AI and Semiconductors A Server GPU Market Report & Size _ BIS Research

1. AI and Semiconductors A Server GPU Market Report & Size | BIS Research Introduction to AI and Semiconductors A Server GPU Market The global AI and semiconductor - a server GPU market accounted for $15.4 billion in 2023 and is expected to grow at a CAGR of 31.99% and reach $61.7 billion by 2028. The proliferation of edge computing, where data processing occurs closer to the source of data generation rather than relying solely on centralized cloud servers, is driving the demand for GPU servers. The increasing trend toward virtualization in data centers and enterprise environments is also a significant driver for GPU servers. The rapid acceleration of artificial intelligence (AI) in recent years has ignited a massive transformation across industries, with

2. semiconductors playing a critical role in this evolution. At the heart of this transformation lies the server GPU (Graphics Processing Unit) market, where AI workloads demand unprecedented computational power, driving innovation and growth in the semiconductor industry. The rapid development of machine learning and artificial intelligence applications is a major driver of this trend. A key element of AI and ML is the training of sophisticated neural networks, which is accelerated in large part by GPU servers. Companies such as Nvidia, for instance, have noticed a spike in demand for their GPU products, such as the Nvidia A100 Tensor Core GPU, which is intended especially for AI tasks. The global AI and semiconductor – server GPU market is growing as a result of the use of GPU servers by a variety of industries, including healthcare, finance, and autonomous cars, to handle large datasets and increase the precision of AI models. The Role of Semiconductors in AI Semiconductors, often referred to as the "brains" of electronic devices, are the building blocks of modern technology. They enable AI systems to process vast amounts of data quickly, efficiently, and in real-time. As AI applications become more complex and data-intensive, the need for specialized chips, particularly GPUs, has grown exponentially. GPUs, originally designed for rendering graphics in video games, have proven to be highly efficient at performing the parallel processing required for AI tasks such as deep learning, neural networks, and machine learning. The ability of GPUs to handle multiple data points simultaneously makes them ideal for handling large-scale AI computations, driving their adoption in server environments. The end-use application segment is a part of the application segment for the worldwide 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 global AI and Semiconductor – a server GPU market has also been divided into segments based on the kind of facility, which includes blockchain mining facilities, HPC clusters, and data centers (including hyperscale, colocation, enterprise, modular, and edge data centers). Request A Free Detailed Sample on AI and Semiconductors - A Server GPU Market! The Explosion of the Server GPU Market

3. The server GPU market has experienced explosive growth due to the rise of AI across sectors such as healthcare, finance, autonomous vehicles, and big tech companies like Google, Amazon, and Microsoft, which rely heavily on AI-driven cloud computing. Server GPUs are now indispensable in training AI models, running inference tasks, and supporting data centers that power AI operations. Key Drivers of Market Growth: AI-First Workloads: AI applications like natural language processing (NLP), computer vision, and speech recognition require massive computational resources that traditional CPUs struggle to handle. GPUs, with their parallel architecture, are uniquely suited to perform these tasks, leading to increased demand in AI-heavy industries. Data Explosion: The sheer volume of data generated by users, devices, and machines globally requires advanced data processing solutions. GPUs, coupled with specialized AI accelerators, help organizations extract valuable insights from this data quickly, further pushing demand. Cloud Computing and AI-as-a-Service: With more organizations adopting cloud-based AI solutions, the need for server GPUs has grown. Cloud providers are now offering AI-as-a-service models, where customers can access high-performance AI infrastructure without investing in expensive hardware. This trend is accelerating the growth of server GPU deployment. According to estimates, the data center category will have the biggest market share in 2022 and will continue to lead the market during the projection period. The push toward GPU-accelerated computing in data centers is fueled by GPU technological breakthroughs that provide increased energy efficiency and performance. GPU servers can transfer certain computations from conventional CPUs to GPU servers, which improves overall performance and reduces energy consumption. Consequently, the increasing use of GPU servers in data centers is in line with the changing requirements of companies and institutions that want to manage the sustainability and efficiency of their data center operations while achieving higher levels of processing capacity. The push toward GPU-accelerated computing in data centers is fueled by GPU technological breakthroughs that provide increased energy efficiency and performance. GPUs offer an efficient way to strike a balance between processing capacity and power consumption, which is something that data center operators are looking for in solutions. GPU servers can transfer certain computations from conventional CPUs to GPU servers, which improves overall performance and reduces energy consumption. Some prominent names established in this market are: Company Type 1: GPU Manufacturer

4. • • • Nvidia Corporation (Nvidia) Advanced Micro Devices, Inc. (AMD) Intel Corporation (Intel) Company Type 2: Server GPU Manufacturer • Dell Inc. • Penguin Computing, Inc. • Exxact Corporation The Future of AI and Semiconductors As AI continues to evolve, so too will the semiconductor industry. The future of server GPUs lies in pushing the boundaries of computational power, efficiency, and scalability. Semiconductor companies are exploring new materials like gallium nitride (GaN) and silicon carbide (SiC) to improve performance and reduce power consumption. In addition, advancements in quantum computing, neuromorphic chips, and edge AI processing will further redefine the role of semiconductors in AI. While server GPUs are currently the backbone of AI processing, the next generation of chips could shift the landscape even further. Conclusion The convergence of AI and semiconductors, particularly in the server GPU market, represents a fundamental shift in how industries leverage data and computational power. As AI workloads become more demanding, the need for advanced semiconductors will continue to drive innovation and growth in the server GPU market. This trend is not only reshaping the technology landscape but also creating new opportunities for businesses and industries globally.