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Decoupling Capacitor Insertion Minimizing IR-Drop Violations and Routing DRVs

Published: 31 January 2023 Publication History

Abstract

Decoupling capacitor (decap) cells are inserted near function cells of high switching activities so that their IR-drop can be suppressed. Their design becomes more complex and uses higher metal layers, thereby starting to manifest themselves as routing blockage. Post-placement decap insertion, with a goal of minimizing both IR-drop violations and routing design rule violations (DRVs), is addressed for the first time. U-Net with graph convolutional network is introduced to predict routing DRV penalty. The decap insertion problem is formulated and a heuristic algorithm is presented. Experiments with a few test circuits demonstrate that DRVs are reduced by 16% on average with no IR-drop violations, compared to a conventional method which does not explicitly consider DRVs. This results in 48% reduction in routing runtime and 23% improvement in total negative slack.

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Cited By

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  • (2023)CircuitNet: An Open-Source Dataset for Machine Learning in VLSI CAD Applications With Improved Domain-Specific Evaluation Metric and Learning StrategiesIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2023.328797042:12(5034-5047)Online publication date: Dec-2023
  • (2023)Power Distribution Network Optimization Using HLA-GCN for Routability Enhancement2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD)10.1109/ICCAD57390.2023.10323833(1-8)Online publication date: 28-Oct-2023

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cover image ACM Conferences
ASPDAC '23: Proceedings of the 28th Asia and South Pacific Design Automation Conference
January 2023
807 pages
ISBN:9781450397834
DOI:10.1145/3566097
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 31 January 2023

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Author Tags

  1. decoupling capacitor
  2. design rule violation
  3. dynamic IR-drop
  4. machine learning

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  • Research-article

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  • This work was supported in part by the Institute of Information and communications Technology Planning and Evaluation (IITP) grant funded by the Korea Government (MSIT) through Software Systems for AI Semiconductor Design under Grant 2021-0-00754, and in part by Synopsys. The EDA tool was supported by the IC Design Education Center (IDEC), Korea.

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ASPDAC '23 Paper Acceptance Rate 102 of 328 submissions, 31%;
Overall Acceptance Rate 466 of 1,454 submissions, 32%

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Cited By

View all
  • (2023)CircuitNet: An Open-Source Dataset for Machine Learning in VLSI CAD Applications With Improved Domain-Specific Evaluation Metric and Learning StrategiesIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2023.328797042:12(5034-5047)Online publication date: Dec-2023
  • (2023)Power Distribution Network Optimization Using HLA-GCN for Routability Enhancement2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD)10.1109/ICCAD57390.2023.10323833(1-8)Online publication date: 28-Oct-2023

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