- Research Article
7
- 10.1109/tcpmt.2024.3474716
Design Guidelines for 2.5-D Packages Featuring Organic Interposer With Bridges Embedded
- Nov 01, 2024
- IEEE Transactions on Components, Packaging and Manufacturing Technology
- Yangyang Lai + 2 more +2
The rapid advancement of artificial intelligence (AI) has propelled the demand for high-performance computing (HPC) systems capable of handling vast amounts of data. This necessitates improvements in data processing speed within system-on-chip (SoC) units and efficient data transmission between SoC and high-bandwidth memory (HBM). Advanced packaging solutions, particularly the silicon interposer and organic interposer, have emerged to address these challenges. This article delves into the thermo-mechanical performance of 2.5-D packages with an organic interposer, focusing on warpage management during fabrication and stress analysis induced by coefficient of thermal expansion (CTE) mismatches. The study employs finite element analysis (FEA) modeling to evaluate the impact of various factors on warpage behavior and stress levels. Parametric studies on material selection and interposer geometric design reveal crucial insights. Specifically, reducing bridge die and redistribution layer (RDL) thickness mitigates warpage at the controlled collapse chip connection (C4) level, albeit with adverse effects on BGA level warpage. Material selection significantly influences warpage behavior. Organic materials with higher CTE reduce the mismatch between the interposer and the substrate but it is adverse for the interconnection between chiplets and interposer. Moreover, stress analysis indicates the organic interposer’s effectiveness in reducing interconnection stress compared to silicon interposers. This research contributes valuable insights into the design and optimization of advanced packages with bridges embedded in organic interposers, providing guidelines for material selection and geometric design to enhance reliability and functionality. The findings facilitate the development of advanced packaging solutions capable of meeting the demands of AI-driven applications in challenging operational environments.
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