On October 17, 2023, the U.S. government unveiled an updated set of regulations for semiconductor exports, introducing stricter standards for advanced AI chips. Additionally, these regulations expand control over the export of exposure equipment and include Chinese GPU design startups on an Entity List.

TrendForce’s Insights: 

1. New regulations cover chips, manufacturing equipment, and related companies, signaling an effort to restrain China’s AI development.

In this latest set of regulations, the U.S. has relaxed the I/O bandwidth restrictions for AI chips and introduced three additional conditions beyond a total processing performance (TPP) of ≥ 4800 TOPS:

(1) Total processing performance ≥ 1600 TOPS and performance density (PD) ≥ 5.92

(2) Total processing performance ≥ 2400 TOPS but < 4800 TOPS and performance density ≥ 1.6 but < 5.92

(3) Total processing performance ≥ 1600 TOPS and performance density ≥ 3.2 but < 5.92

As a result of these new conditions, NVIDIA’s A800, H800 GPU, and the recent launched L40S GPU for the Chinese market are now included in the list of controlled exports, similar to the A100 and H100 GPUs that were added in September 2022.

Concerning manufacturing equipment, the control threshold for exposure equipment has shifted from single-machine (specified substrate) coverage precision of ≤ 1.5nm to > 1.5nm but ≤ 2.4nm. This change directly led to the inclusion of ASML’s 1980Di DUV lithography machines.

On the corporate front, Chinese domestic GPU design startups such as Birentech, Moore Threads, and high-speed DSP design company Superfusion Semiconductor, along with their related entities, have been placed on the Entity List by the U.S. Department of Commerce.

In summary, these new regulations encompass chips, manufacturing equipment, and related companies. The U.S. is not only controlling the current mainstream AI product lines and applications of DUV lithography machines for 28-7nm processes but is also making a clear effort to interfere Chinese domestic manufacturers’ development of AI computation chips, indicating a strong determination to restrict China’s growth in the AI sector.

2. Priority for Chinese Enterprises: Securing AI Computing Resources through Cloud Service Providers

In light of the impact of the new U.S. semiconductor control regulations, Chinese domestic companies will be limited to AI chip performance not exceeding that of NVIDIA L40 GPU. As leading companies like NVIDIA, AMD, Intel, and others continuously boost the performance of their AI chips, the gap between the AI computing resources established by Chinese companies and their international counterparts will continue to widen.

Looking at it from an angle of independent research and development, with the inclusion of 1980Di and more advanced DUV lithography machines in the control list and the U.S. Department of Commerce placing Chinese IC design companies on the Entity List, short-term mass production of high-performance server AI chips in China seems unlikely.

Faced with challenges in both outsourcing and in-house production, the primary path for Chinese domestic companies to develop AI technology and applications is to obtain high-performance AI computing resources from international cloud service providers (CSP). It is worth noting that the U.S. government is also exploring limitations on Chinese firms attempting to evade semiconductor control policies through CSP. For Chinese companies, establishing robust customer relationships and building extensive AI computing resources are pressing priorities before related policies are enacted.
(Image: Pixabay)

The US Department of Commerce issued new restrictions on AI chips on October 17, 2023, with a focus on controlling the export of chips to China, including NIVIDA’s A800, H800, L40S, and RTX4090, among others. Taiwanese manufacturers primarily serve cloud service providers and brand owners in North America, with relatively fewer shipments to Chinese servers. However, Chinese manufacturers, having already faced two chip restrictions imposed by the US, recognize the significance of AI chips in server applications and are expected to accelerate their in-house chip development processes.

TrendForce’s Insights:

1. Limited Impact on Taiwanese Manufacturers in Shipping AI Servers with H100 GPUs

Major Taiwanese server manufacturering companies, including Foxconn, Quanta, Inventec, GIGABYTE, and Wiwynn, provide AI servers equipped with H100 GPUs to cloud data centers and brand owners in Europe and the United States. These Taiwanese companies have established some AI server factories outside China, in countries such as the US, the Czech Republic, Mexico, Malaysia, and Thailand, focusing on producing L10 server units and L11 cabinets in proximity to end-users. This strategy aligns with the strategic needs of US cloud providers and brand owners for global server product deployment.

On the other hand, including MiTAC, Wistron, and Inventec, also provide server assembly services for Chinese brands such as Inspur and Lenovo. Although MiTAC has a significant share in assembling Inspur’s servers, it acquired Intel DSG (Data Center Solutions Group) business in July 2023. Therefore, the focus of AI servers remains on brand manufacturers using H100 GPUs, including Twitter, Dell, AWS, and European cloud service provider OVH. It is speculated that the production ratio of brand servers will be adjusted before the new restrictions are enforced.

Wistron is a major supplier for NVIDIA’s AI server modules, DGX A100, and HGX H100. Its primary shipments are to end-users in Europe and the United States. It is expected that there will be adjustments in the proportion of shipments to Chinese servers following the implementation of the restrictions.

Compal has fewer AI server orders compared to other Taiwanese manufacturers. It has not yet manifested any noticeable changes in Lenovo server assembly proportions. The full extent of the impact will only become more apparent after the enforcement of the ban.

During the transitional period before the implementation of the chip ban in the United States, the server supply chain can still adapt shipments based on local chip demand in China to address market impacts resulting from subsequent chip controls.

2. Chinese Manufacturers Focusing on Accelerating In-House Chip Development

Chinese cloud companies had already started developing their AI chips before the first U.S. chip restrictions in 2022. This included self-developed AI chips like Alibaba Cloud’s T-HEAD, a data center AI chip, and they expanded investments in areas such as DRAM, AI chips, and semiconductors with the aim of establishing a comprehensive IoT system from chips to the cloud.

Baidu Cloud, on the other hand, accelerated the development of its third-generation self-developed Kunlun chip, designed for cloud and edge computing, with plans for an early 2024 release.

Tencent introduced three self-developed chips in 2021, including an AI inference chip called Zixiao, used for Tencent’s meeting business; a video transcoding chip called Canghai, used in cloud gaming and live streaming applications; and a smart network card chip named Xuanling, applied in network storage and computing.

ByteDance made investments in cloud AI chips through its MooreThread initiative in 2022 for applications in AI servers. Huawei released the Ascend 900 chip in 2019 and is expected to introduce the Ascend 930B AI chip in the latter half of 2024. While this chip has the same computational power as the NVIDIA A100 chip, its performance still requires product validation, and it is speculated that it may not replace the current use of NVIDIA GPUs in Chinese AI servers.

Despite the acceleration of self-developed chip development among Chinese cloud server manufacturers, the high technological threshold, lengthy development cycles, and high costs associated with GPU development often delay the introduction of new server products. Therefore, Chinese cloud companies and brand manufacturers continue to purchase NVIDIA GPUs for the production of mid to high-end servers to align with their economic scale and production efficiency.

In response to the new U.S. restrictions, Chinese cloud companies have adopted short-term measures such as increasing imports of existing NVIDIA chips and building up stockpiles before the enforcement of the new restrictions. They are also focusing on medium to long-term strategies, including accelerating resource integration and shortening development timelines to expedite GPU chip manufacturing processes, thus reducing dependency on U.S. restrictions.

Nvidia has announced that the White House’s embargo on exporting advanced artificial intelligence (AI) chips to China will take effect earlier than anticipated, with no expected significant impact on the company’s short-term earnings.

On October 24th, Nvidia issued an announcement through the U.S. Securities and Exchange Commission (SEC), stating that the U.S. government had notified that the temporary final rule of October 18, titled “Implementation of Additional Export Controls: Certain Advanced Computing Items; Supercomputer and Semiconductor End Use; Updates and Corrections,” would be immediately enforced. This rule is applicable to products related to data centers with a “total processing performance” of 4800 or higher. Nvidia’s affected products include A100, A800, H100, H800, and L40S.

Nvidia clarified that the originally scheduled implementation of the authorization provisions would have occurred 30 days after the regulations were issued on October 17. Given the strong global demand for Nvidia products, the early enforcement of the U.S. government’s authorization provisions is not expected to significantly affect its financial reports in the near future.

According to Reuters, Advanced Micro Devices (AMD), which is also impacted by the White House’s export ban, did not respond to media inquiries, and the U.S. Department of Commerce declined to comment.

Bernstein analyst Stacy Rasgon had previously noted that AMD’s current AI chip “MI250” on the market may also face constraints due to the latest restrictions, and the forthcoming “MI300” could encounter challenges.

Intel, which began selling the “Gaudi 2” chip in China in July 2023, stated that the company is “reviewing the regulations and assessing the potential impacts.” Intel had previously developed a specialized version of Gaudi 2 to comply with the advanced chip export ban imposed by the Washington authorities in 2022.
(Image: Nvidia)

As Jiwei reported, AMD, although trailing NVIDIA in AI, has recently clinched significant deals, earning the trust of two major clients, Oracle and IBM. Oracle plans to integrate AMD’s Instinct MI300X AI chips into their cloud services, complemented by HPC GPUs. Additionally, as per insights from Ming-Chi Kuo, TF International Securities analyst, IBM is set to leverage AMD’s Xilinx FPGA solutions to handle artificial intelligence workloads.

Oracle’s extensive cloud computing infrastructure faces challenges due to a shortage of NVIDIA GPUs. Nonetheless, Oracle maintains an optimistic outlook. They aim to expand the deployment of the H100 chip by 2024 while considering AMD’s Instinct MI300X as a viable alternative. Oracle has decided to postpone the application of their in-house chips, a project with a multi-year timeline. Instead, they are shifting their focus to AMD’s high-performance AI chip, the MI300X, well-regarded for its impressive capabilities.

Reports indicate that Oracle intends to introduce these processor chips into their infrastructure in early 2024.

Similarly, IBM is exploring chip options beyond NVIDIA. Their new AI inference platform relies on NeuReality’s NR1 chip, manufactured on TSMC’s 7nm process. AMD plays a pivotal role in NeuReality’s AI solution by providing the essential FPGA chips. Foxconn is gearing up for AI server production using this technology in the Q4 2023.

Guo also pointed out that, although Nvidia remains the dominant AI chip manufacturer in 2024, AMD strengthens partnerships with platform service providers/CSPs like Microsoft and Amazon while acquiring companies like Nod.ai. This positions AMD to potentially narrow the AI gap with Nvidia starting in 2025. This collaboration also affirms that AMD remains unaffected by the updated U.S. ban on shipping AI chips to China.

(Image: AMD)

The United States has elevated its efforts to curtail the advancement of high-end chips in China. As reported by the CLS News, various companies within China have indicated they received advance notifications and have already amassed chip stockpiles. Analysts suggest that this new wave of bans implies a further restriction by the U.S. on China’s computational capabilities, making the development of domestically-manufactured GPUs in China a matter of utmost importance.

According to the latest regulations, chips, including Nvidia’s A800 and H800, will be impacted by the export ban to China. An insider from a Chinese server company revealed they received the ban notice at the beginning of October and have already stockpiled a sufficient quantity. Nevertheless, they anticipate substantial pressure in the near future. The procurement manager for a downstream customer of Inspur noted that they had proactively shared this information and urged potential buyers to act promptly if they require related products.

Larger companies like Tencent and Baidu are less affected by the ban due to their ample stockpiles. On October 17th, HiRain Technologies announced that its subsidiary had purchased 75 units of H800 and 22 units of A800 from supplier A and had resolved this issue two weeks ago.

(Image: NVIDIA)