In analog integrated circuit design, iterations between electrical and physical syntheses to counterbalance layout-induced performance degradations should be avoided as much as possible. One possible solution involves the integration of traditionally separated electrical and physical synthesis phases by including layout-induced effects right into the electrical synthesis phase in what has been called parasitic-aware synthesis. This solution, as such, is not yet complete since there are geometric requirements (minimization of area or fulfillment of certain layout aspect ratio, among others) whose effects on the resulting parasitics are not usually considered during the electrical synthesis. In this paper, a layout-aware solution for analog cells that tackles both geometric and parasitic-aware electrical synthesis is proposed. Several design examples are provided.

In this paper, a new methodology for the automated generation of the optimal performance trade-offs of integrated inductors is presented. The methodology combines a multiobjective optimization algorithm with electromagnetic simulation to get highly accurate results. A set of sized inductors is obtained showing the best performance trade-offs for a given technology. Unlike reported approaches for inductor synthesis, performance trade-offs are generated offline, i.e., before any specific inductance or quality factor are required. The tight efficiency versus accuracy trade-off of existing approaches is, in this way, avoided and performance evaluation via electromagnetic simulation becomes affordable.

This article introduces an evolution-based methodology, named memetic single-objective evolutionary algorithm (MSOEA), for automated sizing of high-performance analog integrated circuits. Memetic algorithms may achieve higher global and local search ability by properly combining operators from different standard evolutionary algorithms. By integrating operators from the differential evolution algorithm, from the real-coded genetic algorithm, operators inspired by the simulated annealing algorithm, and a set of constraint handling techniques, MSOEA specializes in handling analog circuit design problems with numerous and tight design constraints. The method has been tested through the sizing of several analog circuits. The results show that design specifications are met and objective functions are highly optimized. Comparisons with available methods like genetic algorithm and differential evolution in conjunction with static penalty functions, as well as with intelligent selection-based differential evolution, are also carried out, showing that the proposed algorithm has important advantages in terms of constraint handling ability and optimization quality.

In this paper, an analysis of the methodologies proposed in the past years to automate the synthesis of radio-frequency (RF) integrated circuit blocks is presented. In the light of this analysis, and to avoid non-systematic iterations between sizing and layout design steps, a multi-objective optimization-based layout-aware sizing approach with pre-optimized integrated inductor(s) design space is proposed. An automatic layout generation from netlist to ready-to-fabricate prototype is carried in-the-loop for each tentative sizing solution using an RF-specific module generator, template-based placer and evolutionary multi-net router with pre-optimized interconnect widths. The proposed approach exploits the full capabilities of the most established computer-aided design tools for RF design available nowadays, i.e., RF circuit simulator as performance evaluator, electromagnetic simulator for inductor characterization, and layout extractor to determine the complete circuit layout parasitics. Experiments are conducted over a widely-used circuit in the RF context, showing the advantages of performing complete layout-aware sizing optimization from the very initial stages of the design process.

In recent years there has been a growing interest in electronic design automation methodologies for the optimizationbased design of radiofrequency circuits and systems. While for simple circuits several successful methodologies have been proposed, these very same methodologies exhibit significant deficiencies when the complexity of the circuit is increased. The majority of the published methodologies that can tackle radiofrequency systems are either based on high-level system specification tools or use models to estimate the system performances. Hence, such approaches do not usually provide the desired accuracy for RF systems. In this work, a methodology based on hierarchical multilevel bottom-up design approaches is presented, where multi-objective optimization algorithms are used to design an entire radiofrequency system from the passive component level up to the system level. Furthermore, each level of the hierarchy is simulated with the highest accuracy possible: electromagnetic simulation accuracy at device-level and electrical simulations at circuit/system-level.