In recent years, the explosive growth of AI computing demand has made memory bandwidth and capacity central performance metrics for large language models, generative AI, and high-performance computing (HPC) workloads. These applications must access massive volumes of model weights and intermediate data within extremely short timeframes, making “data movement” an increasingly critical bottleneck in the semiconductor industry. Against this backdrop, TSMC’s CoWoS (Chip-on-Wafer-on-Substrate) advanced packaging technology and High Bandwidth Memory (HBM) have formed a highly symbiotic relationship, redefining the architecture of AI servers and high-end computing platforms.
First, CoWoS plays a pivotal role in breaking traditional memory bandwidth limitations. In conventional architectures, CPUs or GPUs connect to external DRAM through printed circuit boards, resulting in long signal transmission distances, high power consumption, and limited bandwidth. By introducing a silicon interposer, CoWoS tightly integrates logic chips and multiple HBM stacks within a single package, shortening data transmission distances to the millimeter scale and dramatically increasing I/O density and efficiency. This architecture enables AI accelerators to access memory at extremely high bandwidth, making it the standard configuration for modern AI GPUs and accelerators. As the demand for KV cache in large models grows rapidly, high bandwidth and large memory capacity have shifted from being “nice-to-have” features to absolute necessities.
Second, CoWoS is accelerating the evolution of HBM technology generations. As AI model parameter counts continue to grow, the memory capacity required within a single package keeps increasing. From HBM2 and HBM2e to HBM3 and HBM3e, stack height and bandwidth have consistently improved. Future AI chips may integrate even more memory stacks to support larger models and more complex inference workloads. In other words, advanced packaging capability has become a key factor determining the pace of memory specification upgrades.
This demand surge is also reshaping the supply–demand structure of the overall memory market. Because HBM is a high-margin product, DRAM manufacturers are shifting substantial production capacity toward HBM, leading to relatively tighter supply for traditional PC and consumer electronics DRAM. Meanwhile, CoWoS capacity itself faces high technical barriers and equipment constraints, meaning AI chip shipments are limited by advanced packaging capacity. As a result, the HBM supply shortage may persist through 2027–2028. Even as the industry explores methods to reduce memory requirements—such as improved caching mechanisms and new data compression techniques—high-bandwidth memory remains irreplaceable for top-tier AI computing.
Looking ahead, packaging technologies will continue to evolve toward higher levels of integration. Following CoWoS-S, CoWoS-R, and CoWoS-L, hybrid bonding is widely viewed as the next key breakthrough. With finer interconnect pitch and higher I/O density, hybrid bonding brings memory and logic chips closer to “chip-level” interconnection. This advancement not only reduces power consumption but also significantly boosts overall system performance, paving the way for the next generation of AI computing.
Within this industry trend, HBM is not only a core component of high-performance computing but also one of the most challenging memory types in terms of yield and reliability. Its stacked structure and advanced packaging significantly increase testing and repair complexity. Ensuring memory quality and long-term reliability before shipment has become a critical competitive factor. iSTART-TEK has long been dedicated to memory testing and repair technologies and holds ISO 26262 TCL1-certified automotive-grade test algorithms and repair solutions, helping chips maintain high yield and reliability under advanced packaging and high-bandwidth architectures, and serving as a key enabler of memory quality assurance in the AI era.