Multiport PDN Optimization with the Newton-Hessian Minimization Method
Abstract
This article proposes an optimization algorithm using the Hessian minimization method, based on the Newton iteration, to evaluate the effectiveness of the placement of multiple decoupling capacitors on a power/ground plane pair. The exact effective decoupling regions are obtained using the Newton iteration method for each decoupling capacitor. The impedance of the IC port is lower than the target impedance no matter where the decoupling capacitor is placed in this region. To optimize specific capacitor placements in this region, the Newton iteration, based on the Hessian matrix, is used to determine the location where the impedance of the IC port is minimized at the antiresonant frequency of the plane pair. This placement optimization algorithm allows for a decoupling design method that can also be applied to a PDN with multiple decoupling capacitors for multiple IC ports. Compared with the method of random selection from within the effective decoupling area, the method proposed here requires fewer decoupling capacitors and less computational time.
Recommended Citation
J. Wang et al., "Multiport PDN Optimization with the Newton-Hessian Minimization Method," IEEE Transactions on Microwave Theory and Techniques, vol. 69, no. 4, pp. 2098 - 2109, article no. 9359545, Institute of Electrical and Electronics Engineers (IEEE), Apr 2021.
The definitive version is available at https://doi.org/10.1109/TMTT.2021.3057236
Department(s)
Electrical and Computer Engineering
Research Center/Lab(s)
Electromagnetic Compatibility (EMC) Laboratory
Keywords and Phrases
Decoupling Capacitor; Hessian Matrix; Newton Iteration Method; Power Integrity (PI); Power Supply Network
International Standard Serial Number (ISSN)
1557-9670; 0018-9480
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2021 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Apr 2021
Comments
National Science Foundation, Grant IIP-1916535