According to a report by Taiwan’s Commercial Times, NVIDIA is facing repercussions from the US chip restriction, leading to controls on the export of high-end AI GPU chips to certain countries in the Middle East. Although NVIDIA claims that these controls won’t have an immediate impact on its performance, and industry insiders in the Taiwanese supply chain believe the initial effects are minimal. However, looking at the past practice of prohibiting exports to China, this could potentially trigger another wave of preemptive stockpiling.

Industry sources from the supply chain note that following the US restrictions on exporting chips to China last year, the purchasing power of Chinese clients increased rather than decreased, resulting in a surge in demand for secondary-level and below chip products, setting off a wave of stockpiling.

Take NVIDIA’s previous generation A100 chip for instance. After the US implemented export restrictions on China, NVIDIA replaced it with the lower-tier A800 chip, which quickly became a sought-after product in the Chinese market, driving prices to surge. It’s reported that the A800 has seen a cumulative price increase of 60% from the start of the year to late August, and it remains one of the primary products ordered by major Chinese CSPs.

Furthermore, the recently launched L40S GPU server by NVIDIA in August has become a market focal point. While it may not match the performance of systems like HGX H100/A100 in large-scale AI algorithm training, it outperforms the A100 in AI inference or small-scale AI algorithm training. As the L40S GPU is positioned in the mid-to-low range, it is currently not included in the list of chips subject to export controls to China.

Supply chain insiders suggest that even if the control measures on exporting AI chips to the Middle East are further enforced, local clients are likely to turn to alternatives like the A800 and  L40S. However, with uncertainty about whether the US will extend the scope of controlled chip categories, this could potentially trigger another wave of purchasing and stockpiling.

The primary direct beneficiaries in this scenario are still the chip manufacturers. Within the Taiwanese supply chain, Wistron, which supplies chip brands in the AI server front-end GPU board sector, stands to gain. Taiwanese supply chain companies producing A800 series AI servers and the upcoming L40S GPU servers, such as Quanta, Inventec, Gigabyte, and ASUS, have the opportunity to benefit as well.

(Photo credit: NVIDIA)

According to the news from Liberty Times Net, NVIDIA’s Q2 financials and Q3 forecasts have astounded the market, driven by substantial growth in their AI-centric data center operations. NVIDIA addresses CoWoS packaging supply issues by collaborating with other suppliers, boosting future capacity, and meeting demand. This move is echoed in South Korea’s pursuit of advanced packaging strategies.

South Korea’s Swift Pursuit on Advanced Packaging

The semiconductor industry highlights that the rapid development of generative AI has outpaced expectations, causing a shortage of advanced packaging production capacity. Faced with this supply-demand gap, TSMC has outsourced some of its capacity, with Silicon Interposer production being shared by facilities under the United Microelectronics Corporation and Siliconware Precision Industries. UMC has also strategically partnered with Siliconware Precision Industries, and Amkor’s Korean facilities have joined the ranks of suppliers to augment production capacity.

Due to equipment limitations, TSMC’s monthly CoWoS advanced packaging capacity is expected to increase from 10,000 units to a maximum of 12,000 units by the end of this year. Meanwhile, other suppliers could potentially raise their CoWoS monthly capacity to 3,000 units. TSMC aims to boost its capacity to 25,000 units by the end of next year, while other suppliers might elevate theirs to 5,000 units.

According to the source South Korean media, Samsung entered the scene, competing for advanced packaging orders against NVIDIA. South Korea initiated a strategic research project to rapidly narrow the gap in packaging technology within 5~7 years, targeting giants like TSMC, Amkor, and China’s JCET.

(Source: https://ec.ltn.com.tw/article/paper/1601162)

Dell, a major server brand, placed a substantial order for AI servers just before NVIDIA’s Q2 financial report. This move is reshaping Taiwan’s supply chain dynamics, favoring companies like Wistron and Lite-On.

Dell is aggressively entering the AI server market, ordering NVIDIA’s top-tier H100 chips and components. The order’s value this year is estimated in hundreds of billions of Taiwanese dollars, projected to double in the next year. Wistron and Lite-On are poised to benefit, securing vital assembly and power supply orders. EMC and Chenbro are also joining the supply chain.

Dell’s AI server order, which includes assembly (including complete machines, motherboards, GPU boards, etc.) and power supply components, stands out with its staggering value. The competition was most intense in the assembly sector, ultimately won by Wistron. In the power supply domain, industry leaders like Delta, Lite-On, secured a notable share, with Lite-On emerging as a winner, sparking significant industry discussions.

According to Dell’s supply chain data, AI server inventory will reach 20,000 units this year and increase next year. The inventory primarily features the highest-end H100 chips from NVIDIA, with a few units integrating the A100 chips. With each H100 unit priced at $300,000 and A100 units exceeding $100,000, even with a seemingly modest 20,000 units, the total value remains in the billions of New Taiwan Dollars.

Wistron is a standout winner in Dell’s AI server assembly order, including complete machines, motherboards, and GPU boards. Wistron has existing H100 server orders and will supply new B100 baseboard orders. Their AI server baseboard plant in Hsinchu, Taiwan will expand by Q3 this year. Wistron anticipates year-round growth in the AI server business.

Following Saudi Arabia’s $13 billion investment, the UK government is dedicating £100 million (about $130 million) to acquire thousands of NVIDIA AI chips, aiming to establish a strong global AI foothold. Potential beneficiaries include Wistron, GIGABYTE, Asia Vital Components, and Supermicro.

Projections foresee a $150 billion AI application opportunity within 3-5 years, propelling the semiconductor market to $1 trillion by 2030. Taiwan covers the full industry value chain. Players like TSMC, Alchip, GUC, Auras, Asia Vital Components, SUNON, EMC, Unimicron, Delta, and Lite-On are poised to gain.

Reports suggest the UK is in advanced talks with NVIDIA for up to 5,000 GPU chips, but models remain undisclosed. The UK government recently engaged with chip giants NVIDIA, Supermicro, Intel, and others through the UK Research and Innovation (UKRI) to swiftly acquire necessary resources for Prime Minister Sunak’s AI development initiative. Critics question the adequacy of the £100 million investment in NVIDIA chips, urging Chancellor Jeremy Hunt to allocate more funds to support the AI project.

NVIDIA’s high-performance GPU chips have gained widespread use in AI fields. Notably, the AI chatbot ChatGPT relies heavily on NVIDIA chips to meet substantial computational demands. The latest iteration of AI language model, GPT-4, requires a whopping 25,000 NVIDIA chips for training. Consequently, experts contend that the quantity of chips procured by the UK government is notably insufficient.

Of the UK’s £1 billion investment in supercomputing and AI, £900 million is for traditional supercomputers, leaving £50 million for AI chip procurement. The budget recently increased from £70 million to £100 million due to global chip demand.

Saudi Arabia and the UAE also ordered thousands of NVIDIA AI chips, and Saudi Arabia’s order includes at least 3,000 of the latest H100 chips. Prime Minister Sunak’s AI initiative begins next summer, aiming for a UK AI chatbot like ChatGPT and AI tools for healthcare and public services.

As emerging AI applications proliferate, countries are actively competing in the race to bolster AI data centers, turning the acquisition of AI-related chips into an alternative arms race. Compal said, “An anticipate significant growth in the AI server sector in 2024, primarily within hyperscale data centers, with a focus on European expansion in the first half of the year and a shift toward the US market in the latter half.”

According to a report by Taiwan’s Commercial Times, JPMorgan’s latest analysis reveals that AI demand will remain robust in the second half of the year. Encouragingly, TSMC’s CoWoS capacity expansion progress is set to exceed expectations, with production capacity projected to reach 28,000 to 30,000 wafers per month by the end of next year.

The trajectory of CoWoS capacity expansion is anticipated to accelerate notably in the latter half of 2024. This trend isn’t limited to TSMC alone; other players outside the TSMC are also actively expanding their CoWoS-like production capabilities to meet the soaring demands of AI applications.

Gokul Hariharan, Head of Research for JPMorgan Taiwan, highlighted that industry surveys indicate strong and unabated AI demand in the latter half of the year. Shortages amounting to 20% to 30% are observed with CoWoS capacity being a key bottleneck and high-bandwidth memory (HBM) also facing supply shortages.

JPMorgan’s estimates indicate that Nvidia will account for 60% of the overall CoWoS demand in 2023. TSMC is expected to produce around 1.8 to 1.9 million sets of H100 chips, followed by significant demand from Broadcom, AWS’ Inferentia chips, and Xilinx. Looking ahead to 2024, TSMC’s continuous capacity expansion is projected to supply Nvidia with approximately 4.1 to 4.2 million sets of H100 chips.

Apart from TSMC’s proactive expansion of CoWoS capacity, Hariharan predicts that other assembly and test facilities are also accelerating their expansion of CoWoS-like capacities.

For instance, UMC is preparing to have a monthly capacity of 5,000 to 6,000 wafers for the interposer layer by the latter half of 2024. Amkor is expected to provide a certain capacity for chip-on-wafer stacking technology, and ASE Group will offer chip-on-substrate bonding capacity. However, these additional capacities might face challenges in ramping up production for the latest products like H100, potentially focusing more on older-generation products like A100 and A800.

(Photo credit: TSMC)