Design-Aware Full-Chip Warpage Modeling for STCO: Bridging Reliability and Design for a New Era of Advanced Systems

A novel design-aware warpage modeling methodology overcomes formidable computational barriers in full-chip layout simulation. By integrating representative volume element (RVE) analysis with AI-driven pattern clustering, this method enables efficient finite element method (FEM) simulations while capturing intricate BEOL design impacts. Validated by strong agreement with measured chip warpage across diverse temperatures conditions, the model reveals how mechanical property distributions drive warpage behavior. Demonstrated in system-technology co-optimization (STCO) for high bandwidth memory (HBM), it supports micro-bump (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mu$</tex>bump) and power delivery network (PDN) designs, achieving up to 13% warpage reduction without sacrificing performance. This scalable solution provides critical insights into balancing mechanical reliability and performance, paving the way for advanced semiconductor systems.

Authors

Institutions

Publication Details

Published
2025-06-08
DOI
https://doi.org/10.23919/vlsitechnologyandcir65189.2025.11074937
Primary Topic
Advancements in Photolithography Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Design-Aware Full-Chip Warpage Modeling for STCO: Bridging Reliability and Design for a New Era of Advanced Systems

S.E. Kim, Dae Sin Kim, Min‐Chul Park, In Young Huh et al.
Advancements in Photolithography Techniques
article

Design-Aware Full-Chip Warpage Modeling for STCO: Bridging Reliability and Design for a New Era of Advanced Systems

S.E. Kim, Dae Sin Kim, Min‐Chul Park, In Young Huh, Sanghoon Myung, Youngjoo Lee, Young-Gu Kim, Jihye Lee, Sung Jin Kim, Na-Rae Jeong, Hyunjae Jang, Boo Soo
article en

Abstract

A novel design-aware warpage modeling methodology overcomes formidable computational barriers in full-chip layout simulation. By integrating representative volume element (RVE) analysis with AI-driven pattern clustering, this method enables efficient finite element method (FEM) simulations while capturing intricate BEOL design impacts. Validated by strong agreement with measured chip warpage across diverse temperatures conditions, the model reveals how mechanical property distributions drive warpage behavior. Demonstrated in system-technology co-optimization (STCO) for high bandwidth memory (HBM), it supports micro-bump (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mu$</tex>bump) and power delivery network (PDN) designs, achieving up to 13% warpage reduction without sacrificing performance. This scalable solution provides critical insights into balancing mechanical reliability and performance, paving the way for advanced semiconductor systems.

Samsung (South Korea) (KR)
Industry, innovation and infrastructure
Openalex Percentile: Top 82%
Advancements in Photolithography Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.