TSMC is reportedly negotiating with NVIDIA to manufacture advanced "Blackwell" GPUs in its Arizona facility. First reported by Reuters, this partnership could mark another major shift in AI chip production toward US soil. The discussion centers around TSMC's Fab 21 in Phoenix, Arizona, specializing in 4 nm and 5 nm chip production. NVIDIA's Blackwell GPUs utilize TSMC's 4NP process technology, making the Arizona facility a technically viable production site. However, the proposed arrangement faces several logistical challenges. A key issue is the absence of advanced packaging facilities in the United States. There is Amkor that planned to do advanced packaging, but it's only scheduled to begin packaging in 2027. TSMC's sophisticated CoWoS packaging technology is currently available only in Taiwan. This means that chips manufactured in Arizona would need to be shipped back to Taiwan for final assembly, potentially increasing production costs.

While alternative solutions exist, such as redesigning the chips to use Intel's packaging technology or focusing on gaming GPU production in Arizona, these options present their own complications. Intel's packaging methods would likely increase costs, and the current absence of graphics card manufacturing infrastructure in the US makes domestic gaming GPU production less practical. Both TSMC and NVIDIA have declined to comment on the ongoing negotiations, as this is confidential information unknown to the public. Interestingly, TSMC's Arizona facility has already attracted a few more US firms for domestic manufacturing, like Apple, rumored to manufacture its A16 Bionic chip and AMD with high-performance designs, likely either EPYC or Instinct MI chips.

According to The Information, NVIDIA's latest "Blackwell" processors are reportedly encountering significant thermal management issues in high-density server configurations, potentially affecting deployment timelines for major tech companies. The challenges emerge specifically in NVL72 GB200 racks housing 72 GB200 processors, which can consume up to 120 kilowatts of power per rack, weighting a "mere" 3,000 pounds (or about 1.5 tons). These thermal concerns have prompted NVIDIA to revisit and modify its server rack designs multiple times to prevent performance degradation and potential hardware damage. Hyperscalers like Google, Meta, and Microsoft, who rely heavily on NVIDIA GPUs for training their advanced language models, have allegedly expressed concerns about possible delays in their data center deployment schedules.

The thermal management issues follow earlier setbacks related to a design flaw in the Blackwell production process. The problem stemmed from the complex CoWoS-L packaging technology, which connects dual chiplets using RDL interposer and LSI bridges. Thermal expansion mismatches between various components led to warping issues, requiring modifications to the GPU's metal layers and bump structures. A company spokesperson characterized these modifications as part of the standard development process, noting that a new photomask resolved this issue. The Information states that mass production of the revised Blackwell GPUs began in late October, with shipments expected to commence in late January. However, these timelines are unconfirmed by NVIDIA, and some server makers like Dell confirmed that these GB200 NVL72 liquid-cooled systems are shipping now, not in January, with CoreWave GPU cloud provider as a customer. The original report could be using older information, as Dell is one of NVIDIA's most significant partners and among the first in the supply chain to gain access to new GPU batches.

At TSMC's earnings call on the 17th, the company revealed that its CoWoS (Chip-on-Wafer-on-Substrate) capacity will double each year in 2024 and 2025, but demand will continue to outpace supply. According to a report from Money DJ, the CoWoS expansion wave is expected to extend into 2026, promising strong growth for equipment suppliers for at least the next two to three years.

TSMC stated that advanced packaging currently accounts for approximately 7-9% of its revenue, and growth in this segment is expected to outpace the company's average over the next five years. While the gross margin for advanced packaging is slightly below the company average, it is steadily approaching it. Regarding CoWoS capacity, customer demand significantly exceeds TSMC's ability to supply, even with production capacity doubling year-on-year in both 2024 and 2025.

TSMC announced that its revenue for September 2024 reached NT$251.87 billion (US$7.80 billion), representing a 39% increase compared to the same month last year. The cumulative revenue for the first three quarters of 2024 climbed to NT$2,025.85 billion (US$62.72 billion), showing a 32% year-over-year growth. The company's third-quarter revenue amounted to NT$759.7 billion (US$23.52 billion), exceeding TSMC's own guidance of NT$706.6 billion to NT$731.5 billion (US$22.4 billion to US$23.2 billion). TSMC will report full third-quarter earnings on Oct. 17.

A report from Data Center Dynamics quotes sources saying that, due to increasing demand from NVIDIA and others, TSMC has been forced to change its CoWoS capacity expansion plan several times. In response, TSMC is building two more fabs, named P4 and P5, in Kaohsiung, Taiwan, raising the company's total number of facilities in the region to five. Four months ago, the company announced that it would build a third 2 nm fab at Nanzih Technology Industrial Park in Kaohsiung. The company's P1 fab, which started in August 2022, is expected to begin mass production next year, while P2 and P3 are still in the construction phase. TSMC's CoWoS monthly capacity is expected to reach more than 40,000 wafers by the end of 2024, 65,000 wafers in 2025, and at least 80,000 wafers in 2026.

After Apple, we just learned that AMD is the next company in line for US-based manufacturing in the TSMC Arizona facility. Industry analyst Tim Culpan reports that TSMC's Fab 21 in Arizona will soon be producing AMD's high-performance computing (HPC) processors, with tape out and manufacturing expected to commence on TSMC's 5 nm node next year. This move comes after previously reported Apple's A16 SoC production, which is already in progress at the facility and could see shipments before the end of this year, significantly ahead of the initially projected early 2025 schedule. The production of AMD's HPC chips in Arizona marks a crucial step towards establishing an AI-hardware supply chain operating entirely on American soil, which is expected to further expand with Intel Foundry and Samsung Texas facility.

Making HPC processors domestically serves as a significant milestone in reducing dependence on overseas semiconductor manufacturing and strengthening the US's position in the global chip industry. Adding to the momentum, TSMC and Amkor recently announced a collaboration on advanced packaging technologies, including Integrated Fan-Out (InFO) and Chip-on-Wafer-on-Substrate (CoWoS), which are vital for high-performance AI chips. However, as Amkor facilities are yet to be built, these chips are going to be shipped back to Taiwan for packaging before being integrated into the final product. Once the Amkor facility is up and running, Arizona will become the birthplace of fully manufactured and packaged silicon chips.

Amkor Technology, Inc. and TSMC announced today that the two companies have signed a memorandum of understanding to collaborate and bring advanced packaging and test capabilities to Arizona, further expanding the region's semiconductor ecosystem.

Amkor and TSMC have been closely collaborating to deliver high volume, leading-edge technologies for advanced packaging and testing of semiconductors to support critical markets such as high-performance computing and communications. Under the agreement, TSMC will contract turnkey advanced packaging and test services from Amkor in their planned facility in Peoria, Arizona. TSMC will leverage these services to support its customers, particularly those using TSMC's advanced wafer fabrication facilities in Phoenix. The close collaboration and proximity of TSMC's front-end fab and Amkor's back-end facility will accelerate overall product cycle times.

Synopsys, Inc. today announced its continued, close collaboration with TSMC to deliver advanced EDA and IP solutions on TSMC's most advanced process and 3DFabric technologies to accelerate innovation for AI and multi-die designs. The relentless computational demands in AI applications require semiconductor technologies to keep pace. From an industry leading AI-driven EDA suite, powered by Synopsys.ai for enhanced productivity and silicon results to complete solutions that facilitate the migration to 2.5/3D multi-die architectures, Synopsys and TSMC have worked closely for decades to pave the path for the future of billion to trillion-transistor AI chip designs.

"TSMC is excited to collaborate with Synopsys to develop pioneering EDA and IP solutions tailored for the rigorous compute demands of AI designs on TSMC advanced process and 3DFabric technologies," said Dan Kochpatcharin, head of the Ecosystem and Alliance Management Division at TSMC. "The results of our latest collaboration across Synopsys' AI-driven EDA suite and silicon-proven IP have helped our mutual customers significantly enhance their productivity and deliver remarkable performance, power, and area results for advanced AI chip designs.

During the Semicon Taiwan 2024 summit event, TSMC VP of Advanced Packaging Technology, Jun He, spoke about the importance of merging AI chip memory and logic chips using 3D IC technology. He predicted that by 2030 the worldwide semiconductor industry would hit the $1 trillion milestone with HPC and AI leading 40 percent of the market share. In 2027, TSMC will introduce the 2.5D CoWoS technology that includes eight A16 process chipsets and 12 HBM4. AI processors that use this technology will not only be much cheaper to produce but will also provide engineers with a greater level of convenience. Engineers will have the option to write new codes into them instead. Manufacturers are cutting the SoC and HBM architectural conversion and mass production costs down to nearly one-fourth.

Nevertheless, the increasing production capacities of 3D IC technology remain the main challenge, as the size of chips and the complexity of manufacturing are decisive factors. However, the higher the size of the chips, the more chiplets are added, and thus the performance is improved, but this now makes the process even more complicated and is associated with more risks of misalignment, breakage, and extraction failure.

Despite recent rumors speculating on NVIDIA's supposed cancellation of the B100 in favor of the B200A, TrendForce reports that NVIDIA is still on track to launch both the B100 and B200 in the 2H24 as it aims to target CSP customers. Additionally, a scaled-down B200A is planned for other enterprise clients, focusing on edge AI applications.

TrendForce reports that NVIDIA will prioritize the B100 and B200 for CSP customers with higher demand due to the tight production capacity of CoWoS-L. Shipments are expected to commence after 3Q24. In light of yield and mass production challenges with CoWoS-L, NVIDIA is also planning the B200A for other enterprise clients, utilizing CoWoS-S packaging technology.

Alphawave Semi, a global leader in high-speed connectivity and compute silicon for the world's technology infrastructure, has launched the industry's first 3 nm successful silicon bring-up of Universal Chiplet Interconnect Express (UCIe) Die-to-Die (D2D) IP with TSMC's Chip-on-Wafer-on-Substrate (CoWoS) advanced packaging technology.

The complete PHY and Controller subsystem was developed in collaboration with TSMC and targets applications such as hyperscaler, high-performance computing (HPC) and artificial intelligence (AI).

Taiwanese semiconductor giant TSMC is reportedly planning to increase its wafer prices by up to 10% in 2025, according to a Morgan Stanley note cited by investor Eric Jhonsa. The move comes as demand for cutting-edge processors in smartphones, PCs, AI accelerators, and HPC continues to surge. Industry insiders reveal that TSMC's state-of-the-art 4 nm and 5 nm nodes, used for AI and HPC customers such as AMD, NVIDIA, and Intel, could see up to 10% price hikes. This increase would push the cost of 4 nm-class wafers from $18,000 to approximately $20,000, representing a significant 25% rise since early 2021 for some clients and an 11% rise from the last price hike. Talks about price hikes with major smartphone manufacturers like Apple have proven challenging, but there are indications that modest price increases are being accepted across the industry. Morgan Stanley analysts project a 4% average selling price increase for 3 nm wafers in 2025, which are currently priced at $20,000 or more per wafer.

Mature nodes like 16 nm are unlikely to see price increases due to sufficient capacity. However, TSMC is signaling potential shortages in leading-edge capacity to encourage customers to secure their allocations. Adding to the industry's challenges, advanced chip-on-wafer-on-substrate (CoWoS) packaging prices are expected to rise by 20% over the next two years, following previous increases in 2022 and 2023. TSMC aims to boost its gross margin to 53-54% by 2025, anticipating that customers will absorb these additional costs. The impact of these price hikes on end-user products remains uncertain. Competing foundries like Intel and Samsung may seize this opportunity to offer more competitive pricing, potentially prompting some chip designers to consider alternative manufacturing options. Additionally, TSMC's customers could reportedly be unable to secure their capacity allocation without "appreciating TSMC's value."

TrendForce reports that NVIDIA's Hopper H100 began to see a reduction in shortages in 1Q24. The new H200 from the same platform is expected to gradually ramp in Q2, with the Blackwell platform entering the market in Q3 and expanding to data center customers in Q4. However, this year will still primarily focus on the Hopper platform, which includes the H100 and H200 product lines. The Blackwell platform—based on how far supply chain integration has progressed—is expected to start ramping up in Q4, accounting for less than 10% of the total high-end GPU market.

The die size of Blackwell platform chips like the B100 is twice that of the H100. As Blackwell becomes mainstream in 2025, the total capacity of TSMC's CoWoS is projected to grow by 150% in 2024 and by over 70% in 2025, with NVIDIA's demand occupying nearly half of this capacity. For HBM, the NVIDIA GPU platform's evolution sees the H100 primarily using 80 GB of HBM3, while the 2025 B200 will feature 288 GB of HBM3e—a 3-4 fold increase in capacity per chip. The three major manufacturers' expansion plans indicate that HBM production volume will likely double by 2025.

During the European Technology Symposium 2024, TSMC has announced its readiness to manufacture next-generation HBM4 base dies using both 12 nm and 5 nm nodes. This significant development is expected to substantially improve the performance, power consumption, and logic density of HBM4 memory, catering to the demands of high-performance computing (HPC) and artificial intelligence (AI) applications. The shift from a traditional 1024-bit interface to an ultra-wide 2048-bit interface is a key aspect of the new HBM4 standard. This change will enable the integration of more logic and higher performance while reducing power consumption. TSMC's N12FFC+ and N5 processes will be used to produce these base dies, with the N12FFC+ process offering a cost-effective solution for achieving HBM4 performance and the N5 process providing even more logic and lower power consumption at HBM4 speeds.

The company is collaborating with major HBM memory partners, including Micron, Samsung, and SK Hynix, to integrate advanced nodes for HBM4 full-stack integration. TSMC's base die, fabricated using the N12FFC+ process, will be used to install HBM4 memory stacks on a silicon interposer alongside system-on-chips (SoCs). This setup will enable the creation of 12-Hi (48 GB) and 16-Hi (64 GB) stacks with per-stack bandwidth exceeding 2 TB/s. TSMC's collaboration with EDA partners like Cadence, Synopsys, and Ansys ensures the integrity of HBM4 channel signals, thermal accuracy, and electromagnetic interference (EMI) in the new HBM4 base dies. TSMC is also optimizing CoWoS-L and CoWoS-R for HBM4 integration, meaning that massive high-performance chips are already utilizing this technology and getting ready for volume manufacturing.

NVIDIA barely started shipping its "Blackwell" line of AI GPUs, and its next-generation architecture is already on the horizon. Codenamed "Rubin," after Vera Rubin, the new architecture will power NVIDIA's future AI GPUs with generational jumps in performance, but more importantly, a design focus on lowering the power draw. This will become especially important as NVIDIA's current architectures already approach the kilowatt range, and cannot scale boundlessly. TF International Securities analyst, Mich-Chi Kuo says that NVIDIA's first AI GPU based on "Rubin," the R100 (not to be confused with an ATI GPU from many moons ago); is expected to enter mass-production in Q4-2025, which means it could be unveiled and demonstrated sooner than that; and select customers could have access to the silicon sooner, for evaluations.

The R100, according to Mich-Chi Kuo, is expected to leverage TSMC's 3 nm EUV FinFET process, specifically the TSMC-N3 node. In comparison, the new "Blackwell" B100 uses the TSMC-N4P. This will be a chiplet GPU, and use a 4x reticle design compared to Blackwell's 3.3x reticle design, and use TSMC's CoWoS-L packaging, just like the B100. The silicon is expected to be among the first users of HBM4 stacked memory, and feature 8 stacks of a yet unknown stack height. The Grace Ruben GR200 CPU+GPU combo could feature a refreshed "Grace" CPU built on the 3 nm node, likely an optical shrink meant to reduce power. A Q4-2025 mass-production roadmap target would mean that customers will start receiving the chips by early 2026.

SK hynix showcased its next-generation technologies and strengthened key partnerships at the TSMC 2024 Technology Symposium held in Santa Clara, California on April 24. At the event, the company displayed its industry-leading HBM AI memory solutions and highlighted its collaboration with TSMC involving the host's CoWoS advanced packaging technology.

TSMC, a global semiconductor foundry, invites its major partners to this annual conference in the first half of each year so they can share their new products and technologies. Attending the event under the slogan "Memory, the Power of AI," SK hynix received significant attention for presenting the industry's most powerful AI memory solution, HBM3E. The product has recently demonstrated industry-leading performance, achieving input/output (I/O) transfer speed of up to 10 gigabits per second (Gbps) in an AI system during a performance validation evaluation.

TSMC today unveiled its newest semiconductor process, advanced packaging, and 3D IC technologies for powering the next generation of AI innovations with silicon leadership at the Company's 2024 North America Technology Symposium. TSMC debuted the TSMC A16 technology, featuring leading nanosheet transistors with innovative backside power rail solution for production in 2026, bringing greatly improved logic density and performance. TSMC also introduced its System-on-Wafer (TSMC-SoW) technology, an innovative solution to bring revolutionary performance to the wafer level in addressing the future AI requirements for hyperscaler datacenters.

This year marks the 30th anniversary of TSMC's North America Technology Symposium, and more than 2,000 attended the event, growing from less than 100 attendees 30 years ago. The North America Technology Symposium in Santa Clara, California kicks off TSMC Technology Symposiums around the world in the coming months. The symposium also features an "Innovation Zone," designed to highlight the technology achievements of our emerging start-up customers.

SK hynix Inc. announced today that it has recently signed a memorandum of understanding with TSMC for collaboration to produce next-generation HBM and enhance logic and HBM integration through advanced packaging technology. The company plans to proceed with the development of HBM4, or the sixth generation of the HBM family, slated to be mass-produced from 2026, through this initiative.

SK hynix said the collaboration between the global leader in the AI memory space and TSMC, a top global logic foundry, will lead to more innovations in HBM technology. The collaboration is also expected to enable breakthroughs in memory performance through trilateral collaboration between product design, foundry, and memory provider. The two companies will first focus on improving the performance of the base die that is mounted at the very bottom of the HBM package. HBM is made by stacking a core DRAM die on top of a base die that features TSV technology, and vertically connecting a fixed number of layers in the DRAM stack to the core die with TSV into an HBM package. The base die located at the bottom is connected to the GPU, which controls the HBM.

NVIDIA's next-gen Blackwell platform, which includes B-series GPUs and integrates NVIDIA's own Grace Arm CPU in models such as the GB200, represents a significant development. TrendForce points out that the GB200 and its predecessor, the GH200, both feature a combined CPU+GPU solution, primarily equipped with the NVIDIA Grace CPU and H200 GPU. However, the GH200 accounted for only approximately 5% of NVIDIA's high-end GPU shipments. The supply chain has high expectations for the GB200, with projections suggesting that its shipments could exceed millions of units by 2025, potentially making up nearly 40 to 50% of NVIDIA's high-end GPU market.

Although NVIDIA plans to launch products such as the GB200 and B100 in the second half of this year, upstream wafer packaging will need to adopt more complex and high-precision CoWoS-L technology, making the validation and testing process time-consuming. Additionally, more time will be required to optimize the B-series for AI server systems in aspects such as network communication and cooling performance. It is anticipated that the GB200 and B100 products will not see significant production volumes until 4Q24 or 1Q25.

One key takeaway from the ongoing GTC is that Nvidia's AI empire has taken shape with strong partnerships from TSMC and other Taiwanese makers, such as those major server ODMs.

According to the news report from the technology-focused media DIGITIMES Asia, during his keynote at GTC on March 18, Huang underscored his company's partnerships with TSMC, as well as the supply chain in Taiwan. Speaking to the press later, Huang said Nvidia will have a very strong demand for CoWoS, the advanced packaging services TSMC offers.

TSMC is experiencing unprecedented demand from AI chip customers—unnamed parties have (fancifully) requested the construction of entirely new fabrication facilities. Taiwan's leading semiconductor contract manufacturer seems to concentrating on "sensible" expansions, mainly in the area of CoWoS packaging output—according to an Economic Daily report, company leadership and local government were negotiating over the construction of four new advanced packaging plants. Insiders propose that plans have been revised—an investment in excess of 500 billion yuan ($16 billion) will enable the founding of six new CoWoS-focused facilities. TSMC is expected to make an official announcement next month—industry moles reckon that construction work will start in April. Two (of the six total) advanced packaging plants could become fully operational before the conclusion of 2024.

Lately, TSMC has initiated an ambitious recruitment drive—targeting around 6000 new workers. A touring entity is tasked with the attraction of "talents with high enthusiasm for semiconductors." The majority of new recruits are likely heading to new or expanded Taiwan-based facilities. The Economic Daily report proposes that Chiayi City's technological hub will play host to TSMC's new CoWoS packaging plants. A DigiTimes Asia news piece (from January) posited that TSMC leadership anticipates CoWoS output reaching 44,000 units by the end of 2024. This predicted tally could grow, thanks to the (rumored) activation of additional factories. CoWoS packaging is considered to be a vital aspect of AI accelerators—insiders believe that TSMC's latest investment will boost production of NVIDIA H100 GPUs. The combined output of six new CoWoS plants will assist greatly in the creation of next-gen B100 chips.

Jensen Huang's opening GTC 2024 keynote is scheduled to happen tomorrow afternoon (13:00 Pacific time)—many industry experts believe that the NVIDIA boss will take the stage and formally introduce his company's B100 "Blackwell" GPU architecture. An enlightened few have been treated to preview (AI and HPC) units—including Dell's CEO, Jeff Clarke—but pre-introduction leaks have not flowed out. Team Green is likely enforcing strict conditions upon a fortunate selection of trusted evaluators, within a pool of ecosystem partners and customers.

Today, a brave soul has broken that silence—tech tipster, AGF/XpeaGPU, fears repercussions from the leather-jacketed one. They revealed a handful of technical details, a day prior to Team Green's highly anticipated unveiling: "I don't want to spoil NVIDIA B100 launch tomorrow, but this thing is a monster. 2 dies on (TSMC) CoWoS-L, 8x8-Hi HBM3E stacks for 192 GB of memory." They also crystal balled an inevitable follow-up card: "one year later, B200 goes with 12-Hi stacks and will offer a beefy 288 GB. And the performance! It's... oh no Jensen is there... me run away!" Reuters has also joined in on the fun, with some predictions and insider information: "NVIDIA is unlikely to give specific pricing, but the B100 is likely to cost more than its predecessor, which sells for upwards of $20,000." Enterprise products are expected to arrive first—possibly later this year—followed by gaming variants, maybe months later.

TrendForce highlights the current landscape of the HBM market, which as of early 2024, is primarily focused on HBM3. NVIDIA's upcoming B100 or H200 models will incorporate advanced HBM3e, signaling the next step in memory technology. The challenge, however, is the supply bottleneck caused by both CoWoS packaging constraints and the inherently long production cycle of HBM—extending the timeline from wafer initiation to the final product beyond two quarters.

The current HBM3 supply for NVIDIA's H100 solution is primarily met by SK hynix, leading to a supply shortfall in meeting burgeoning AI market demands. Samsung's entry into NVIDIA's supply chain with its 1Znm HBM3 products in late 2023, though initially minor, signifies its breakthrough in this segment.

During the recent IEDM conference, TSMC previewed its process roadmap for delivering next-generation chip packages packing over one trillion transistors by 2030. This aligns with similar long-term visions from Intel. Such enormous transistor counts will come through advanced 3D packaging of multiple chipsets. But TSMC also aims to push monolithic chip complexity higher, ultimately enabling 200 billion transistor designs on a single die. This requires steady enhancement of TSMC's planned N2, N2P, N1.4, and N1 nodes, which are slated to arrive between now and the end of the decade. While multi-chipset architectures are currently gaining favor, TSMC asserts both packaging density and raw transistor density must scale up in tandem. Some perspective on the magnitude of TSMC's goals include NVIDIA's 80 billion transistor GH100 GPU—among today's largest chips, excluding wafer-scale designs from Cerebras.

Yet TSMC's roadmap calls for more than doubling that, first with over 100 billion transistor monolithic designs, then eventually 200 billion. Of course, yields become more challenging as die sizes grow, which is where advanced packaging of smaller chiplets becomes crucial. Multi-chip module offerings like AMD's MI300X and Intel's Ponte Vecchio already integrate dozens of tiles, with PVC having 47 tiles. TSMC envisions this expansion to chip packages housing more than a trillion transistors via its CoWoS, InFO, 3D stacking, and many other technologies. While the scaling cadence has recently slowed, TSMC remains confident in achieving both packaging and process breakthroughs to meet future density demands. The foundry's continuous investment ensures progress in unlocking next-generation semiconductor capabilities. But physics ultimately dictates timelines, no matter how aggressive the roadmap.

The burgeoning AI market is significantly impacting TSMC's CoWoS (Chip on Wafer on Substrate) advanced packaging production capacity, causing it to overflow due to high demand from major companies like NVIDIA, AMD, and Amazon. To accommodate this, TSMC is in the process of expanding its production capacity by acquiring additional CoWoS machines from equipment manufacturers like Xinyun, Wanrun, Hongsu, Titanium, and Qunyi. These expansions are expected to be operational in the first half of the next year, leading to an increased monthly production capacity, potentially close to 30,000 pieces, enabling TSMC to cater to more AI-related orders. These endeavors to increase capacity are in response to the amplified demand for AI chips from their applications in various domains, including autonomous vehicles and smart factories.

Despite TSMC's active steps to enlarge its CoWoS advanced packaging production, the overwhelming client demand is driving the company to place additional orders with equipment suppliers. It has been indicated that NVIDIA is currently TSMC's largest CoWoS advanced packaging customer, accounting for 60% of its production capacity. Due to the surge in demand, companies like AMD, Amazon, and Broadcom are also placing urgent orders, leading to a substantial increase in TSMC's advanced process capacity utilization. The overall situation indicates a thriving scenario for equipment manufacturers with clear visibility of orders extending into the following year, even as they navigate the challenges of fulfilling the rapidly growing and immediate demand in the AI market.

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.