Power supply noise analysis methodology for deep-submicron VLSI chip design
DAC '97 Proceedings of the 34th annual Design Automation Conference
IC power distribution challenges
Proceedings of the 2001 IEEE/ACM international conference on Computer-aided design
Power network analysis using an adaptive algebraic multigrid approach
Proceedings of the 40th annual Design Automation Conference
Power grid reduction based on algebraic multigrid principles
Proceedings of the 40th annual Design Automation Conference
A fast decoupling capacitor budgeting algorithm for robust on-chip power delivery
Proceedings of the 2004 Asia and South Pacific Design Automation Conference
Fast Decap Allocation Algorithm For Robust On-Chip Power Delivery
ISQED '05 Proceedings of the 6th International Symposium on Quality of Electronic Design
Partitioning-based approach to fast on-chip decap budgeting and minimization
Proceedings of the 42nd annual Design Automation Conference
An Improved AMG-based Method for Fast Power Grid Analysis
ISQED '06 Proceedings of the 7th International Symposium on Quality Electronic Design
Power Distribution Network Design for VLSI
Power Distribution Network Design for VLSI
Decoupling capacitance allocation and its application to power-supply noise-aware floorplanning
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
A multigrid-like technique for power grid analysis
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Optimal decoupling capacitor sizing and placement for standard-cell layout designs
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
On-chip power-supply network optimization using multigrid-based technique
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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Decap (decoupling capacitor) is an effective technique for suppressing power supply noise. Nevertheless, over-usage of decap usually causes excessive power dissipation. Therefore, the total decap area needs to be minimized subject to power supply noise constraints. This is a complicated nonlinear optimization problem that may have as many as millions of variables. We propose an algebraic multigrid (AMG) based method to handle the high complexity. An error compensation scheme is developed to compensate the accuracy loss during the AMG reduction. A charge based back-mapping method and a few other techniques are suggested to further improve the computation efficiency. Our method is flexible to use and can be easily integrated with other existing decap allocation works. When compared to several previous works, the results from our method are usually the closest to the optimum. Our method also runs fast and can solve circuits with up to 1 million nodes in about 11 minutes. In addition, it has better scalability than the previous works.