System-Level Thermal Validation of 2.5D Packages in GPU Servers: TCB vs. HCB HBM Platforms

This study investigates the thermal scalability and long-term reliability of 2.5D System-in- Package (SiP) platforms, focusing on the critical impact of HBM integration on concentrated heat profiles. By implementing thermal test vehicles (TTVs) within an Open Compute Project (OCP)-standard GPU server equipped with embedded sensors and controllable heaters, the research provides a comparative analysis between Hybrid Copper Bonding (HCB) and Thermo-Compression Bonding (TCB). Experimental results show that HCB significantly enhances thermal conduction and reduces both intra- and inter-package thermal crosstalk, with a 9.8% reduction in crosstalk under liquid cooling conditions at 1030 W per package. From a data-center operational perspective, the adoption of HCB allows for a 0.9°C increase in the allowable coolant inlet temperature, leading to a 3% reduction in cooling power and an improvement in Power Usage Effectiveness (PUE) from 1.26 to 1.24. For a large-scale AI cluster of 1,000 racks, this efficiency gain translates to approximately 31 GWh in annual energy savings. This study indicates that as AI infrastructure evolves toward inference-heavy workloads with increased HBM base-die power, HCB platforms will provide progressively greater thermal advantages. This work establishes a robust methodology for system-level thermal validation and demonstrates that HBM bonding selection is a pivotal factor in achieving data-center efficiency and future hardware scalability.