On the 7th, TSMC convened the 2023 Supply Chain Management Forum, C.C. Wei, President of TSMC, acknowledging persistent inflationary pressures, remains optimistic about 2024. He also cited the rapid growth of AI applications as a key driver of opportunities, reported by CTEE.

Wei addressed the pivotal role of semiconductors in AI development. Looking ahead, the focus extends to continual AI technology advancement and computational power enhancement, with a parallel emphasis on energy consumption reduction. Given projections of AI computational demand tripling in the next 2 years, addressing energy efficiency becomes paramount.

To meet escalating AI computational needs, Wei highlighted the imperative to develop technologies balancing high performance with effective power control. TSMC commits to providing ample production capacity to meet end-user demands while sustaining cost-efficiency.

Global supply chain resilience amid challenges from society, economy, and geopolitics. Collaborating with partners. TSMC navigates 3nm, advanced and specialty processes for capacity expansions, R&D for 2nm and beyond, and global production plans. The company aims to lead through cutting-edge technology and top-notch manufacturing services, fostering innovation for customers.

Apart from the insightful speech, Wei also presented the 2023 Excellent Performance Award during the forum. It recognized suppliers’ performance in technology collaboration, global production support, green manufacturing, fab construction management, production capacity, quality control and other categories. Companies like Applied Materials, ASM International, KLA, Lam Research, TOKYO ELECTRON LIMITED and others.

(Image: TSMC)

Bloomberg reported in early December 2023 that the Chinese government has been directly investing to assist Huawei in building its chip supply chain since 2019, indicating that the ongoing uncertainties in the U.S.-China trade war, the pursuit of semiconductor industry self-sufficiency is expected to be a long-term development direction for China.

TrendForce’s insight:

1. Chinese Government Establishes Investment Fund for Huawei, Creating Exclusive Supply Chain

On May 15, 2019, when the United States announced the inclusion of Huawei and its 70 subsidiaries in the trade blacklist, the Chinese government swiftly established a fund named “Shenzhen Major Industry Investment Group” in Shenzhen, where Huawei’s headquarter is located.

This fund, directly funded by the local government, aimed primarily at creating a large supply chain for Huawei, consisting of optical factories, chip equipment developers, and chemical manufacturers.

One chip manufacturer, SiCarrier, maintained close ties with Huawei. Besides talent exchanges, the company also transferred over a dozen patented technologies to Huawei.

2. Escalating U.S.-China Trade War Drives Long-Term Semiconductor Self-Reliance in China

Recently, the Nikkei news, in collaboration with the research company Fomalhaut Techno Solutions, conducted a renewed disassembly of Huawei’s Mate 60 Pro smartphone. The findings indicate that, based on component costs, approximately 47% of the components are manufactured in China.

This contradicts the earlier claim by Chinese media of a 90% domestic production rate. Nevertheless, the Mate 60 Pro shows a noteworthy 18% increase in domestic production compared to the Mate 40 Pro in 2020.

Additionally, during the component analysis, it was reaffirmed that the self-developed 5G processor, Kirin 9000S, featured in Huawei’s Mate 60 Pro smartphone, has a circuit width of 7nm. This demonstrates China’s semiconductor technological prowess despite restrictions imposed by the U.S. ban.

However, when the semiconductor industry value chain is divided regionally, it can be observed that in the uppermost stream of the supply chain, including electronic design automation software and licensed intellectual property used in chip design, this domain is primarily concentrated in the hands of U.S. firms.

Currently, China’s overall share in the global semiconductor value chain remains relatively low and is more concentrated in downstream packaging and manufacturing. If China aims to establish a fully “self-sufficient” semiconductor supply chain, it is estimated that there is still a long way to go.

However, what is certain is that in the ongoing U.S.-China trade war, the pursuit of semiconductor industry autonomy will be a long-term development direction for China.

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Market reports suggest Nvidia’s new product release cycle has shortened from two to a year, sparking intense competition among major memory companies in the realm of next-gen High Bandwidth Memory (HBM) technology. Samsung, SK Hynix, and Micron are fervently competing, with SK Hynix currently holding the dominant position in the HBM market. However, Micron and Samsung are strategically positioned, poised for a potential overtake, reported by TechNews.

Current Status of the HBM Industry

SK Hynix made a breakthrough in 2013 by successfully developing and mass-producing HBM using the Through Silicon Via (TSV) architecture. In 2019, they achieved success with HBM2E, maintaining the overwhelming advantage in the HBM market. According to the latest research from TrendForce, Nvidia plan to partner with more HBM suppliers. Samsung, as one of the suppliers, its HBM3 (24GB) is anticipated to complete verification with NVIDIA by December this year.

Regarding HBM3e progress, Micron, SK Hynix, and Samsung provided 8-layer (24GB) Nvidia samples in July, August, and October, respectively, with the fastest verification expected by year-end. All three major players anticipate completing verification in the first quarter of 2024.

As for HBM4, the earliest launch is expected in 2026, with a stack increase to 16 layers from the existing 12 layers. The memory stack will likely adopt a 2048-bit memory stack connection interface, driving demand for the new “Hybrid Bonding” stacking method. The 12-layer HBM4 product is set to launch in 2026, followed by the 16-layer product expected in 2027.

Navigating HBM4, the New Technologies and Roadmaps of Memory Industry Leaders

SK Hynix

According to reports from Business Korea, SK Hynix is preparing to adopt “2.5D Fan-Out” packaging for the next-generation HBM technology. This move aims to enhance performance and reduce packaging costs. This technology, not previously used in the memory industry but common in advanced semiconductor manufacturing, is seen as having the potential to “completely change the semiconductor and foundry industry.” SK Hynix plans to unveil research results using this packaging method as early as next year.

The 2.5D Fan-Out packaging technique involves arranging two DRAM horizontally and assembling them similar to regular chips. The absence of a substrate beneath the chips allows for thinner chips, significantly reducing the thickness when installed in IT equipment. Simultaneously, this technique bypasses the Through Silicon Via (TSV) process, providing more Input/Output (I/O) options and lowering costs. 

According to their previous plan, SK Hynix aims to mass-produce the sixth-generation HBM (HBM4) as early as 2026. The company is also actively researching “Hybrid Bonding” technology, likely to be applied to HBM4 products.

Currently, HBM stacks are placed on the interposer next to or GPUs and are connected to their interposer. While SK Hynix’s new goal is to eliminate the interposer completely, placing HBM4 directly on GPUs from companies like Nvidia and AMD, with TSMC as the preferred foundry.

Samsung

Samsung is researching the application of photonics in HBM technology’s interposer layer, aiming to address challenges related to heat and transistor density. Yan Li, Principal Engineer in Samsung’s advanced packaging team, shared insights at the OCP Global Summit in October 2023.

(Image: Samsung)

According to Samsung, The industry has made significant strides in integrating photonics with HBM through two main approaches. One involves placing a photonics interposer between the bottom packaging layer and the top layer containing GPU and HBM, acting as a communication layer. However, this method is costly, requiring an interposer and photon I/O for logic chips and HBM.

(Image: Samsung)

The alternative approach separates the HBM memory module from packaging, directly connecting it to the processor using photonics. Rather than dealing with the complexity of packaging, a more efficient approach is to separate the HBM memory module from the chip itself and connect it to the logic IC using photonics technology. This approach not only simplifies the manufacturing and packaging costs for HBM and logic ICs but also eliminates the need for internal digital-to-optical conversions in the circuitry. However, careful attention is required to address heat dissipation.

Micron

As reported by Tom’s Hardware, Micron’s 8-layer HBM3e (24GB) is expected to launch in early 2024, contributing to improved AI training and inference performance. The 12-layer HBM3e (36GB) chip is expected to debut in 2025.

Micron is working on HBM4 and HBM4e along with other companies. The required bandwidth is expected to exceed 1.5 TB/s. Micron anticipates launching 12-layer and 16-layer HBM4 with capacities of 36GB to 48GB between 2026 and 2027. After 2028, HBM4E will be introduced, pushing the maximum bandwidth beyond 2+ TB/s and increasing stack capacity to 48GB to 64GB.

Micron is taking a different approach from Samsung and SK Hynix by not integrating HBM and logic chips into a single die, suggested by Chinese media Semiconductor Industry Observation. This difference in strategy may lead to distinct technical paths, and Micron might advise Nvidia, Intel, AMD that relying solely on the same company’s chip carries greater risks.

(Image: Micron)

TSMC Aids Memory Stacking       

Currently, TSMC 3DFabric Alliance closely collaborates with major memory partners, including Micron, Samsung, and SK Hynix. This collaboration ensures the rapid growth of HBM3 and HBM3e, as well as the packaging of 12-layer HBM3/HBM3e, by providing more memory capacity to promote the development of generative AI.

(Image: TSMC)

(Image: SK Hynix)

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• Manufacturers Anticipate Completion of NVIDIA’s HBM3e Verification by 1Q24; HBM4 Expected to Launch in 2026, Says TrendForce
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• [News] Memory Giants Samsung & Micron Actively Embrace DDR5 and HBM as Favorable Choices
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The investment momentum of China’s Big Fund Phase II shows no signs of slowing down, with its latest investment directed at Shanghai Huali Microelectronics Co., Ltd. (HLMC), a subsidiary of Huahong Group.

According to Sina Finance’s report, this substantial investment of up to USD 1 billion will support HLMC in continuous development of advanced process technologies and enhancing its manufacturing capabilities.

Given industry reports from as early as 2020 suggesting HLMC has progressed to the 14nm process, this investment from the Big Fund II signifies China’s commitment to even more advanced processes below 10nm in pursuit of semiconductor self-sufficiency.

Recently, Huahong Corporation announced that, to accelerate the research and development as well as mass production of the 40nm featured IC process on the 12-inch wafer production line in Wuxi, Jiangsu Province, jointly established by its wholly-owned subsidiary Huahong Hongli and other joint venture partners, Huahong Hongli signed a “Technology Development Agreement” with HLMC on December 1, 2023.

The agreement stipulates that HLMC will provide Huahong Hongli with 40nm logic fundamentals and related process technology, along with corresponding technical services, consultation, and support.

In contrast to Semiconductor Manufacturing International Corp. (SMIC), historically positioned as China’s leading foundry to compete with TSMC, HLMC has maintained a more discreet profile.

Officially capable of manufacturing chips on 22nm- and 28nm-class fabrication technologies, rumors circulated in the market as early as 2020 that HLMC could produce chips on a 14nm FinFET process nodes using deep ultraviolet (DUV).

Moreover, leveraging DUV multi-patterning methods could potentially drive production for advanced processes below 10nm, contributing to China’s pursuit of semiconductor self-sufficiency.

HLMC increased its registered capital from approximately CNY 22 billion to around CNY 28.4 billion, with Big Fund Phase II holding a stake exceeding 10%. This data indicates Big Fund Phase II’s confidence in HLMC’s development, providing substantial financial support to bolster its progress in semiconductor processes.

The investment direction of Big Fund Phase II differs from that of Big Fund Phase I, which primarily focusing on key industries such as chip manufacturing. It is more diversified, spanning multiple areas, including wafer manufacturing, integrated circuit design tools, chip design, packaging testing, equipment, components, materials, and applications.

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(Photo credit: Hua Hong Group)

AMD announced the Ryzen 8040 series processor at the AMD Advance AI event. With TSMC’s advanced 4nm process, this new processor boasts up to a 1.6x improvement in AI processing performance compared to its predecessor.

From AMD’s press release, the Ryzen 8040 series introduces the Ryzen AI Network Processing Unit (NPU), featuring up to 8 Zen 4 CPU cores and an integrated GPU based on RDNA 3. Utilizing TSMC’s 4nm process, AMD claims that the Ryzen 8040 series NPU is approximately 1.4x faster than the NPU in the previous 7040 series and 1.8x faster than Intel’s high-end i9-13900H Processor.

AMD CEO, Lisa Su, stated that AMD is the first global entity to integrate an NPU into an x86 processor. The Ryzen 8040 series is already in supply and is set to be featured in new models from major players such as Dell, HP, Acer, Asus, and Lenovo starting early 2024.

In fact, the integration of NPUs into Windows PCs is not a new thing. Both AMD and Intel lag behind Qualcomm. Back in October 2022, Qualcomm had already revealed its collaboration with on the development of the Microsoft SQ3 processor, set to be used in the Surface Pro 9 5G tablet, reported by ANUE.

While AMD and Intel compete, Apple is also a formidable player in the AI field. Since the introduction of the A11 Bionic in 2017, Apple has been integrating the neural engine into its hardware to accelerate AI tasks, similar to the NPUs developed by AMD and Intel, aiding in facial recognition and photo processing.

(Image: AMD)