China Advances AI Chip Self-Sufficiency, Yet Struggles with High-End Development

Huawei’s subsidiary HiSilicon has made notable progress in the independent research and development of AI chips with the launch of the next-gen Ascend 910B. These chips are not only used in Huawei’s public cloud infrastructure but also sold to other Chinese companies. Baidu, for instance, has ordered over a thousand Ascend 910B chips to build around 200 AI servers. Additionally, iFlytek, in collaboration with Huawei, has released the “Gemini Star Program,” a hardware and software integrated device for exclusive enterprise LLMs, equipped with the Ascend 910B AI acceleration chip.

According to TrendForce’s research, it is speculated that the next-generation Ascend 910B chip is manufactured using SMIC’s N+2 process. However, there are two potential risks in production. Firstly, as Huawei has been focusing on expanding its smartphone business, the N+2 process capacity at SMIC is primarily allocated to Huawei’s smartphone products, which could limit future capacity for AI chips. Secondly, SMIC is on the Entity List, which may restrict access to advanced process equipment.

Market analysis suggests that the performance of the Ascend 910B slightly lags behind the A800 series, and its software ecosystem differs significantly from nVidia’s CUDA, affecting usage efficiency. However, considering the potential expansion of U.S. restrictions, Chinese manufacturers might be compelled to shift towards the Ascend 910B. There is still considerable potential for China to improve and establish a complete AI ecosystem.

Chinese cloud service providers (CSPs) like Baidu and Alibaba are actively investing in autonomous AI chip development due to U.S. sanctions. Baidu has developed its first self-researched ASIC AI chip called Kunlunxin, with plans for mass production of its second generation in 2021 and the third generation expected to launch in 2024. After 2023, Baidu aims to use Huawei’s Ascend 910B acceleration chips and expand the use of Kunlunxin chips for its AI infrastructure.

Alibaba, on the other hand, acquired CPU IP supplier Zhongtian Micro Systems in 2018 and established T-Head Semiconductor the same year to develop its own ASIC AI chips, including the Hanguang 800. Initially, T-Head’s ASIC chips were co-designed with external companies like GUC, but after 2023, Alibaba is expected to rely more on its internal resources to enhance the independent design capabilities of its next-gen ASIC chips, primarily for Alibaba Cloud’s AI infrastructure.

The U.S. sanctions have limited China’s high-end AI chip development. The inclusion of companies like Biren and Moore Threads in the Entity List and the introduction of regulations governing advanced manufacturing processes have complicated the supply of high-end AI chips from leading manufacturers like NVIDIA and AMD. Furthermore, restrictions on EDA semiconductor design software tools have affected the design of advanced processes. While these restrictions may not have an immediate significant impact, they pose long-term challenges for China in adopting more advanced processes and developing next-gen, higher-performance HPC or AI chips.

Background Information

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About AMD:

AMD, a large player in the semiconductor industry is known for its powerful processors and graphic solutions, AMD has consistently pushed the boundaries of performance, efficiency, and user experience. With a customer-centric approach, the company has cultivated a reputation for delivering high-performance solutions that cater to the needs of gamers, professionals, and general users. AMD's Ryzen series of processors have redefined the landscape of desktop and laptop computing, offering impressive multi-core performance and competitive pricing that has challenged the dominance of its competitors. Complementing its processor expertise, AMD's Radeon graphics cards have also earned accolades for their efficiency and exceptional graphical capabilities, making them a favored choice among gamers and content creators. The company's commitment to innovation and technology continues to shape the client computing landscape, providing users with powerful tools to fuel their digital endeavors.

  

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About nVidia:

NVIDIA has firmly established itself as a leader in the realm of client computing, continuously pushing the boundaries of innovation in graphics and AI technologies. With a deep commitment to enhancing user experiences, NVIDIA's client computing business focuses on delivering solutions that power everything from gaming and creative workloads to enterprise applications. for its GeForce graphics cards, the company has redefined high-performance gaming, setting industry standards for realistic visuals, fluid frame rates, and immersive experiences. Complementing its gaming expertise, NVIDIA's Quadro and NVIDIA RTX graphics cards cater to professionals in design, content creation, and scientific fields, enabling real-time ray tracing and AI-driven workflows that elevate productivity and creativity to unprecedented heights. By seamlessly integrating graphics, AI, and software, NVIDIA continues to shape the landscape of client computing, fostering innovation and immersive interactions in a rapidly evolving digital world.

  

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Technology Explained

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CPU: The Central Processing Unit (CPU) is the brain of a computer, responsible for executing instructions and performing calculations. It is the most important component of a computer system, as it is responsible for controlling all other components. CPUs are used in a wide range of applications, from desktop computers to mobile devices, gaming consoles, and even supercomputers. CPUs are used to process data, execute instructions, and control the flow of information within a computer system. They are also used to control the input and output of data, as well as to store and retrieve data from memory. CPUs are essential for the functioning of any computer system, and their applications in the computer industry are vast.

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EDA: EDA stands for Electronic Design Automation, and it refers to a category of software tools and solutions used in the design and development of electronic systems and integrated circuits. EDA tools assist engineers and designers in creating complex electronic designs, from individual components to entire systems, by automating various aspects of the design process. These tools encompass a wide range of functionalities, including schematic capture, simulation, layout design, verification, and testing.

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