Found results matching for:
Author: Fabio Moreira de Passos
Year: Since 2002
Journal Papers
PACOSYT: A Passive Component Synthesis Tool based on Machine Learning and Tailored Modeling Strategies Towards Optimal RF and mm-Wave Circuit Designs
F. Passos, N. Lourenço, E. Roca, R. Martins, R. Castro-López, N. Horta and F.V. Fernández
Journal Paper · IEEE Journal of Microwaves, first online, 2023
abstract
doi
In this paper, the application of regression-based supervised machine learning (ML) methods to the modeling of integrated inductors and transformers is examined. Different ML techniques are used and compared to improve accuracy. However, it is demonstrated that none of the ML techniques considered provided good results unless a smart modeling strategy, tailored to the specific design problem, is used. Taking advantage of these modeling strategies, high accuracy can be obtained when compared to full-wave electromagnetic (EM) simulations (less than 2% error) and experimental measurements (less than 5% error). The most accurate model, obtained by the appropriate combination of an ML technique and modeling strategy, has been integrated into a tool called PACOSYT. The tool uses optimization algorithms to allow the designer to obtain an inductor/transformer with optimal performances in just seconds while keeping the accuracy of EM simulations. Furthermore, the tool provides the passive component S parameter description file for seamless use in circuit simulations. The tool can be used standalone or integrated with design frameworks, like Cadence Virtuoso or AIDASoft, a framework for circuit optimization. To illustrate the different usages of the tool, several passive devices are synthesized, and hundreds of millimeter-wave power amplifiers are synthesized using AIDASoft together with PACOSYT. The tool has been developed using open-source Python frameworks and does not use any closed-source licenses. PACOSYT, which also allows other designers to create their models for different technologies, is made publicly available.
Addressing a New Class of Multi-Objective Passive Device Optimization for Radiofrequency Circuit Design
F. Passos, E. Roca, R. Castro-López and F.V. Fernández
Journal Paper · Electronics, vol. 11, no. 16, article 2624, 2022
abstract
doi
The design of radiofrequency circuits and systems lends itself to multi-objective optimization and the bottom-up composition of Pareto-optimal fronts. Conventional multi-objective optimization algorithms can effectively attain these fronts, which maximize or minimize a set of competing objective functions of interest. However, some of these real-life optimization problems reveal a non-conventional feature: there is one objective function that calls neither for minimization nor maximization. Instead, using the Pareto front demands this objective function to be swept across so that all its feasible values are available. Such a non-conventional feature, as shown here, emerges in the case of inductor optimization. The problem thus turns into a non-conventional one: determining how to find uniformly distributed feasible values of this function over the broadest possible range (typically unknown) while minimizing or maximizing the remaining competing objective functions. An NSGA-II-inspired algorithm is proposed that, based on the dynamic allocation of objective function slots and a modified dominance definition, can successfully return sets of solutions for inductor optimization problems with one sweeping objective. Furthermore, a mathematical benchmark function modeling this kind of problem is presented, which is also used to exhaustively test the proposed algorithm and obtain insight into its parameter settings.
Hierarchical Yield-Aware Synthesis Methodology Covering Device-, Circuit-, and System-Level for Radiofrequency ICs
A. Canelas, F. Passos, N. Lourenço, R. Martins, E. Roca, R. Castro-Lopez, N. Horta and F.V. Fernandez
Journal Paper · IEEE Access, vol. 9, pp 124152-124164, 2021
abstract
doi pdf
This paper presents an innovative yield-aware synthesis strategy based on a hierarchical bottom-up methodology that uses a multiobjective evolutionary optimization algorithm to design a complete radiofrequency integrated circuit from the passive component level up to the system level. Within it, performances’ calculation aims for the highest possible accuracy. A surrogate model calculates the performances for the inductive devices, with accuracy comparable to full electromagnetic simulation; and, an electrical simulator calculates circuit- and system-level performances. Yield is calculated using Monte-Carlo (MC) analysis with the foundry-provided models without any model approximation. The computation of the circuit yield throughout the hierarchy is estimated employing parallelism and reducing the number of simulations by performing MC analysis only to a reduced number of candidate solutions, alleviating the computational requirements during the optimization. The yield of the elements not accurately evaluated is assigned using their degree of similitude to the simulated solutions. The result is a novel synthesis methodology that reduces the total optimization time compared to a complete MC yield-aware optimization. Ultimately, the methodology proposed in this work is compared against other methodologies that do not consider yield throughout the system’s complete hierarchy, demonstrating that it is necessary to consider it over the entire hierarchy to achieve robust optimal designs.
An efficient transformer modeling approach for mm-wave circuit design
F. Passos, E. Roca, J. Sieiro, R. Castro-Lopez and F.V. Fernandez
Journal Paper · AEU - International Journal of Electronics and Communications, vol. 128, article 153496, 2021
abstract
doi pdf
In this paper, a Gaussian-process surrogate modeling methodology is used to accurately and efficiently model transformers, which are still a bottleneck in radio-frequency and millimeter-wave circuit design. The proposed model is useful for a wide range of frequencies from DC up to the millimeter-wave range (over 100 GHz). The technique is statistically validated against full-wave electromagnetic simulations. The efficient model evaluation enables its exploitation in iterative user-driven design approaches, as well as automated design exploration involving thousands of simulations. As experimental results, the model is used in several scenarios, such as the design of an inter-stage amplifier operating at 60 GHz, where the model assisted in the simulation of the transformers and baluns used, and the design of individual transformers and a matching network.
Synthesis of mm-Wave Wideband Receivers in 28nm CMOS Technology for Automotive Radar Applications
F. Passos, M. Chanca, E. Roca, R. Castro-López and F.V. Fernández
Journal Paper · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 39, no. 12, pp 4375-4384, 2020
abstract
doi pdf
A new strategy for millimeter-wave circuit and system synthesis, where the accuracy of electromagnetic simulations can be achieved in optimization-based design methodologies without sacrificing efficiency, is presented and tested within a real industrial project. This is done by properly partitioning the system, generating libraries of passive devices which are electromagnetically simulated prior to any circuit optimization, generating performance trade-offs at different hierarchical levels with multi-objective optimization algorithms and hierarchically composing lower level sub-blocks. With this proposed solution, an entire millimeter-wave system, from the passive component level up to the system level, has been designed and compared with the results obtained from a conventional design approach, demonstrating the outstanding capabilities of the methodology.
Ready-to-Fabricate RF Circuit Synthesis using a Layout- and Variability-Aware Optimization-based Methodology
F. Passos, E. Roca, R. Martins, N. Lourenço, S. Ahyoune, J. Sieiro, R. Castro-Lopez, N. Horta and F.V. Fernandez
Journal Paper · IEEE Access, vol. 8, pp. 51601-51609, 2020
abstract
doi pdf
In this paper, physical implementations and measurement results are presented for several Voltage Controlled Oscillators that were designed using a fully-automated, layout-and variability-aware optimization-based methodology. The methodology uses a highly accurate model, based on machine-learning techniques, to characterize inductors, and a multi-objective optimization algorithm to achieve a Pareto-optimal front containing optimal circuit designs offering different performance trade-offs. The final outcome of the proposed methodology is a set of design solutions (with their GDSII description available and ready-to-fabricate) that need no further designer intervention. Two key elements of the proposed methodology are the use of an optimization algorithm linked to an off-the-shelf simulator and an inductor model that yield EM-like accuracy but with much shorter evaluation times. Furthermore, the methodology guarantees the same high level of robustness against layout parasitics and variability that an expert designer would achieve with the verification tools at his/her disposal. The methodology is technology-independent and can be used for the design of radio frequency circuits. The results are validated with experimental measurements on a physical prototype.
A Multilevel Bottom-up Optimization Methodology for the Automated Synthesis of RF Systems
F. Passos, E. Roca, J. Sieiro, R. Fiorelli, R. Castro-López, J.M. López-Villegas and F.V. Fernández
Journal Paper · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 39, no. 3, pp 560-571, 2020
abstract
doi pdf
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.
Two-Step RF IC Block Synthesis with Preoptimized Inductors and Full Layout Generation In-the-Loop
R. Martins, N. Lourenço, F. Passos, R. Póvoa, A. Canelas, E. Roca, R. Castro-López, J. Sieiro, F.V. Fernández and N. Horta
Journal Paper · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 38, no. 6, pp 989-1002, 2019
abstract
doi pdf
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 nonsystematic iterations between sizing and layout design steps, a multiobjective optimization-based layout-aware sizing approach with preoptimized 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 multinet router with preoptimized 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.
A two-step surrogate modeling strategy for single-objective and multi-objective optimization of radiofrequency circuits
F. Passos, R. González-Echevarría, E. Roca, R. Castro-López and F.V. Fernández
Journal Paper · Soft Computing, vol. 23, no. 13, pp 4911-4925, 2019
abstract
doi pdf
The knowledge-intensive radiofrequency circuit design and the scarce design automation support play against the increasingly stringent time-to-market demands. Optimization algorithms are starting to play a crucial role; however, their effectiveness is dramatically limited by the accuracy of the evaluation functions of objectives and constraints. Accurate performance evaluation of radiofrequency passive elements, e.g., inductors, is provided by electromagnetic simulators, but their computational cost makes their use within iterative optimization loops unaffordable. Surrogate modeling strategies, e.g., Kriging, support vector machines, artificial neural networks, etc., arise as a promising modeling alternative. However, their limited accuracy in this kind of applications has prevented a widespread use. In this paper, inductor performance properties are exploited to develop a two-step surrogate modeling strategy in order to evaluate the behavior of inductors with high efficiency and accuracy. An automated design flow for radiofrequency circuits using this surrogate modeling of passive components is presented. The methodology couples a circuit simulator with evolutionary computation algorithms such as particle swarm optimization, genetic algorithm or non-dominated sorting genetic algorithm (NSGA-II). This methodology ensures optimal performances within short computation times by avoiding electromagnetic simulations of inductors during the entire optimization process and using a surrogate model that has less than 1% error in inductance and quality factor when compared against electromagnetic simulations. Numerous real-life experiments of single-objective and multi-objective low-noise amplifier design demonstrate the accuracy and efficiency of the proposed strategies.
A comparison of automated RF circuit design methodologies: online vs. offline passive component design
F. Passos, E. Roca, R. Castro-López and F.V. Fernández
Journal Paper · IEEE Transactions on Very Large Scale Integration Systems, vol. 26, no. 11, pp 2386-2394, 2018
abstract
doi pdf
In this paper, surrogate modeling techniques are applied for passive component modeling. These techniques are exploited to develop and compare two alternative strategies for automated radio-frequency circuit design. The first one is a traditional approach where passive components are designed during the optimization stage. The second one, inspired on bottom-up circuit design methodologies, builds passive component Pareto-optimal fronts (POFs) prior to any circuit optimization. Afterward, these POFs are used as an optimized library from where the passive components are selected. This paper exploits the advantages of evolutionary computation algorithms in order to efficiently explore the circuit design space, and the accuracy and efficiency of surrogate models to model passive components.
Enhanced systematic design of a voltage controlled oscillator using a two-step optimization methodology
F. Passos, R. Martins, N. Lourenço, E. Roca, R. Póvoa, A. Canelas, R. Castro-López, N. Horta and F.V. Fernández
Journal Paper · Integration, vol. 63, pp 351-361, 2018
abstract
doi pdf
In this paper a design strategy based on bottom-up design methodologies is used in order to systematically design a voltage controlled oscillator. The methodology uses two computer-aided design tools: AIDA, a multi-objective multi-constraint circuit optimization tool, and SIDe-O, a tool that characterizes and optimizes integrated inductors with high accuracy (around 1% when compared to electromagnetic simulations). By using such tools, the difficult trade-offs inherent to radio-frequency circuits can be explored efficiently and accurately. Furthermore, with the capability that AIDA has at considering process parameter variations during the optimization, the resulting methodology is able to obtain truly robust circuit designs.
Radio-frequency inductor synthesis using evolutionary computation and Gaussian-process surrogate modeling
F. Passos, E. Roca, R.Castro-López and F.V. Fernández
Journal Paper · Applied Soft Computing, vol. 60, pp 495-507, 2017
abstract
doi pdf
In recent years, the application of evolutionary computation techniques to electronic circuit design problems, ranging from digital to analog and radiofrequency circuits, has received increasing attention. The level of maturity runs inversely to the complexity of the design task, less complex in digital circuits, higher in analog ones and still higher in radiofrequency circuits. Radiofrequency inductors are key culprits of such complexity. Their key performance parameters are inductance and quality factors, both a function of the frequency. The inductor optimization requires knowledge of such parameters at a few representative frequencies. Most common approaches for optimization-based radiofrequency circuit design use analytical models for the inductors. Although a lot of effort has been devoted to improve the accuracy of such analytical models, errors in inductance and quality factor in the range of 5%-25% are usual and it may go as high as 200% for some device sizes. When the analytical models are used in optimization-based circuit design approaches, these errors lead to suboptimal results, or, worse, to a disastrous non-fulfilment of specifications. Expert inductor designers rely on iterative evaluations with electromagnetic simulators, which, properly configured, are able to yield a highly accurate performance evaluation. Unfortunately, electromagnetic simulations typically take from some tens of seconds to a few hours, hampering their coupling to evolutionary computation algorithms. Therefore, analytical models and electromagnetic simulation represent extreme cases of the accuracy-efficiency trade-off in performance evaluation of radiofrequency inductors. Surrogate modeling strategies arise as promising candidates to improve such trade-off. However, obtaining the necessary accuracy is not that easy as inductance and quality factor at some representative frequencies must be obtained and both performances change abruptly around the self-resonance frequency, which is particular to each device and may be located above or below the frequencies of interest. Both, offline and online training methods will be considered in this work and a new two-step strategy for inductor modeling is proposed that significantly improves the accuracy of offline methods The new strategy is demonstrated and compared for both, single-objective and multi-objective optimization scenarios. Numerous experimental results show that the proposed two-step approach outperforms simpler application strategies of surrogate modelling techniques, getting comparable performances to approaches based on electromagnetic simulation but with orders of magnitude less computational effort.
An inductor modeling and optimization toolbox for RF circuit design
F. Passos, E. Roca, R. Castro-López and F.V. Fernández
Journal Paper · Integration, the VLSI Journal, vol. 58, pp 463-472, 2017
abstract
doi pdf
This paper describes the SIDe-O toolbox and the support it can provide to the radio-frequency designer. SIDe-O is a computer-aided design toolbox developed for the design of integrated inductors based on surrogate modeling techniques and the usage of evolutionary optimization algorithms. The models used feature less than 1% error when compared to electromagnetic simulations while reducing the simulation time by several orders of magnitude. Furthermore, the tool allows the creation of S-parameter files that accurately describe the behavior of inductors for a given range of frequencies, which can later be used in SPICE-like simulations for circuit design in commercial environments. This toolbox provides a solution to the problem of accurately and efficiently optimizing inductors, which alleviates the bottleneck that these devices represent in the radio-frequency circuit design process.
Conferences
Machine Learning Approaches for Transformer Modeling
F. Passos, N. Lourenço, R. Martins, E. Roca, R. Castro-Lopez, N. Horta and F.V. Fernandez
Conference · Int. Conf. on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design SMACD 2022
abstract
In this paper, several machine learning modeling methodologies are applied to accurately and efficiently model transformers, which are still a bottleneck in millimeter-wave circuit design. In order to compare the models, a statistical validation is performed against electromagnetic simulations using hundreds of passive structures. The presented models using machine learning techniques have proven to be accurate, efficient, and useful for a wide range of frequencies from (around) DC up to the millimeter-wave range (around 100GHz). As an application example, the models are used as a performance evaluator in a synthesis procedure to optimize a transformer and a balun.
Dealing with hierarchical partitioning in bottom-up design methodologies
F. Passos, P. Saraza-Canflanca, R. Castro Lopez, E. Roca and F.V. Fernandez
Conference · Int. Conf. on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design SMACD 2021
abstract
This paper deals with the expertise blend of circuit design and design methodology development required to successfully
address hierarchical partitioning of analog, radio-frequency and mm-Wave circuits in bottom-up design methodologies. A set
of guidelines is discussed for the optimal configuration of the bottom-up process that yields sound design results are obtained.
These guidelines are demonstrated with two case studies.
Using Polynomial Regression and Artificial Neural Networks for Reusable Analog IC Sizing
N. Lourenco, E. Afacan, R. Martins, F. Passos, A. Canelas, R. Povoa, N. Horta and G. Dundar
Conference · Int. Conf. on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design SMACD 2019
abstract
In this paper, the use of machine learning techniques to repurpose already available Pareto optimal fronts of analog integrated circuit blocks for new contexts (loads, supply voltage, etc.) is explored. Data from previously sized circuits is used to train models that predict both circuit performance under the new context and the corresponding device sizes. A two-model chain is proposed, where, in the first layer, a multivariate polynomial regression estimates the performance tradeoffs. The output of this performance model is then used as input of an artificial neural network that predicts the device sizing that corresponds to that performance. Moreover, the models are trained with optimized sizing solutions, leading almost instantly to predicted solutions that are near optimal for the new context. The proposed methodology was integrated into a new framework and tested against a real circuit topology, with promising results. The model was able to predict wider and, in some cases, better, performance tradeoff, when compared to independent optimization runs for the same context, despite requiring 400 times fewer circuit simulations.
Synthesis of mm-Wave circuits using EM-simulated passive structure libraries
F. Passos, E. Roca, R. Castro-Lopez, N. Horta and F.V. Fernandez
Conference · Int. Conf. on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design SMACD 2019
abstract
Millimeter-wave circuit design is extremely complex and time-consuming. One of the reasons is the dependence on electromagnetic simulators used to accurately predict the performance of the high amount of passive structures that compose such circuits. Also, achieving optimal performances is not trivial in the millimeter-wave regime. Although synthesis methodologies can aid the designer to achieve optimal circuit performances, the usage of electromagnetic simulators is prohibitive in such methodologies due to efficiency issues. In this work, a new synthesis methodology is presented where the accuracy of electromagnetic simulations can be included without losing efficiency.
Generation of Lifetime-Aware Pareto-Optimal Fronts Using a Stochastic Reliability Simulator
A. Toro-Frias, P. Saraza-Canflanca, F. Passos, P. Martin-Lloret, R. Castro-Lopez, E. Roca, J. Martin-Martinez, R. Rodriguez, M. Nafria and F.V. Fernandez
Conference · Design Automation and Test in Europe DATE 2019
abstract
Process variability and time-dependent variability have become major concerns in deeply-scaled technologies. Two of the most important time-dependent variability phenomena are Bias Temperature Instability (BTI) and Hot-Carrier Injection (HCI), which can critically shorten the lifetime of circuits. Both BTI and HCI reveal a discrete and stochastic behavior in the nanometer scale, and, while process variability has been extensively treated, there is a lack of design methodologies that address the joint impact of these two phenomena on circuits. In this work, an automated and timeefficient design methodology that takes into account both process and time-dependent variability is presented. This methodology is based on the utilization of lifetime-aware Pareto-Optimal Fronts (POFs). The POFs are generated with a multi-objective optimization algorithm linked to a stochastic simulator. Both the optimization algorithm and the simulator have been specifically tailored to reduce the computational cost of the accurate evaluation of the impact on a circuit of both sources of variability.
Handling the Effects of Variability and Layout Parasitics in the Automatic Synthesis of LNAs
F. Passos, R. Martins, N. Lourenço, E. Roca, R. Castro-López, R. Póvoa, A. Canelas, N. Horta and F.V. Fernández
Conference · Int. Conf. on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design SMACD 2018
abstract
This paper exposes the problematic issue of not considering device variability and layout parasitic effects in optimization-based design of radiofrequency integrated circuits. Therefore, in order to handle these issues, a new design methodology that performs an all-inclusive optimization is proposed, by taking into account the process variability, and, performing the complete layout automatically while performing an accurate parasitic extraction during the optimization for each candidate solution. Furthermore, the problematic inductor parasitics are also taken into account with EM-accuracy, by using a state-of-the-art surrogate modelling technique. The methodology was applied in the design and optimization of a low-noise amplifier, obtaining a set of extremely robust designs ready for fabrication.
Design considerations of an SRAM array for the statistical validation of time-dependent variability models
P. Saraza-Canflanca, D. Malagon, F. Passos, A. Toro, J. Nuñez, J. Diaz-Fortuny, R. Castro-Lopez, E. Roca, J. Martin-Martinez, R. Rodriguez, M. Nafria and F.V. Fernandez
Conference · Int. Conf. on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design SMACD 2018
abstract
Modeling and characterization of time-dependent variability phenomena as well as the simulation of their impact on circuit operation have attracted considerable efforts. This paper digs into the validation of compact models and simulation tools in the real operation of circuits. One of the most popular blocks, the 6T SRAM, is proposed for this purpose and a test chip containing an SRAM array is designed. The array allows individual access to each SRAM cell, the application of accelerated aging tests as well as the characterization of common performance metrics.
A strategy to efficiently include electromagnetic simulations in optimization-based RF circuit design methodologies
F. Passos, E. Roca, R. Castro-López, F.V. Fernández, J. Sieiro, and J.M. López-Villegas
Conference · IEEE MTT-S Int. Conf. on Numerical Electromagnetic and Multiphysics Modeling and Optimization for RF, Microwave, and Terahertz Applications NEMO 2017
abstract
The use of electromagnetic simulations is crucial in radiofrequency and microwave circuits since accurate estimations of parasitics and performances are essential. In addition, design methodologies based on optimization algorithms have been used in order to design such circuits, while efficiently exploring its design trade-offs. However, due to the high computational cost, optimization-based methodologies seldom use electromagnetic simulation. In order to overcome this issue, this paper demonstrates an optimization-based design methodology for radiofrequency circuits which can incorporate electromagnetic simulations without efficiency loss.
Systematic design of a voltage controlled oscillator using a layout-aware approach
F. Passos, E. Roca, R. Castro-López, F.V. Fernández, R. Martins, N. Lourenço, R. Póvoa, A. Canelas and N. Horta
Conference · Int. Conf. on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design SMACD 2017
abstract
This paper focuses on the systematic design of voltage controlled oscillators (VCO), a commonly used radiofrequency (RF) electronic circuit. RF circuits are among the most difficult analog circuits to design due to its trade-offs and high operation frequencies. At such operation frequencies, layout parasitics and accurate passive component characterization become of upmost importance, causing re-design iterations if they are not considered by the designer. To avoid this problem, and reduce the design time, this paper presents a systematic design of a VCO, entailing layout parasitics and accurate characterization of passive components from early design stages. Results clearly illustrate the benefit of this strategy.
An algorithm for a class of real-life multi-objective optimization problems with a sweeping objective
F. Passos, E. Roca, R. Castro-López and F.V. Fernández
Conference · IEEE Congress on Evolutionary Computation CEC 2017
abstract
This paper describes a class of real-life optimization problems that has not been addressed before: a multi-objective optimization in which one objective is neither minimized nor maximized but uniformly swept over a wide range. The limitations of conventional multi-objective optimization algorithms to deal with this kind of problems are illustrated via the optimization of radiofrequency inductors. For the first time, an algorithm is proposed that provides sets of solutions for this kind of problems.
Layout-aware challenges and a solution for the automatic synthesis of radio-frequency IC blocks
R. Martins, N. Lourenço, R. Póvoa, A. Canelas, N. Horta, F. Passos, R. Castro-López, E. Roca and F.V. Fernández
Conference · Int. Conf. on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design SMACD 2017
abstract
In this paper, the major methodologies proposed in the last years to speed-up the synthesis of radio-frequency integrated circuits blocks are overviewed. The challenges to automate this task are discussed, and, to avoid non-systematic iterations between circuit and layout design steps, the architecture of an innovative solution is proposed. The proposed tool exploits the full capabilities of most established computer-aided design tools available nowadays, i.e., off-the-shelf circuit simulator, electromagnetic simulator and layout extractor. The approach intends to bypass the two major bottlenecks of RF-design: the design of reliable integrated inductors and accurate layout parasitic estimates since the early stages of design process.
New mapping strategies for pre-optimized inductor sets in bottom-up RF IC sizing optimization
N. Lourenço, R. Martins, R. Póvoa, A. Canelas, N. Horta, F. Passos, R. Castro-López, E. Roca and F. V. Fernández
Conference · Int. Conf. on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design SMACD 2017
abstract
This paper presents new indexing and mutation operators, in the context of bottom-up hierarchical multi-objective optimization of radio frequency integrated circuits, for pre-optimized sets of solutions from the hierarchical sub-levels when moving up in hierarchy. Two ideas, one based on a Voronoi decomposition and another based on the nearest neighborhood, are explored, where, and unlike previous approaches that are based on sorting, the distance between elements determines the probability of decisions taken during optimization. Three implementations of those ideas were tried in AIDA's NSGAII evolutionary kernel, and successfully used in the optimization of a Voltage Controlled Oscillator and a Low Noise Amplifier with pre-optimized inductor sets obtained using the SIDeO toolbox, showing their strengths when compared to previous state-of-the-art mapping strategies.
SIDe-O: A Toolbox for Surrogate Inductor Design and Optimization
F. Passos, E. Roca, R. Castro-López, F. V. Fernández
Conference · Int. Conf. on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design SMACD 2016
abstract
This paper presents SIDe-O, a CAD tool developed for the design and optimization of integrated inductors based on surrogate modeling techniques. This tool provides a solution to the problem of accurately and efficiently optimizing the design of inductors. The models used present less than 1% error when compared to EM simulations while reducing the simulation time by several orders of magnitude. Additionally, the tool provides the ability to create new surrogate models for different technologies and inductor topologies. The tool also allows the creation of an S-Parameter file that accurately describes the behavior of the inductor for a given range of frequencies, which can later be used in SPICE-like simulations.
Frequency-Dependent Parameterized Macromodeling of Integrated Inductors
F. Passos, E. Roca, R. Castro-López, F.V. Fernández, Y. Ye, D. Spina and T. Dhaene
Conference · Int. Conf. on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design SMACD 2016
abstract
Integrated inductors are one of the most important passive elements in radio frequency design, due to their wide usage in wireless communication circuits. Typically, electromagnetic simulators are used in order to estimate the inductors performance with high accuracy as a function of the inductor geometrical and electrical parameters. Such simulations offer high-accuracy, but are computationally expensive and extremely time consuming. In this paper, a frequency-dependent parameterized macromodeling technique is adopted in order to overcome this problem. The proposed approach offers a high degree of automation, since it is based on sequential sampling algorithms, high efficiency and flexibility: a continuous frequency-domain model is given for each value of the chosen inductors parameters in the design space.
Accurate Synthesis of Integrated RF Passive Components using Surrogate Models
F. Passos, R. González-Echevarría, E. Roca, R. Castro-López and F.V. Fernández
Conference · Design, Automation and Test in Europe DATE 2016
abstract
Passive components play a key role on the design of RF CMOS integrated circuits. Their synthesis, however, is still an unsolved problem due to the lack of accurate analytical models that can replace the computationally expensive electromagnetic simulations (EM). Both, physical-based and surrogate models have been reported that fail to accurately model the complete design space of inductors. Surrogate-assisted optimization techniques, where coarse models are locally enhanced during the inductor synthesis process by using new EM-simulated points to update the model, have been proposed, but either the efficiency is dramatically decreased due to the online EM simulations or the optimization may converge to suboptimal regions. In this paper, we present a new surrogate model, valid in the entire design space with less than 1% error when compared with EM simulations. This model can be generated offline, and, when embedded within an optimization algorithm, allows the synthesis of integrated inductors with high accuracy and high efficiency, reducing the synthesis time in three orders of magnitude.
Surrogate Modeling and Optimization of Inductor Performances using Kriging functions
F. Passos, R. González-Echevarría, E. Roca, R. Castro-López and F.V. Fernandez
Conference · Int. Conf. on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design SMACD 2015
abstract
Integrated inductors are one of the most important passive elements in RF circuits. However, time-consuming simulations, such as electromagnetic simulations, have to be used to evaluate their performances with high accuracy. In order to overcome this problem, analytical models can be used. In this paper, a surrogate model based on Kriging functions is presented that accurately predicts the performance parameters of integrated inductors. The different approaches followed to obtain the model are presented. Finally, the model is linked to an evolutionary algorithm to optimize inductor performances.
Physical vs. Surrogate Models of Passive RF Devices
F. Passos, M. Kotti, R. González-Echevarría, M.H. Fino, M. Fakhfakh, E. Roca, R.Castro-López and F.V. Fernández
Conference · IEEE International Symposium on Circuits and Systems ISCAS 2015
abstract
The accuracy of high-frequency models of passive RF devices, e.g., inductors or transformers, presents one of the most challenging problems for RF integrated circuits. Accuracy limitations lead RF designers to time-consuming iterations with electromagnetic simulators. This paper will explore and compare two advanced modeling techniques. The first one is based on the segmented model approach, in which each device segment is characterized with a lumped element model. The second technique is based on the generation of surrogate models from the electromagnetic simulation of a set of device samples. Different modeling strategies (frequency separation, filtering according to self-resonance frequency, etc.) will be considered. Efficiency and accuracy of both, physical and surrogate, modeling techniques will be compared using a Si process technology.
Books
Automated Hierarchical Synthesis of Radio-Frequency Integrated Circuits and Systems. A Systematic and Multilevel Approach
F. Passos, E. Roca, R. Castro-López and F.V. Fernández
Book · 204 p, 2020
abstract
link
This book describes a new design methodology that allows optimization-based synthesis of RF systems in a hierarchical multilevel approach, in which the system is designed in a bottom-up fashion, from the device level up to the (sub)system level. At each level of the design hierarchy, the authors discuss methods that increase the design robustness and increase the accuracy and efficiency of the simulations. The methodology described enables circuit sizing and layout in a complete and automated integrated manner, achieving optimized designs in significantly less time than with traditional approaches.
- Describes an efficient and accurate methodology to design automatically RF systems, with guaranteed accuracy from the device to the system level.
- Discusses analytical and machine learning techniques for modelling integrated inductors and uses such models in synthesis approaches.
- Compares synthesis strategies for RF circuits based on bottom-up versus flat approaches.
- Discusses layout-aware bottom-up design methodologies for RF circuits.
- Discusses variability-aware bottom-up design methodologies for RF circuits.
- Describes multilevel bottom-up design methodologies from the device up to the system level.
Book Chapters
On the usage of machine-learning techniques for the accurate modeling of integrated inductors for RF applications
F. Passos, E. Roca, R. Castro-Lopez and F.V. Fernandez
Book Chapter · Modelling Methodologies in Analogue Integrated Circuit Design, pp 155-178, 2020
abstract
doi
This chapter describes an inductor modeling strategy based on machine-learning techniques. The model developed is based on Kriging functions and uses a novel modeling technique based on a two-step strategy, which is able to obtain an extremely accurate model with less than 1% error when compared to electromagnetic (EM) simulations. Due to its extreme accuracy and efficiency, the model can be used in inductor synthesis processes using single- or multi-objective optimization algorithms in order to obtain a single design or a Pareto-optimal front. Also, the model can describe the inductor behavior in frequency and therefore can also be used in circuit design using modern electrical simulators. This chapter discusses both applications (inductor synthesis and circuit design), performing several singleand multi-objective inductor optimizations, using different inductor topologies and operating frequencies. Furthermore, the model is also used in order to accurately model inductors during the design of a voltage-controlled oscillator (VCO) and a low-noise amplifier (LNA).
Other publications
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