Modeling and analysis of package PDN for computing system based on cavity model
Recent computing systems consume more than several hundred watts of power and a robust PDN design is critical to minimize power/ground (P/G) voltage fluctuation and get stable performance. In most cases, the IC package (PKG) PDN determines mid-frequency P/G noise characteristics. The PDN of our targ...
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Published in: | 2017 IEEE International Symposium on Electromagnetic Compatibility & Signal/Power Integrity (EMCSI) pp. 213 - 218 |
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Main Authors: | , , , , , , , , |
Format: | Conference Proceeding |
Language: | English |
Published: |
IEEE
01-08-2017
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Subjects: | |
Online Access: | Get full text |
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Summary: | Recent computing systems consume more than several hundred watts of power and a robust PDN design is critical to minimize power/ground (P/G) voltage fluctuation and get stable performance. In most cases, the IC package (PKG) PDN determines mid-frequency P/G noise characteristics. The PDN of our target IC package consists of more than ten thousands staggered microvias and tens of layers, representing a significant modeling challenge. Commercial tools can estimate the PKG PDN impedance via full-wave simulations, but it has several limitations at pre-layout stage. Whole simulation should be run for every small geometry changes and it takes much time. It can give circuit model seen at port, but does not provide physics-based circuit models corresponding to whole current path. In this paper we apply the cavity model, which has been previously largely used for PCB modeling, to a complex organic package structure. We here describe the assumptions used to get an equivalent circuit model for this type of geometry and the comparison of its loop inductances with commercial tools. The cavity model gives about 10 % error compared to commercial tool and the reason of error is analyzed. In addition, a study of the PKG decoupling capacitors location is performed with the goal of a minimal loop inductance. In the final paragraph, several unique features of the PKG PDN compared to PCB PDN modeling are described. |
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ISBN: | 9781538622292 1538622297 |
ISSN: | 2158-1118 |
DOI: | 10.1109/ISEMC.2017.8077869 |