Name
Title | ||
|---|---|---|
A new metaheuristc combining gradient models with NSGA-II to enhance analog IC synthesis. |
Abstract | ||
|---|---|---|
This paper presents a new approach to enhance a state-of-the-art layout-aware analog IC circuit-level optimizer, by embedding statistical knowledge from an automatically generated gradient model into the multi-objective multi-constraint optimization kernel based on a modified NSGA-II algorithm. The gradient model is automatically generated by, first, using a design of experiments (DOE) approach with two alternative sampling strategies, the full factorial design and the fractional factorial design, which define the samples that will be accurately evaluated using a circuit simulator (e.g. HSPICE (R)), second, extracting and ranking the contributions of each design variable to each performance measure or objective, and, finally, building the model based on series of gradient rules. The gradient model is then embedded into the modified NSGA-II optimization kernel, by acting on the mutation operator. The approach was validated with typical analog circuit structures for an industry standard 0.13 mu m integration process, showing that, by enhancing the circuit sizing evolutionary kernel with the gradient model, the optimal solutions are achieved, considerably, faster and with identical or superior accuracy. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/CEC.2013.6557906 | IEEE Congress on Evolutionary Computation |
Keywords | Field | DocType |
analogue integrated circuits,design of experiments,gradient methods,integrated circuit design,integrated circuit layout,integrated circuit modelling,optimisation,DOE approach,analog IC synthesis,analog circuit structures,circuit simulator,circuit sizing evolutionary kernel enhancement,design of experiment approach,fractional factorial design,industry standard integration process,layout-aware analog IC circuit-level optimizer,metaheuristc combining gradient models,modified NSGA-II optimization kernel,multiobjective multiconstraint optimization kernel,mutation operator,optimal solutions,sampling strategies,statistical knowledge,Analog Integrated Circuit Sizing,Electronic Design Automation,Evolutionary Computation,Gradient Model,Multi-Objective Multi-Constraint Optimization | Integrated circuit layout,Fractional factorial design,Kernel (linear algebra),Mathematical optimization,Computer science,Circuit extraction,Integrated circuit design,Artificial intelligence,Physical design,Electronic circuit simulation,Machine learning,Design of experiments | Conference |
Citations | PageRank | References |
1 | 0.35 | 6 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Frederico Rocha | 1 | 1 | 0.69 |
| Nuno C. Lourenço | 2 | 122 | 18.24 |
| Ricardo Povoa | 3 | 53 | 10.57 |
| Ricardo Martins | 4 | 179 | 20.81 |
| Nuno Cavaco Horta | 5 | 310 | 49.65 |