Core Insights - The article emphasizes the critical role of High Bandwidth Memory (HBM) in supporting AI technologies, highlighting its evolution from a niche technology to a necessity for AI performance [1][2][15]. Understanding HBM - HBM is designed to address the limitations of traditional memory, which struggles to keep up with the computational demands of AI models [4][7]. - Traditional memory types like DDR5 and LPDDR5 have significant drawbacks, including limited bandwidth, high latency, and inefficient data transfer methods [4][10]. HBM Advantages - HBM offers three main advantages: significantly higher bandwidth, reduced power consumption, and a compact form factor suitable for high-density AI servers [11][12][14]. - For instance, HBM3 has a bandwidth of 819GB/s, while HBM4 is expected to double that to 2TB/s, enabling faster AI model training [12][15]. HBM Generational Roadmap - The KAIST report outlines a roadmap for HBM development from HBM4 to HBM8, detailing the technological advancements and their implications for AI [15][17]. - Each generation of HBM is tailored to meet the evolving needs of AI applications, with HBM4 focusing on mid-range AI servers and HBM5 addressing the computational demands of large models [17][27]. HBM Technical Innovations - HBM's architecture includes a "sandwich" 3D stacking design that enhances data transfer efficiency [8][9]. - Innovations such as Near Memory Computing (NMC) in HBM5 allow memory to perform computations, reducing the workload on GPUs and improving processing speed [27][28]. Market Dynamics - The global HBM market is dominated by three major players: SK Hynix, Samsung, and Micron, which together control over 90% of the market share [80][81]. - These companies have secured long-term contracts with major clients, ensuring a steady demand for HBM products [83][84]. Future Challenges - The article identifies key challenges for HBM's widespread adoption, including high costs, thermal management, and the need for a robust ecosystem [80]. - Addressing these challenges is crucial for transitioning HBM from a high-end product to a more accessible solution for various applications [80].

Core Insights - Nvidia's CEO Jensen Huang announced the receipt of advanced memory samples from Samsung Electronics and SK Hynix, indicating strong support for Nvidia's growth in AI chip demand [3][4] - Huang expressed concerns about potential memory supply shortages due to robust business growth across various sectors, suggesting that memory prices may rise depending on operational conditions [3] - TSMC's CEO C.C. Wei acknowledged Nvidia's significant wafer demand, emphasizing the critical role TSMC plays in Nvidia's success [3] Memory Market Dynamics - SK Hynix, Micron, and Samsung are in fierce competition to dominate the HBM4 market, estimated to be worth $100 billion [6] - Micron has begun shipping its next-generation HBM4 memory, claiming record performance and efficiency, with bandwidth exceeding 2.8TB/s [6][7] - SK Hynix has also delivered 12-Hi HBM4 samples to major clients, including Nvidia, and plans to ramp up production [7][8] Future HBM Generations - The latest HBM generation, HBM4, supports bandwidth up to 2TB/s and a maximum of 16 layers of Hi DRAM chips, with a capacity of up to 64GB [10] - Future generations, HBM5 to HBM8, are projected to significantly increase bandwidth and capacity, with HBM8 expected to reach 64TB/s by 2038 [11][12][15] - HBM technology is evolving with new stacking techniques and cooling methods, enhancing performance and efficiency [12][13]

Core Viewpoint - The cooling technology will become a key competitive factor in the high bandwidth memory (HBM) market as HBM5 is expected to commercialize around 2029, shifting the focus from packaging to cooling methods [1][2]. Summary by Sections HBM Technology Roadmap - The roadmap from HBM4 to HBM8 spans from 2025 to 2040, detailing advancements in HBM architecture, cooling methods, TSV density, and interlayer technologies [1]. - HBM4 is projected to have a data rate of 8 Gbps, a bandwidth of 2.0 TB/s, and a capacity of 36/48 GB per HBM, utilizing liquid cooling methods [3]. - HBM5 will maintain the 8 Gbps data rate but will double the bandwidth to 4 TB/s and increase capacity to 80 GB [3]. - HBM6 will introduce a data rate of 16 Gbps and a bandwidth of 8 TB/s, with a capacity of 96/120 GB [3]. - HBM7 is expected to reach 24 TB/s bandwidth and 160/192 GB capacity, while HBM8 will achieve 32 Gbps data rate, 64 TB/s bandwidth, and 200/240 GB capacity [3]. Cooling Technologies - HBM5 will utilize immersion cooling, where the substrate and package are submerged in cooling liquid, addressing limitations of current liquid cooling methods [1]. - HBM7 will require embedded cooling systems to inject cooling liquid between DRAM chips, introducing fluid TSVs [2]. - The professor emphasizes that cooling will be critical as the base chip will take on part of the GPU workload starting from HBM4, leading to increased temperatures [1][2]. Bonding and Performance Factors - Bonding will also play a significant role in determining HBM performance, with mixed glass and silicon interlayers being introduced from HBM6 onwards [2].

Core Viewpoint - The cooling technology will become a key competitive factor in the high bandwidth memory (HBM) market as HBM5 is expected to commercialize around 2029, shifting the focus from packaging to cooling solutions [1][2]. Summary by Sections HBM Technology Roadmap - The roadmap from HBM4 to HBM8 spans from 2025 to 2040, detailing advancements in HBM architecture, cooling methods, TSV density, and interposer layers [1]. - HBM4 is projected to be available in 2026, with a data rate of 8 Gbps, bandwidth of 2.0 TB/s, and a capacity of 36/48 GB per HBM [3]. - HBM5, expected in 2029, will double the bandwidth to 4 TB/s and increase capacity to 80 GB [3]. - HBM6, HBM7, and HBM8 will further enhance data rates and capacities, reaching up to 32 Gbps and 240 GB respectively by 2038 [3]. Cooling Technologies - HBM5 will utilize immersion cooling, where the substrate and package are submerged in cooling liquid, addressing limitations of current liquid cooling methods [2]. - HBM7 will require embedded cooling systems to inject coolant between DRAM chips, introducing fluid TSVs for enhanced thermal management [2]. - The introduction of new types of TSVs, such as thermal TSVs and power TSVs, will support the cooling needs of future HBM generations [2]. Performance Factors - Bonding techniques will also play a crucial role in HBM performance, with HBM6 introducing a hybrid interposer of glass and silicon [2]. - The integration of advanced packaging technologies will allow base chips to take on GPU workloads, necessitating improved cooling solutions due to increased temperatures [2].