Enhancing a Layout-Aware Synthesis Methodology for Analog ICs by Embedding Statistical Knowledge into the Evolutionary Optimization Kernel - Technological Innovation for the Internet of Things Access content directly
Conference Papers Year : 2013

Enhancing a Layout-Aware Synthesis Methodology for Analog ICs by Embedding Statistical Knowledge into the Evolutionary Optimization Kernel

Frederico Rocha
  • Function : Author
  • PersonId : 986728
Ricardo Martins
  • Function : Author
  • PersonId : 986729
Nuno Lourenço
  • Function : Author
  • PersonId : 986730
Nuno Horta
  • Function : Author
  • PersonId : 986731

Abstract

This paper applies to the scientific area of electronic design automation (EDA) and addresses the automatic sizing of analog integrated circuits (ICs). Particularly, this work presents an innovative approach to enhance a state-of-the-art layout-aware circuit-level optimizer (GENOM-POF), by embedding statistical knowledge from an automatically generated gradient model into the multi-objective multi-constraint optimization kernel based on the NSGA-II algorithm. The approach was validated with typical analog circuit structures, using the UMC 0.13 μm integration technology, showing that, by enhancing the circuit sizing optimization kernel with the gradient model, the optimal solutions are achieved, considerably, faster and with identical or superior accuracy. Finally, the results are Pareto Optimal Fronts (POFs), which consist of a set of fully compliant sizing solutions, allowing the designer to explore the different trade-offs of the solution space, both through the achieved device sizes, or the respective layout solutions.
Fichier principal
Vignette du fichier
978-3-642-37291-9_57_Chapter.pdf (4 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01348799 , version 1 (25-07-2016)

Licence

Attribution

Identifiers

Cite

Frederico Rocha, Ricardo Martins, Nuno Lourenço, Nuno Horta. Enhancing a Layout-Aware Synthesis Methodology for Analog ICs by Embedding Statistical Knowledge into the Evolutionary Optimization Kernel. 4th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Apr 2013, Costa de Caparica, Portugal. pp.531-538, ⟨10.1007/978-3-642-37291-9_57⟩. ⟨hal-01348799⟩
28 View
68 Download

Altmetric

Share

Gmail Facebook X LinkedIn More