Insights
According to a report by Taiwan’s Economic Daily, Google has notified Chromebook manufacturers to start collecting licensing fees from July 1st, prompting laptop brands to accelerate shipments ahead of schedule. As a result of this “urgent order,” Taiwan’s contract manufacturers achieved better-than-expected results in Q2.
In a press release dated July 3rd, TrendForce noted that Google’s formal imposition of Chromebook licensing fees is bound to affect the competitiveness of Chromebooks in the entry-level market. However, laptop brands, in order to avoid incurring additional costs due to licensing fees, are actively advancing Chromebook shipments regardless of having a clear grasp of end-demand orders. This enthusiasm has driven overall Chromebook shipment performance in the second quarter.
TrendForce mentioned that after a seven-quarter adjustment period, education tender orders from North America, Indonesia, and India have begun to emerge for Chromebooks. Additionally, with assistance from the United Nations Children’s Fund, Ukraine’s educational reconstruction needs have also gradually emerged. Nevertheless, due to the off-peak season for Chromebooks in the latter half of the year and the impact of licensing fees, demand is expected to remain subdued compared to the first half.
Furthermore, according to TrendForce’s insights, following Google’s formal initiation of licensing fees, the ODM production costs for consumer-grade Chromebooks have risen by $6 to $8, while business-grade laptops have experienced an increase of $7 to $12. However, considering the stagnation in end-demand this year, brand manufacturers have yet to make any adjustments to end-user pricing.
(Photo credit: Google)
Insights
Charlie Boyle, Vice President of NVIDIA’s DGX Systems, recently addressed the issue of limited GPU production at the company.
Boyle clarified that the current GPU shortage is not a result of NVIDIA misjudging demand or constraints in Taiwan Semiconductor Manufacturing Company’s (TSMC) wafer production. The primary bottleneck for GPUs lies in the packaging process.
It’s worth noting that the NVIDIA A100 and H100 GPUs are currently manufactured by TSMC using their advanced CoWoS (Chip-on-Wafer-on-Substrate) packaging technology. TSMC has indicated that it may take up to a year and a half, including the completion of additional wafer fabs and expansion of existing facilities, to normalize the backlog of packaging orders.
Furthermore, due to the significant strain on TSMC’s CoWoS capacity, there have been reports of overflow of NVIDIA GPU packaging orders to other manufacturers.
Sources familiar with the matter have revealed that NVIDIA is in discussions with potential alternative suppliers, including Samsung, as secondary suppliers for the 2.5D packaging of NVIDIA’s A100 and H100 GPUs. Other potential suppliers include Amkor and the Siliconware Precision Industries Co., Ltd. (SPIL), a subsidiary of ASE Technology Holding.
In December 2022, Samsung established its Advanced Packaging (AVP) division to seize opportunities in high-end packaging and testing. Sources suggest that if NVIDIA approves of Samsung’s 2.5D packaging process yield, a portion of AI GPU packaging orders may be placed with Samsung.
TrendForce’s research in June this year indicated that driven by strong demand for high-end AI chips and High-Bandwidth Memory (HBM), TSMC’s CoWoS monthly capacity could reach 12,000 units by the end of 2023. Particularly, demand from NVIDIA for A100 and H100 GPUs in AI servers has led to nearly a 50% increase in CoWoS capacity compared to the beginning of the year. Coupled with the growth in demand for high-end AI chips from companies like AMD and Google, the second half of the year is expected to witness tighter CoWoS capacity. This robust demand is projected to continue into 2024, with advanced packaging capacity potentially growing by 30-40% if the necessary equipment is in place.
(Photo credit: NVIDIA)
News
According to the news from Commercial Times, in a recent press conference, the four major American cloud service providers (CSPs) collectively expressed their intention to expand their investment in AI application services. Simultaneously, they are continuing to enhance their cloud infrastructure. Apple has also initiated its foray into AI development, and both Intel and AMD have emphasized the robust demand for AI servers. These developments are expected to provide a significant boost to the post-market prospects of Taiwan’s AI server supply chain.
Industry insiders have highlighted the ongoing growth of the AI spillover effect, benefiting various sectors ranging from GPU modules, substrates, cooling systems, power supplies, chassis, and rails, to PCB manufacturers.
The American CSP players, including Microsoft, Google, Meta, and Amazon, which recently released their financial reports, have demonstrated growth in their cloud computing and AI-related service segments in their latest quarterly performance reports. Microsoft, Google, and Amazon are particularly competitive in the cloud services arena, and all have expressed optimistic outlooks for future operations.
The direct beneficiaries among Taiwan’s cloud data center suppliers are those in Tier 1, who are poised to reap positive effects on their average selling prices (ASP) and gross margins, driven by the strong demand for AI servers from these CSP giants in the latter half of the year.
Among them, the ODM manufacturers with over six years of collaboration with NVIDIA in multi-GPU architecture AI high-performance computing/cloud computing, including Quanta, Wistron, Wistron, Inventec, Foxconn, and Gigabyte, are expected to see operational benefits further reflected in the latter half of the year. Foxconn and Inventec are the main suppliers of GPU modules and GPU substrates, respectively, and are likely to witness noticeable shipment growth starting in the third quarter.
Furthermore, AI servers not only incorporate multiple GPU modules but also exhibit improvements in aspects such as chassis height, weight, and thermal design power (TDP) compared to standard servers. As a result, cooling solution providers like Asia Vital Components, Auras Technology, and SUNON; power supply companies such as Delta Electronics and Lite-On Technology; chassis manufacturers Chenbro; rail industry players like King Slide, and PCB/CCL manufacturers such as EMC, GCE are also poised to benefit from the increasing demand for AI servers.
In-Depth Analyses
OpenAI’s ChapGPT, Microsoft’s Copilot, Google’s Bard, and latest Elon Musk’s TruthGPT – what will be the next buzzword for AI? In just under six months, the AI competition has heated up, stirring up ripples in the once-calm AI server market, as AI-generated content (AIGC) models take center stage.
The convenience unprecedentedly brought by AIGC has attracted a massive number of users, with OpenAI’s mainstream model, GPT-3, receiving up to 25 million daily visits, often resulting in server overload and disconnection issues.
Given the evolution of these models has led to an increase in training parameters and data volume, making computational power even more scarce, OpenAI has reluctantly adopted measures such as paid access and traffic restriction to stabilize the server load.
High-end Cloud Computing is gaining momentum
According to Trendforce, AI servers currently have a merely 1% penetration rate in global data centers, which is far from sufficient to cope with the surge in data demand from the usage side. Therefore, besides optimizing software to reduce computational load, increasing the number of high-end AI servers in hardware will be another crucial solution.
Take GPT-3 for instance. The model requires at least 4,750 AI servers with 8 GPUs for each, and every similarly large language model like ChatGPT will need 3,125 to 5,000 units. Considering ChapGPT and Microsoft’s other applications as a whole, the need for AI servers is estimated to reach some 25,000 units in order to meet the basic computing power.
As the emerging applications of AIGC and its vast commercial potential have both revealed the technical roadmap moving forward, it also shed light on the bottlenecks in the supply chain.
The down-to-earth problem: cost
Compared to general-purpose servers that use CPUs as their main computational power, AI servers heavily rely on GPUs, and DGX A100 and H100, with computational performance up to 5 PetaFLOPS, serve as primary AI server computing power. Given that GPU costs account for over 70% of server costs, the increase in the adoption of high-end GPUs has made the architecture more expansive.
Moreover, a significant amount of data transmission occurs during the operation, which drives up the demand for DDR5 and High Bandwidth Memory (HBM). The high power consumption generated during operation also promotes the upgrade of components such as PCBs and cooling systems, which further raises the overall cost.
Not to mention the technical hurdles posed by the complex design architecture – for example, a new approach for heterogeneous computing architecture is urgently required to enhance the overall computing efficiency.
The high cost and complexity of AI servers has inevitably limited their development to only large manufacturers. Two leading companies, HPE and Dell, have taken different strategies to enter the market:
With the booming market for AIGC applications, we seem to be one step closer to a future metaverse centered around fully virtualized content. However, it remains unclear whether the hardware infrastructure can keep up with the surge in demand. This persistent challenge will continue to test the capabilities of cloud server manufacturers to balance cost and performance.
(Photo credit: Google)
Insights
Smart watch shipments reached 107 million units in 2021, surpassing the shipments of smart bands for the first time. Smart bands declined in 2021 with only 70.33 million units delivered. As branded manufacturers strengthen their investment in the smart watch market, market growth has accelerated. Due to the proximity of functional applications, the smart band market has been gradually supplanted by low-cost smart watch products. Therefore, driven by new products in 2022, the current forecast indicates that smart watch shipments will continue to grow in 2022, reaching 119 million units, for an annual growth rate of 11.4%. Smart band shipments are expected to decline to 55.18 million units and the gap between the two continues to widen. It is worth noting, although branded manufacturers are optimistic regarding the development of the smart watch market, in light of risks such as the COVID-19 pandemic, war, and inflation, continuing downward revisions of smart watch shipment volume in 2022 cannot be ruled out and annual growth rate may even fall below 5%.
The top five major manufacturers of smart watches are Apple, Samsung, Huawei, Xiaomi, and Garmin with a combined market share of 63%. Apple Watch shipments reached 36.6 million units in 2021, with an annual growth rate of 20%. Apple is optimistic regarding the market in 2022. On the one hand, the company believes that the Watch Series 8 can maintain the same consumer interest as the Watch Series 7. On the other hand, a wave of entry-level product replacements is expected with the launch of the second-generation Watch SE. Coupled with the launch of new Pro products, Apple believes that market demand in 2022 will surpass that in 2021 and shipment volume is expected to reach 43 million to 46 million units.
However, considering the negative economic impacts following the wake of the COVID-19 pandemic and inflation, 4Q22 holiday sales may not pan out as expected. Throwing in the wildcard of China’s lockdown strategy, production of new Apple Watches may be affected if lockdown measures reappear in 2H22, which will lead to a risk of further delays in shipments of new products, upsetting shipments in 2022. Therefore, shipments of Apple Watches are conservatively forecast to reach 39.1 million units in 2022.
Although Samsung began exploring the wearable device market very early, due to the small market size and the rapid growth of the smartphone market, smart watches were not the focus of Samsung’s product development at the time. This was true up until recent years. As the growth of smartphones slowed, Samsung has once again strengthened its distribution of other consumer electronics products which has led to continuous growth in Samsung Galaxy Watch shipments. In addition, since Huawei has been flattened by Sino-US trade friction, Samsung leaped to claim the number two spot in the smart watch market in 2021. Samsung smartwatch shipments are estimated to grow from 11.09 million in 2021 to 14.1 million units in 2022.
After Google officially acquired Fitbit, although Fitbit remains nominally an independent brand, internal reorganization is bound to be carried out considering this affords more efficient resource allocation, integrating the companies’ procurement, product development, etc. Google will have two smart watch brands, Fitbit and Pixel. In terms of high-end watches, the Pixel Watch is a flagship product positioned as an extension of the Pixel mobile phone and is primarily used in synergy with smart phone functionality. Therefore, the Pixel Watch uses the Samsung Exynos chip and it is expected to highlight the features of various apps in the Google Play Store. Since Fitbit was acquired by Google, it has become necessary to adjust unified strategy and integrate and reorganize resources. Although smart watch shipments resumed growth in 2021, there is some distance between leading brands. Fitbit Is expected to launch new products in 2H22. Google Pixel Watch is also expected to be launched in 2H22, so Google/Fitbit smart watch shipments are estimated to grow to 3.65 million units in 2022.
(Image credit: Pixabay)