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Main Authors: Zhu, Tianxiang, Wang, Qipan, Lin, Yibo, Wang, Runsheng, Huang, Ru
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2411.12690
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author Zhu, Tianxiang
Wang, Qipan
Lin, Yibo
Wang, Runsheng
Huang, Ru
author_facet Zhu, Tianxiang
Wang, Qipan
Lin, Yibo
Wang, Runsheng
Huang, Ru
contents Thermomechanical stress induced by through-silicon vias (TSVs) plays an important role in the performance and reliability analysis of 2.5D/3D ICs. While the finite element method (FEM) adopted by commercial software can provide accurate simulation results, it is very time- and memory-consuming for large-scale analysis. Over the past decade, the linear superposition method has been utilized to perform fast thermal stress estimations of TSV arrays, but it suffers from a lack of accuracy. In this paper, we propose MORE-Stress, a novel strict numerical algorithm for efficient thermal stress simulation of TSV arrays based on model order reduction. Extensive experimental results demonstrate that our algorithm can realize a 153-504 times reduction in computational time and a 39-115 times reduction in memory usage compared with the commercial software ANSYS, with negligible errors less than 1%. Our algorithm is as efficient as the linear superposition method, with an order of magnitude smaller errors and fast convergence.
format Preprint
id arxiv_https___arxiv_org_abs_2411_12690
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle MORE-Stress: Model Order Reduction based Efficient Numerical Algorithm for Thermal Stress Simulation of TSV Arrays in 2.5D/3D IC
Zhu, Tianxiang
Wang, Qipan
Lin, Yibo
Wang, Runsheng
Huang, Ru
Computational Engineering, Finance, and Science
Thermomechanical stress induced by through-silicon vias (TSVs) plays an important role in the performance and reliability analysis of 2.5D/3D ICs. While the finite element method (FEM) adopted by commercial software can provide accurate simulation results, it is very time- and memory-consuming for large-scale analysis. Over the past decade, the linear superposition method has been utilized to perform fast thermal stress estimations of TSV arrays, but it suffers from a lack of accuracy. In this paper, we propose MORE-Stress, a novel strict numerical algorithm for efficient thermal stress simulation of TSV arrays based on model order reduction. Extensive experimental results demonstrate that our algorithm can realize a 153-504 times reduction in computational time and a 39-115 times reduction in memory usage compared with the commercial software ANSYS, with negligible errors less than 1%. Our algorithm is as efficient as the linear superposition method, with an order of magnitude smaller errors and fast convergence.
title MORE-Stress: Model Order Reduction based Efficient Numerical Algorithm for Thermal Stress Simulation of TSV Arrays in 2.5D/3D IC
topic Computational Engineering, Finance, and Science
url https://arxiv.org/abs/2411.12690