Proceedings ArticleDOI
Optimal Design of a Decoupling Network Using Variants of Particle Swarm Optimization Algorithm
Surendra Hemaram,Jai Narayan Tripathi +1 more
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TLDR
In this paper, a practical case study is presented, where, in order to design an efficient PDN, the cumulative impedance of the PDN is optimized below the target impedance.Abstract:
This paper discusses a discrete optimization problem of optimal design of Power Delivery Networks (PDN) in VLSI systems. In this paper, a practical case study is presented, where, in order to design an efficient PDN, the cumulative impedance of the PDN is optimized below the target impedance. For this purpose, the decoupling capacitors (from commercially available capacitors) are chosen in such a way that the minimum number of the capacitors are used, and also their optimal locations are identified. The different variants of inertia weight strategies incorporated into particle swarm optimization algorithms are used for this purpose. A comparative analysis of the performance of these algorithms is also presented.read more
Citations
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Journal ArticleDOI
MCB-DPO: Multiport Constrained Barrier Method-Based Decoupling Capacitor Placement Optimization on Irregularly Shaped Planes
Ihsan Erdin,Ramachandra Achar +1 more
TL;DR: In this article , a multi-port constrained optimization methodology is presented for the optimal placement of decoupling capacitors in power distribution networks (PDNs) of printed circuit boards (PCBs).
Journal ArticleDOI
Trade-Off-Oriented Impedance Optimization of Chiplet-Based 2.5-D Integrated Circuits With a Hybrid MDP Algorithm for Noise Elimination
TL;DR: In this article , a new hybrid metaheuristic algorithm named Metropolis-based differential particle swarm optimization (MDP) is designed to jointly optimize the multiconstraints and impedance-based hybrid objective function of chiplet-based 2.5D integrated circuit (IC) designs.
Journal ArticleDOI
Trade-Off-Oriented Impedance Optimization of Chiplet-Based 2.5-D Integrated Circuits With a Hybrid MDP Algorithm for Noise Elimination
TL;DR: In this paper , a new hybrid metaheuristic algorithm named Metropolis-based differential particle swarm optimization (MDP) is designed to jointly optimize the multiconstraints and impedance-based hybrid objective function of chiplet-based 2.5D integrated circuit (IC) designs.
A Radial Basis Function Network-Based Surrogate-Assisted Swarm Intelligence Approach for Fast Optimization of Power Delivery Networks
TL;DR: In this paper , a novel approach using surrogate-assisted swarm intelligence is presented for efficient and fast optimization of power delivery networks (PDNs) in very large scale integration systems are becoming very challenging with the increasing complexity of such systems.
Large-Scale Optimization of Decoupling Capacitors Using Adaptive Region Based Encoding Scheme in Particle Swarm Optimization
TL;DR: In this article , a novel approach using the Social-Learning Particle Swarm Optimization (SLPSO) technique along with Adaptive Region Search (ARS) is used to tackle the Large-Scale Optimization Problem (LSOP) of decoupling capacitor placement.
References
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Journal ArticleDOI
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Proceedings ArticleDOI
A modified particle swarm optimizer
Yuhui Shi,Russell C. Eberhart +1 more
TL;DR: A new parameter, called inertia weight, is introduced into the original particle swarm optimizer, which resembles a school of flying birds since it adjusts its flying according to its own flying experience and its companions' flying experience.
Journal ArticleDOI
Differential Evolution: A Survey of the State-of-the-Art
TL;DR: A detailed review of the basic concepts of DE and a survey of its major variants, its application to multiobjective, constrained, large scale, and uncertain optimization problems, and the theoretical studies conducted on DE so far are presented.
Proceedings ArticleDOI
Particle swarm optimization: developments, applications and resources
TL;DR: Developments in the particle swarm algorithm since its origin in 1995 are reviewed and brief discussions of constriction factors, inertia weights, and tracking dynamic systems are included.
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