In late March, NVIDIA CEO Jensen Huang personally delivered the first high-end DGX H200 AI server to customer OpenAI. According to a report from Commercial Times, following this, the upstream chips for the H200 AI-GPU entered mass production in late Q2, with large-scale deliveries expected from Q3 onwards.

Downstream companies, including Inventec, Quanta (QCT), Hewlett Packard Enterprise (HPE), Supermicro, and Lenovo, have reportedly listed the H200 products as ready for shipment, with deliveries anticipated to begin in the second half of the year.

The same report, citing sources, indicates that current pending orders are still largely focused on the H100 in the HGX architecture, with the H200’s share remaining limited. The H200 shipments expected in Q3 will primarily be NVIDIA’s DGX H200. As for the B100, there is already some visibility, with shipments expected in the first half of next year.

Despite the CoWoS production capacity catching up and a significant easing in the supply of AI GPUs, due to the allocation system, the delivery time for the main H100 GPU shipments from various end-system partners can still reach up to 20 weeks.

However, major Taiwanese manufacturers such as Quanta, Inventec, Wistron, Gigabyte, and ASUS have seen a substantial boost in their overall server operations, driven by AI server business in the first half of the year. They are reportedly optimistic about AI server shipments in the second half of the year, expecting strong demand to continue, making the server business effectively free from any off-season throughout the year.

Among them, Wistron holds a significant advantage in the production and supply of H100 series substrates and the subsequent B100 series GPU modules and substrates. Starting from the second quarter, Wistron’s AI server-related business has shown high visibility, providing strong support for its overall operations.

On the other hand, the H20 series, an AI chip tailored for China due to U.S. chip restrictions, has also seen demand in the Chinese market. As NVIDIA recently secured a rush order for the H20 series, Taiwanese companies, including Wistron and Inventec, are expected to benefit.

Read more

• [News] Taiwanese AI Server Supply Chain to Benefit from Apple’s Potential Collaboration with Baidu and Alibaba
• [News] Rumored Sharp Drop in H100 Server Black Market Prices in China Raises Concerns Over Market Stability

(Photo credit: NVIDIA)

Charles Liang, President and CEO of AI server giant Supermicro, delivered a keynote speech at COMPUTEX earlier today. According to a report from CNA, while expressing his optimism in expanding the company’s market share in the Direct Liquid Cooling (DLC) field, Liang targets to capture a 15% market share in the new data center market by next year.

According to the report, Liang mentioned that Supermicro’s DLC solutions had a market share of less than 1% over the past 30 years. However, as DLC solutions now have a cost comparable to air-cooled solutions, yet more energy-efficient, more manufacturers are beginning to adopt them. It is estimated that Supermicro has around 1000 liquid-cooled cabinets shipped each month, and the aim is to capture 15% of the new data center market share within next year.

Supermicro offers comprehensive solutions at both the cabinet and data center levels. Its operations have expanded globally from the headquarter in San Jose, California, to manufacturing and operation centers in Asia and Europe. Liang stated that Supermicro’s Malaysian plant is expected to be operational in the fourth quarter of this year, with a monthly production capacity of up to 5000 cabinets, according to CNA’s report today.

Regarding Supermicro’s expansion plans, Liang said earlier that Supermicro, with over 4000 employees worldwide, its top priority would be expanding in Taiwan, aiming to finalize plans for a new campus in the near future.

In addition, Liang pointed out that AI is rapidly and significantly changing the world. Through its collaboration with GPU giant NVIDIA, Supermicro has become one of the leading suppliers of AI systems. He also emphasized that by adopting more energy-efficient systems, green computing can be cost-free and offer significant bonuses, according to the report.

While reiterating Supermicro’s strong bond with NVIDIA, Liang invited NVIDIA CEO Jensen Huang to join him on stage. When Liang introduced the liquid-cooled server cabinets on stage, Huang praised the liquid cooling solution for significantly reducing data center costs.

Read more

• [COMPUTEX 2024] The Rise of Generative AI Sparks Innovation across Industries, with Taiwan-based Companies Leading as Essential Partners in the Global Supply Chain

(Photo credit: Supermicro)

According to a Reuters, despite the U.S. expanding export controls on advanced artificial intelligence (AI) chips to China last year, Chinese universities and research institutions have recently acquired high-end AI chips from Nvidia through distributors.

Reviewing hundreds of bidding documents, Reuters found that since the U.S. expanded chip export controls on November 17 last year, ten Chinese entities have acquired Nvidia’s advanced chips embedded in server products produced by U.S. firms Supermicro, Dell, and Taiwanese company Gigabyte Technology.

Based on this Reuters report, bidding documents not reported from November 20 last year to February 28 this year show that Chinese institutions such as the Chinese Academy of Sciences, Shandong Artificial Intelligence Institute, Hubei Earthquake Administration, Shandong University, Southwest University, a technology investment company owned by the Heilongjiang Provincial Government, a state-owned aerospace research center, and a space science center have purchased these server products from distributors, which include some of Nvidia’s most advanced chips.

In response, a Nvidia spokesperson told Reuters that the products involved in these bids were exported before the ban was implemented in the United States. The spokesperson stated that the report does not imply that Nvidia or any of its partners violated export control regulations, and the proportion of these products in global sales is negligible. Nvidia complies with U.S. regulatory standards.

Both Supermicro and Dell stated that they would investigate and take action if any third-party illegal exports or re-exports are found. Gigabyte, the Taiwanese company mentioned in the report, told the Central News Agency that it has fully complied with relevant regulations since the chip ban took effect on November 17 last year, and has not shipped any restricted products to China. Gigabyte reiterated its strict adherence to relevant Taiwanese laws and international embargo regulations, stating that there has been no violation of any embargo regulations.

In 2023, the United States further restricted Chinese businesses from acquiring high-end AI chips. At that time, Nvidia responded by launching a China-specific version, the H20. TrendForce also presented relevant data for the Chinese market, indicating that Chinese CSP companies, including ByteDance, Baidu, Alibaba, and Tencent (BBAT), accounted for approximately 6.3% of high-end AI server shipments in 2023. Considering the ban and subsequent risks, it is estimated that the proportion in 2024 may be less than 4%.

(Photo credit: NVIDIA)

NVIDIA’s latest financial report for FY2Q24 reveals that its data center business reached US$10.32 billion—a QoQ growth of 141% and YoY increase of 171%. The company remains optimistic about its future growth. TrendForce believes that the primary driver behind NVIDIA’s robust revenue growth stems from its data center’s AI server-related solutions. Key products include AI-accelerated GPUs and AI server HGX reference architecture, which serve as the foundational AI infrastructure for large data centers.

TrendForce further anticipates that NVIDIA will integrate its software and hardware resources. Utilizing a refined approach, NVIDIA will align its high-end, mid-tier, and entry-level GPU AI accelerator chips with various ODMs and OEMs, establishing a collaborative system certification model. Beyond accelerating the deployment of CSP cloud AI server infrastructures, NVIDIA is also partnering with entities like VMware on solutions including the Private AI Foundation. This strategy extends NVIDIA’s reach into the edge enterprise AI server market, underpinning steady growth in its data center business for the next two years.

NVIDIA’s data center business surpasses 76% market share due to strong demand for cloud AI

In recent years, NVIDIA has been actively expanding its data center business. In FY4Q22, data center revenue accounted for approximately 42.7%, trailing its gaming segment by about 2 percentage points. However, by FY1Q23, data center business surpassed gaming—accounting for over 45% of revenue. Starting in 2023, with major CSPs heavily investing in ChatBOTS and various AI services for public cloud infrastructures, NVIDIA reaped significant benefits. By FY2Q24, data center revenue share skyrocketed to over 76%.

NVIDIA targets both Cloud and Edge Data Center AI markets

TrendForce observes and forecasts a shift in NVIDIA’s approach to high-end GPU products in 2H23. While the company has primarily focused on top-tier AI servers equipped with the A100 and H100, given positive market demand, NVIDIA is likely to prioritize the higher-priced H100 to effectively boost its data-center-related revenue growth.

NVIDIA is currently emphasizing the L40s as their flagship product for mid-tier GPUs, meaning several strategic implications: Firstly, the high-end H100 series is constrained by the limited production capacity of current CoWoS and HBM technologies. In contrast, the L40s primarily utilizes GDDR memory. Without the need for CoWos packaging, it can be rapidly introduced to the mid-tier AI server market, filling the gap left by the A100 PCle interface in meeting the needs of enterprise customers.

Secondly, the L40s also target enterprise customers who don’t require large parameter models like ChatGPT. Instead, it focuses on more compact AI training applications in various specialized fields, with parameter counts ranging from tens of billions to under a hundred billion. They can also address edge AI inference or image analysis tasks. Additionally, in light of potential geopolitical issues that might disrupt the supply of the high-end GPU H series for Chinese customers, the L40s can serve as an alternative. As for lower-tier GPUs, NVIDIA highlights the L4 or T4 series, which are designed for real-time AI inference or image analysis in edge AI servers. These GPUs underscore affordability while maintaining a high-cost-performance ratio.

HGX and MGX AI server reference architectures are set to be NVIDIA’s main weapons for AI solutions in 2H23

TrendForce notes that recently, NVIDIA has not only refined its product positioning for its core AI chip GPU but has also actively promoted its HGX and MGX solutions. Although this approach isn’t new in the server industry, NVIDIA has the opportunity to solidify its leading position with this strategy. The key is NVIDIA’s absolute leadership stemming from its extensive integration of its GPU and CUDA platform—establishing a comprehensive AI ecosystem. As a result, NVIDIA has considerable negotiating power with existing server supply chains. Consequently, ODMs like Inventec, Quanta, FII, Wistron, and Wiwynn, as well as brands such as Dell, Supermicro, and Gigabyte, are encouraged to follow NVIDIA’s HGX or MGX reference designs. However, they must undergo NVIDIA’s hardware and software certification process for these AI server reference architectures. Leveraging this, NVIDIA can bundle and offer integrated solutions like its Arm CPU Grace, NPU, and AI Cloud Foundation.

It’s worth noting that for ODMs or OEMs, given that NVIDIA is expected to make significant achievements in the AI server market for CSPs from 2023 to 2024, there will likely be a boost in overall shipment volume and revenue growth of AI servers. However, with NVIDIA’s strategic introduction of standardized AI server architectures like HGX or MGX, the core product architecture for AI servers among ODMs and others will become more homogenized. This will intensify the competition among them as they vie for orders from CSPs. Furthermore, it’s been observed that large CSPs such as Google and AWS are leaning toward adopting in-house ASIC AI accelerator chips in the future, meaning there’s a potential threat to a portion of NVIDIA’s GPU market. This is likely one of the reasons NVIDIA continues to roll out GPUs with varied positioning and comprehensive solutions. They aim to further expand their AI business aggressively to Tier-2 data centers (like CoreWeave) and edge enterprise clients.

NVIDIA’s robust financial report reveals the true impact of AI on the technology industry, particularly in the AI server supply chain. …