Executive Summary

The global graphic processing unit (GPU) market size is experiencing explosive growth, transforming from a gaming-focused technology into a cornerstone of artificial intelligence and high-performance computing. The market was valued at USD 48.38 billion in 2023 and is projected to grow from USD 61.58 billion in 2024 to USD 461.02 billion by 2032, exhibiting an exceptional CAGR of 28.6% during the forecast period.

LIST OF KEY COMPANIES PROFILED:

• NVIDIA Corporation (U.S.)
• Advanced Micro Devices, Inc. (U.S.)
• Intel Corporation (U.S.)
• ASUSTeK Computer Inc. (Taiwan)
• GIGA-BYTE Technology Co. (Taiwan)
• PC Partner Group Limited (Hong Kong)
• EVGA (U.S.)
• SAPPHIRE Technology Limited. (Hong Kong)
• SAMSUNG (South Korea)
• Imagination Technologies (U.K.)

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Technology Evolution and AI Integration

GPUs have evolved far beyond their original graphics rendering purpose, becoming essential for AI and machine learning applications due to their parallel processing architecture. This capability enables thousands of simultaneous operations, perfectly aligning with neural network requirements in generative AI applications. ChatGPT exemplifies this evolution, utilizing hundreds of NVIDIA GPUs to serve over 100 million users worldwide.

The integration with generative AI technologies, including Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), has become a primary growth driver. These applications require massive parallel processing capabilities that GPUs provide more efficiently than traditional CPUs, enabling faster model training and inference for AI-generated content.

Market Drivers and Growth Catalysts

Artificial Intelligence and Machine Learning Dominance

The machine learning and artificial intelligence segment held the highest market share in 2023, driven by GPUs' superior performance in handling vast neural networks and mechanical calculations. GPUs deliver enhanced performance for AI training and inference across diverse implementations, significantly outperforming CPUs in efficiency and speed.