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Samsung, the Korean tech giant, has unveiled SAINT technology to counter TSMC’s advanced CoWoS packaging, aiming to benefit from the surging AI market. Market reports reveal that Samsung is strategically procuring a substantial amount of 2.5D packaging equipment, indicating a keen awareness of the soaring demand from AI chip companies like NVIDIA, reported by Korean media The Elec.
Samsung has acquired 16 sets of packaging equipment from the Japanese company Shinkawa. Currently, 7 sets have been received, with the possibility of additional orders based on future requirements. Samsung’s objective is to demonstrate its prowess in packaging and HBM technologies, seeking recognition and partnership with NVIDIA. As the limitations in NVIDIA’s current supply chain, especially due to insufficient CoWoS advanced packaging capacity in TSMC, Samsung emerges as a promising alternative for diverse supply chain.
On the other hand, NVIDIA’s ambitious goal of achieving USD 300 billion in AI sector revenue by 2027 requires a reliable supply chain, as per reported by TechNews. To this end, Samsung is poised to supply its next-gen GPU, Blackwell, featuring HBM3 and 2.5D packaging. This move aligns with NVIDIA’s strategy to diversify its supply chain away from existing providers like TSMC.
For Samsung, this collaboration presents a significant opportunity to enter the thriving AI market. Success in this venture could not only bolster the financial performance of Samsung’s memory and advanced packaging divisions but also open doors to orders from players like AMD and Tesla. However, the key lies in how effectively Samsung meets the formidable market demand, particularly in semiconductor production, advanced packaging, and memory technology.
(Image: Samsung)
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As applications like AIGC, 8K, AR/MR, and others continue to develop, 3D IC stacking and heterogeneous integration of chiplet have become the primary solutions to meet future high-performance computing demands and extend Moore’s Law.
Major companies like TSMC and Intel have been expanding their investments in heterogeneous integration manufacturing and related research and development in recent years. Additionally, leading EDA company Cadence has taken the industry lead by introducing the “Integrity 3D-IC” platform, an integrated solution for design planning, realization, and system analysis simulation tools, marking a significant step towards 3D chip stacking.
Differences between 2.5D and 3D Packaging
The main difference between 2.5D and 3D packaging technologies lies in the stacking method. 2.5D packaging involves stacking chips one by one on an interposer or connecting them through silicon bridges, primarily used for assembling logic processing chips and high-bandwidth memory. On the other hand, 3D packaging is a technology that vertically stacks chips, mainly targeting high-performance logic chips and SoC manufacturing.
CPU and HBM Stacking Demands
With the rapid development of applications like AIGC, AR/VR, and 8K, it is expected that a significant amount of computational demand will arise, particularly driving the need for parallel computing systems capable of processing big data in a short time. To overcome the bandwidth limitations of DDR SDRAM and further enhance parallel computing performance, the industry has been increasingly adopting High-Bandwidth Memory (HBM). This trend has led to a shift from the traditional “CPU + memory (such as DDR4)” architecture to the “Chip + HBM stacking” 2.5D architecture. With continuous growth in computational demand, the future may see the integration of CPU, GPU, or SoC through 3D stacking.
3D Stacking with HBM Prevails, but CPU Stacking Lags Behind
HBM was introduced in 2013 as a 3D stacked architecture for high-performance SDRAM. Over time, the stacking of multiple layers of HBM has become widespread in packaging, while the stacking of CPUs/GPUs has not seen significant progress.
The main reasons for this disparity can be attributed to three factors: 1. Thermal conduction, 2. Thermal stress, and 3. IC design. First, 3D stacking has historically performed poorly in terms of thermal conduction, which is why it is primarily used in memory stacking, as memory operations generate much less heat than logic operations. As a result, the thermal conduction issues faced by current memory stacking products can be largely disregarded.
Second, thermal stress issues arise from the mismatch in coefficients of thermal expansion (CTE) between materials and the introduction of stress from thinning the chips and introducing metal layers. The complex stress distribution in stacked structures has a significant negative impact on product reliability.
Finally, IC design challenges from a lack of EDA tools, as traditional CAD tools are inadequate for handling 3D design rules. Developers must create their own tools to address process requirements, and the complex design of 3D packaging further increases the design, manufacturing, and testing costs.
How EDA Companies Offer Solutions
Cadence, during the LIVE Taiwan 2023 user annual conference, highlighted its years of effort in developing solutions. They have introduced tools like the Clarity 3D solver, Celsius thermal solver, and Sigrity Signal and Power Integrity, which can address thermal conduction and thermal stress simulation issues. When combined with Cadence’s comprehensive EDA tools, these offerings contribute to the growth of the “Integrity 3D-IC” platform, aiding in the development of 3D IC design.
“3D IC” represents a critical design trend in semiconductor development. However, it presents greater challenges and complexity than other projects. In addition to the challenges in Logic IC design, there is a need for analog and multi-physics simulations. Therefore, cross-platform design tools are indispensable. The tools provided by EDA leader Cadence are expected to strengthen the 3D IC design tool platform, reducing the technological barriers for stacking CPU, GPU, or SoC to enhance chip computing performance.
This article is from TechNews, a collaborative media partner of TrendForce.
(Photo credit: TSMC)
In-Depth Analyses
With the advancements in AIGC models such as ChatGPT and Midjourney, we are witnessing the rise of more super-sized language models, opening up new possibilities for High-Performance Computing (HPC) platforms.
According to TrendForce, by 2025, the global demand for computational resources in the AIGC industry – assuming 5 super-sized AIGC products equivalent to ChatGPT, 25 medium-sized AIGC products equivalent to Midjourney, and 80 small-sized AIGC products – would be approximately equivalent to 145,600 – 233,700 units of NVIDIA A100 GPUs. This highlights the significant impact of AIGC on computational requirements.
Additionally, the rapid development of supercomputing, 8K video streaming, and AR/VR will also lead to an increased workload on cloud computing systems. This calls for highly efficient computing platforms that can handle parallel processing of vast amounts of data.
However, a critical concern is whether hardware advancements can keep pace with the demands of these emerging applications.
HBM: The Fast Lane to High-Performance Computing
While the performance of core computing components like CPUs, GPUs, and ASICs has improved due to semiconductor advancements, their overall efficiency can be hindered by the limited bandwidth of DDR SDRAM.
For example, from 2014 to 2020, CPU performance increased over threefold, while DDR SDRAM bandwidth only doubled. Additionally, the pursuit of higher transmission performance through technologies like DDR5 or future DDR6 increases power consumption, posing long-term impacts on computing systems’ efficiency.
Recognizing this challenge, major chip manufacturers quickly turned their attention to new solutions. In 2013, AMD and SK Hynix made separate debuts with their pioneering products featuring High Bandwidth Memory (HBM), a revolutionary technology that allows for stacking on GPUs and effectively replacing GDDR SDRAM. It was recognized as an industry standard by JEDEC the same year.
In 2015, AMD introduced Fiji, the first high-end consumer GPU with integrated HBM, followed by NVIDIA’s release of P100, the first AI server GPU with HBM in 2016, marking the beginning of a new era for server GPU’s integration with HBM.
HBM’s rise as the mainstream technology sought after by key players can be attributed to its exceptional bandwidth and lower power consumption when compared to DDR SDRAM. For example, HBM3 delivers 15 times the bandwidth of DDR5 and can further increase the total bandwidth by adding more stacked dies. Additionally, at system level, HBM can effectively manage power consumption by replacing a portion of GDDR SDRAM or DDR SDRAM.
As computing power demands increase, HBM’s exceptional transmission efficiency unlocks the full potential of core computing components. Integrating HBM into server GPUs has become a prominent trend, propelling the global HBM market to grow at a compound annual rate of 40-45% from 2023 to 2025, according to TrendForce.
The Crucial Role of 2.5D Packaging
In the midst of this trend, the crucial role of 2.5D packaging technology in enabling such integration cannot be overlooked.
TSMC has been laying the groundwork for 2.5D packaging technology with CoWoS (Chip on Wafer on Substrate) since 2011. This technology enables the integration of logic chips on the same silicon interposer. The third-generation CoWoS technology, introduced in 2016, allowed the integration of logic chips with HBM and was adopted by NVIDIA for its P100 GPU.
With development in CoWoS technology, the interposer area has expanded, accommodating more stacked HBM dies. The 5th-generation CoWoS, launched in 2021, can integrate 8 HBM stacks and 2 core computing components. The upcoming 6th-generation CoWoS, expected in 2023, will support up to 12 HBM stacks, meeting the requirements of HBM3.
TSMC’s CoWoS platform has become the foundation for high-performance computing platforms. While other semiconductor leaders like Samsung, Intel, and ASE are also venturing into 2.5D packaging technology with HBM integration, we think TSMC is poised to be the biggest winner in this emerging field, considering its technological expertise, production capacity, and order capabilities.
In conclusion, the remarkable transmission efficiency of HBM, facilitated by the advancements in 2.5D packaging technologies, creates an exciting prospect for the seamless convergence of these innovations. The future holds immense potential for enhanced computing experiences.
In-Depth Analyses
The surge in AIGC and new technologies such IoT, AI, 5G, AR/VR are driving a huge demand for computational power of high-end chips. This has been even outpacing the performance increase offered by the long-standing Moore’s Law, ushering in a “post-Moore” era where revolutions in advanced chip design are crucial.
Over recent years, chiplet design has seemingly become the mainstream approach for upgrading high-end chips. The concept is to allow more transistors on a single chip, effectively increasing the production yield of high-end chips while reducing overall costs.
By the large, major IC players have all jumped on board. Even Apple has joined the game by releasing their M1 Ultra SoC using the chiplet concept, which doubles computational performance by integrating two M1 Max units in a single chip.
The CPU sector is definitely a clear demonstration of this trend:
Transition from Bumping to Hybrid Bonding
Our analysis in “Chiplet Design: A Real Game-Changer for Substrates” laid out the comprehensive impact of the evolution of chiplet technology on substrates. In fact, chiplets have already caused a significant disruption to the most advanced semiconductor packaging technologies, necessitating the transition towards advanced 2.5D and 3D packaging technologies.
The bottleneck of advanced packaging lies in the chiplets’ interconnections, with bump and microbump still being the key technology for linking chips and forming I/O joints. These connection densities are hard to enhance, thus limiting the overall chip’s transmission speed. In addition, the more chiplets being stacked, the bigger the chip volume gets. The challenge is how to limit the chip size within a specific range, considering the current technical constraints.
Therefore, copper-to-copper hybrid bonding, also known as DBI (Direct Bond Interconnect), has been emerging as the key technology route that overcomes major hurdles in chiplet integration from the bottom-up.
Unlike bumping technology, hybrid bonding significantly shrinks the I/O joint space. The future transmission demand requires the I/O joint space between chiplets to be less than 10µm. While bumping is limited to around 20µm, hybrid bonding can take this down to an impressive 1µm or even less. This also means more I/O joints can be fitted in the same chip size – even reaching up to millions on a mere 1cm2 chip.
On top of this, hybrid bonding only adds an extra 1-2µm of thickness, compared to the 10-30µm of microbump, thereby helping reduce the thickness of stacked chips.
To put it simply, hybrid bonding can boost transmission efficiency, minimize energy usage with higher density of copper joints, manage chip volume, and even cut down on material costs.
The Race for Advanced Packaging Is Kicking Off
Moving forward, hybrid bonding is set to become the key technology supporting the continuous development of chiplet design and 3D packaging. This has been exemplified by TSMC’s front-end So IC packaging technology which is based on hybrid bonding. This puts AMD, a key customer of TSMC, in a favorable position to get ahead.
From AMD’s roadmap of 3D V-Cache technology, they have stacked SRAM on top of CCX (CPU Complex), and gradually integrated it into Milan-X series, the EPYC server CPUs, and Ryzen series, the consumer-grade CPUs, over the past two years. This has significantly improved performance and power consumption as a whole.
Not to be outdone, this year Intel also launched their Foveros Direct packaging technology, which is also based on hybrid bonding route. Assuming everything proceeds smoothly, we can anticipate the release of CPUs utilizing Foveros Direct technology by 2024.
As we look at the current products, AMD’s hybrid bonding apparently focuses on stacking SRAM and computing units at the moment. However, as CPU leaders deepen their understanding of this technology, the application field is expected to further expand. In other words, the future of hybrid bonding solutions stacking multiple computation units is just around the corner.