera data, lidar data, radar data, etc.), GPUs are well-suited to handle the workload distributed across their cores, speeding up tasks such as object detection or scene understanding. Modern GPUs do not focus on graphics rendering. They can also run custom algorithms through frameworks like CUDA, which allow developers to leverage the GPU's power for specific automotive functions, such as AI and accelerated computing, fueling the transformation of the entire auto industry.
• The rising popularity of self-driving or autonomous vehicles is a primary growth factor for the demand for GPUs. Many new automobile models have various infotainment system options to aid the driver. Currently, parking cameras are required, particularly for larger vehicles with several dead angles, such as most SUVs. A camera on the front, back, or sides can help the driver avoid colliding with other vehicles, scraping sidewalks, etc. Consequently, a GPU is required to process all these cameras/sensors and render the image.
• In addition, automotive in-vehicle infotainment (IVI) systems have increasingly become more advanced. Premium models can have up to 12 displays with 4K resolution and features like gesture, voice, and facial recognition. Support for technologies, including Android Auto or Apple CarPlay, and larger screen sizes are the important elements of the consumer's wish lists while buying a new car. Automotive manufacturers have started using considerably more complex sensors and cameras to detect items in the surrounding area to improve this capability. The latest innovation is parking assistance with a bird's eye perspective. As a result, the GPU will analyze the sensors and render the complete area around the vehicle in real-time, allowing drivers to have a better awareness of their surroundings.
• Also, the automotive industry has experienced tremendous expansion during the previous decade. The development of affordable, efficient, and powerful electric cars was a major turning point for the industry. Significant innovations are analyzed to roll out as a result of autonomous driving. With significant research and computing power, autonomous vehicle implementation is analyzed to be witnessed during the forecast period, and a strong GPU (and CPU) is required to power artificial intelligence in a Tesla, BMW, Porsche, or any other vehicle. GPUs are also an integral feature of every modern car.

North America Accounts for Significant Market Share

• North America is one of the major investors and innovators in the global GPU as a Service market owing to the increasing domestic adoption and expanding regional data center, gaming, and AI market among consumers. The increase in demand for advanced technologies, such as data center servers, machine-to-machine communication, and AI, is significant compared to other regions. Therefore, it is expected to bring huge growth opportunities for the GPU as a Service market.
• The region's automotive and transport industry is one of the most important in the world due to the size of the domestic market and the use of mass production techniques. Over the past decade, the region's auto industry has grown dramatically from manufacturing to distribution, changing consumer preferences and new technology, pushing the industry into a historical change.
• North America is home to various companies like Honda, Toyota, Ford, Chevrolet, and Tesla. It has been a pioneer in the automotive industry, especially in terms of automation, thus creating new opportunities for the vendors operating in the region. According to CAR (Center for Automotive Research), US motor vehicle production will reach 11.7 million units by 2025.
• The regional government has also developed a National AI Strategy, a policy framework that sets out a strategy for the United States to accelerate AI R&D and adoption. It also promotes investments to provide GPU as a Service and other computing resources, increase international collaboration, increase R&D funding, and ethically develop AI to reduce bias and protect privacy.
• Also, the adoption of cloud technology, increasing penetration of data centers, and increasing 5G technology further expand the market growth in the region. The increasing expansion of the region's data center and cloud market will also fuel the demand for GPU technology.

GPU as a Service Industry Overview

The GPU as a Service market is consolidated and dominated by a few leading vendors, such as NVIDIA, AWS, IBM, Oracle, Google LLC, and Microsoft Corporation. Companies continuously focus on enhancing their market presence by launching new products, expanding their operations, or entering into strategic mergers and acquisitions, partnerships, and collaborations.

• March 2024 - Amazon Web Services (AWS) and NVIDIA announced that the NVIDIA Blackwell GPU platform launched by NVIDIA in 2024 would be introduced on AWS. AWS will provide the NVIDIA B100 Tensor Core GPUs and GB200 Grace Blackwell Superchip, expanding the companies' strategic partnership to offer the most advanced and secure software, infrastructure, and services to assist customers in unlocking generative artificial intelligence (AI) capabilities.
• March 2024 - Singtel launched a GPU as a Service (GPUaaS) in Singapore and Southeast Asia, offering access to NVIDIA's AI Computing power to boost growth and innovation. Singtel's GPU as-a-service will be powered by "NVIDIA H100 Tensor Core GPU".

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 INSIGHTS

• 4.1 Market Overview
• 4.2 Industry Attractiveness - Porter's Five Forces Analysis
  • 4.2.1 Threat of New Entrants
  • 4.2.2 Bargaining Power of Buyers/Consumers
  • 4.2.3 Bargaining Power of Suppliers
  • 4.2.4 Threat of Substitute Products
  • 4.2.5 Intensity of Competitive Rivalry
• 4.3 Industry Value Chain Analysis
• 4.4 Impact of COVID-19 Aftereffects and Other Macroeconomic Factors on the Market
• 4.5 Vendor Service Pricing Analysis
• 4.6 GPU Vendor Analysis for Datacenter Servers

5 MARKET DYNAMICS

• 5.1 Market Drivers
  • 5.1.1 Rising Usage of Generative AI and LLM Models Across Enterprises
  • 5.1.2 Growing Applications of AR, VR, and AI
• 5.2 Market Challenges
  • 5.2.1 Data Security Concerns
  • 5.2.2 Lack of Skilled Workforce

6 MARKET SEGMENTATION

• 6.1 By Application
  • 6.1.1 Artificial Intelligence
  • 6.1.2 High Performance Computing
  • 6.1.3 Other Applications
• 6.2 By Enterprise Type
  • 6.2.1 Small and Medium Enterprise
  • 6.2.2 Large Enterprise
• 6.3 By End User
  • 6.3.1 BFSI
  • 6.3.2 Automotive
  • 6.3.3 Healthcare
  • 6.3.4 IT and Communication
  • 6.3.5 Other End Users
• 6.4 By Geography
  • 6.4.1 North America
  • 6.4.2 Europe
  • 6.4.3 Asia
  • 6.4.4 Australia and New Zealand
  • 6.4.5 Middle East and Africa
  • 6.4.6 Latin America

7 COMPETITIVE LANDSCAPE

• 7.1 Company Profiles
  • 7.1.1 Amazon Web Services Inc.
  • 7.1.2 Microsoft Corporation
  • 7.1.3 Nvidia DGX (Nvidia Corporation)
  • 7.1.4 IBM Corporation
  • 7.1.5 Oracle Systems Corporation
  • 7.1.6 Alphabet Inc (Google)
  • 7.1.7 Latitude.sh
  • 7.1.8 Seeweb
  • 7.1.9 Alibaba cloud
  • 7.1.10 Linode LLC
  • 7.1.11 CoreWeave

8 VENDOR RANKING ANALYSIS

9 MARKET OUTLOOK