Sun, J. orcid.org/0009-0007-0540-7482, Zha, X. orcid.org/0000-0002-4616-2334, Wang, C. orcid.org/0009-0000-1248-889X et al. (4 more authors) (2024) Pseudo adjoint optimization: harnessing the solution curve for SPICE acceleration. In: Xiong, J. and Wille, R., (eds.) ICCAD '24: Proceedings of the 43rd IEEE/ACM International Conference on Computer-Aided Design. ICCAD '24: 43rd IEEE/ACM International Conference on Computer-Aided Design, 27-31 Oct 2024, New York, USA. ACM ISBN 9798400710773
Abstract
Pseudo transient analysis (PTA) has been a promising solution for direct current (DC) analysis of transistor-level circuit simulation. Despite its popularity, PTA requires meticulous hyperparameter tuning for optimal performance. In this paper, we propose pseudo adjoint optimization, Soda-PTA, which models the PTA solution curve (which is used to measure convergence) using a neural ordinary differential equation (Neural ODE) and deriving explicit gradients of the Newton-Raphson (NR) iteration w.r.t. the PTA hyperparameters through the classic adjoint method, enabling effective optimization of the PTA hyperparameters. To generalize Soda-PTA for unseen circuits, we further introduce a graph convolution network to transfer optimal PTA hyperparameters from the other circuits to the target one. Soda-PTA is implemented in an out-of-the-box SPICE simulator. Through extensive experiments, Soda-PTA demonstrates superior acceleration performance: an average speedup of 1.53x over the state-of-the-art BoA-PTA while ensuring superior convergence and up to 22.12x speedup compared to the native PTA solver.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2025 The Authors. Except as otherwise noted, this author-accepted version of a paper published in ICCAD '24: Proceedings of the 43rd IEEE/ACM International Conference on Computer-Aided Design is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ |
Keywords: | circuit simulation; nonlinear DC analysis; pseudo transient analysis; neural ODE; graph convolution network |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > School of Mathematical and Physical Sciences |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 29 May 2025 12:11 |
Last Modified: | 29 May 2025 12:11 |
Status: | Published |
Publisher: | ACM |
Refereed: | Yes |
Identification Number: | 10.1145/3676536.3676789 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:227184 |