电子行业点评报告：算力芯片看点系列-GPGPU与ASIC之争

Investment Rating - The report maintains an "Overweight" investment rating for the electronic industry [1]. Core Viewpoints - The competition between GPGPU and ASIC chips is highlighted, with ASICs focusing on low-precision tasks and showing better power efficiency, but still lagging behind GPGPU in certain performance metrics [5][8]. - Major companies are increasingly investing in self-developed AI chips to meet the growing demand for AI applications, with significant capital expenditures expected to cover initial development costs [5][16]. - The report recommends investing in companies like Cambricon and Haiguang Information, while also suggesting to pay attention to ZTE, Aojie Technology, and Chipone [5]. Summary by Sections 1. GPGPU vs. ASIC Performance Comparison - ASICs primarily target low-precision data types, which are sufficient for large model training, while GPGPU excels in high-precision tasks [8]. - ASICs have better power control and efficiency for specific tasks, but GPGPU still outperforms in certain metrics, such as NVIDIA's GB200 [8][11]. - The report notes that ASICs have high computational density but face challenges in memory bandwidth compared to GPGPU [5][11]. 2. Reasons for Major Companies to Develop AI Chips - The report outlines the cost structure of chip companies, emphasizing that employee salaries constitute a significant portion of expenses [16][17]. - It estimates that a digital chip Fabless company requires approximately 9.7 billion yuan for employee salaries over a two-year product development cycle [18]. - The demand for AI inference is expected to grow significantly, with NVIDIA reporting that 40% of its data center revenue comes from inference business [18] . 3. Who Can Manufacture AI Chips for Major Companies? - Broadcom is identified as a leader in AI interconnect technology, with a strong IP ecosystem and significant market share in AI custom chip services [21][24]. - Marvell is noted for its rapid growth in the AI chip market, with a significant increase in AI-related revenue and partnerships with major cloud service providers [25][27]. - AIchip is recognized for its advanced 3DIC and process technology, which addresses efficiency and performance challenges in AI and high-performance computing [28][29].