Source: Photo.com
On April 11, it was reported that in fiscal year 2023, Nvidia's executive team did not receive any cash rewards for failing to meet specific financial goals, despite the booming sales of Nvidia's GPUs. However, thanks to the company's strong performance and shareholding structure, Nvidia has managed to avoid a significant brain drain.
Take, for example, CEO and founder Jensen Huang. His compensation level has remained at $2 million since fiscal year 2022, plus $4 million in incentive opportunities. His compensation did not change until the Board Compensation Committee announced a new plan for fiscal year 2025 last month. But it is understood that Huang was valued at nearly $500 million through the equity plan.
In addition, Nvidia plans to increase the price of gaming graphics cards, which is expected to increase by about 10%. Affected by reduced supply and increased market demand, the price of gaming graphics cards in Chinese mainland has generally risen, with RTX 4060 Ti and below rising by 10%.
The development history of the global GPU chip industry
Before 1984, GPUs were originally only used for graphics and image related operations, and were allocated by CPUs, but with the development of cloud computing, AI and other technologies, the advantages of GPU parallel computing have been explored, and CPUs have gradually replaced CPUs as the protagonists in the field of high-performance computing. In 1999, NVIDIA first introduced the concept of GPUs when it released its iconic product, the GeForce 256. In 2006, NVIDIA released the first desktop GPU with a unified rendering architecture and the CUDA general-purpose computing platform, enabling developers to use the computing power of NVIDIA GPUs for parallel computing and expanding the field of GPU applications. IN 2011, NVIDIA RELEASED THE TESLAGPU COMPUTING CARD, OFFICIALLY SEPARATING THE GPU PRODUCT LINE FOR COMPUTING, MARKING THE OFFICIAL ENTRY OF GPU CHIPS INTO THE ERA OF HIGH-PERFORMANCE COMPUTING.
The global market size is expected to exceed $32 billion by 2027
AI chips, also known as AI accelerators or compute cards, are modules that are specifically designed to handle a large number of computational tasks in AI applications. At present, artificial intelligence chips can be divided into CPU, GPU, FPGA, ASIC, and brain-like chips according to their technical architecture; According to their location in the network, they can be divided into cloud AI chips, edge AI chips, and terminal AI chips. According to its goals in practice, it can be divided into training chips and inference chips.
According to JPR data, it is expected that from 2022 to 2026, global GUP shipments will achieve a compound annual growth rate of 6.3%, and the market size of the global GPU chip industry is estimated to exceed $32 billion in 2027 at this growth rate.
According to forward-looking industry research, GPUs will still dominate the Al chip market in the short term, and will continue to lead Al chips in the short term. As the most mature and widely used general-purpose chip for Al computing on the market, GPU has great application potential. With its powerful computing power and high versatility, GPUs will continue to occupy the main market share of Al chips.
But for Nvidia's performance development, Tsai Chongxin, chairman of the board of directors of Alibaba Group, said that in October last year, the United States imposed very strict restrictions on the ability of companies like Nvidia to export high-end chips to all Chinese companies. Alibaba's cloud business and ability to provide high-end computing services to customers has also suffered, but in the long run, China can make these high-end GPUs on its own, not necessarily with Nvidia. This also means that Nvidia's position will be challenged to a certain extent.
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For more research and analysis of this industry, please refer to the "Market Prospect and Investment Strategic Planning Analysis Report of China's GPU Chip Industry" by Qianzhan Industry Research Institute
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