Elsevier

Integration

Volume 44, Issue 1, January 2011, Pages 39-50
Integration

Measuring the uniqueness and variety of analog circuit design features

https://doi.org/10.1016/j.vlsi.2010.06.003Get rights and content

Abstract

Analog circuit design activity is currently a less formalized process, in which the main source for innovation is the designer's ability to produce new designs by combining basic devices, sub-circuits, and ideas from similar solutions. There are few systematic methods that can fuse and transform the useful features of the existing designs into new solutions. Moreover, most automated circuit synthesis tools are still limited to routine tasks, like transistor sizing and layout design. Developing new design techniques that can combine the existing design features requires metrics that describe the uniqueness and variety of the features. This paper evaluates for analog circuits two such general-purpose metrics proposed in [1], [2]. Three case studies are discussed on using the metrics to characterize the design features of current mirrors, transconductors, and operational amplifiers. The two metrics and the presented study is useful in producing an overall characterization of analog circuit features. This can help in enhancing the circuit design process, training of young designers, and developing new automated synthesis tools that can explore more solution space regions that are likely to include novel design features.

Introduction

Analog circuit design is considered to be by and large an art [3], [4], [5]. This is arguably due to the circuit design activity being a less structured process that is not fully formalized as an algorithmic sequence of steps. Designers often rely on similarities with previous designs (experience), on analogies with solutions in other engineering domains, and even on inspiration drawn from biology and anatomy [6]. However, the main vehicle in creating novel circuit solutions is still a designer's talent to combine the defining features of basic devices and building blocks (e.g., sub-circuits) into new design solutions. While the characteristics of the actual building blocks are well understood, the innovating process of creatively combining them is not.

Designing analog circuits with new features is currently a slow, expensive, and error-prone activity, accessible mainly to a small group of experts. There are no systematic methods to help and improve the process of analog design through fusion and transformation of existing circuit designs. Also, educating designers is tedious and often spans 10–15 years. Without a theory on how to efficiently combine existing circuit structures into new solutions, it is hard to train engineers on developing efficient designs for new requirements. Furthermore, computer-aided design (CAD) tools are continuously challenged to keep pace with state-of-the-art circuit design. Still, most tools are limited to routine tasks, like transistor sizing and constructing layouts [3], [4]. With few exceptions, tools cannot produce new circuit topologies or exploit the innovating features of existing, manually crafted designs. Novel methods are needed to help understand, emulate, and enhance the process of innovation in circuit design.

An intriguing approach towards developing a theory on creative circuit design is to formalize a computational model that captures the process of feature combination and transformation in circuit design. This model would be based on the main cognitive steps of design innovation, such as expanding and contracting the active conceptual space, imposing a new context on a solution, similarities, and deconceptualization [7], [8], [9]. As in other engineering domains, like mechanical engineering design [1], [2], the core of the model would include a set of metrics that can accurately express the uniqueness and variety of the design features of the circuits implementing various specifications.

There is currently few work on metrics that describe the uniqueness and variety of design features. Research in design science has recently proposed new metrics used mainly in mechanical engineering [1]. The metrics characterize both the frequency and variety of the features of an individual design as well as a set of designs. Enhancements to the original metrics have been subsequently proposed to increase the scope of the metrics [2]. Alternatively, the new features of a design also depend to a significant degree on the characteristics of the design flow. Many engineering systems are designed through multiple iterations that involve parameter optimization and technological changes [10]. Design science research focuses on determining the conditions that help generation of solutions with novel yet useful features [10], [11], predicting the potential success of a new design feature [12], and characterizing ideation effectiveness through objective measures [1], [2].

While such design feature-related metrics are general purpose, to the best of our knowledge, there have been no attempts to study the effectiveness of the metrics in describing the uniqueness and variety of the features of various analog circuit designs. Analog circuits have important differences compared to the engineering designs discussed in the literature, e.g., they are built from tightly coupled building blocks, there are strong correlations between the overall performance of the design and the parameters of the building blocks, and design reuse is an important design strategy.

This paper studies the uniqueness and variety of the design features present in popular analog circuits, like transconductors and operational amplifiers, by adapting and applying the related metrics developed by the design science community [1], [2]. The characterized features refer to topological structures for implementing physical principles (i.e. saturation, triode or sub-threshold), working principles (e.g., voltage or current biasing), and embodiment principles (like differential or pseudo-differential). The metrics were applied to a set of circuits that was selected from the recent circuit design literature. In contrast to [1], [2], the metrics were also computed to study the evolution of their values over time. This is important to understand the robustness of the metrics, e.g., their capability to detect early the most novel and unique design features, and to understand the points in time when new design features are more likely to occur. Instead of being applied to the entire set, the metrics were computed for subsets of circuits, in the chronological sequence of their publication. Such clusters include the circuits published at short intervals in time. The analysis also studied the evolution of the metric values depending on the fabrication process of the circuits. The design features of a set of automatically generated circuits has also been analyzed in an attempt to understand the capability of automated synthesis methods, like methods based on genetic algorithms, to produce novel, yet efficient designs.

Characterizing the uniqueness and variety of circuit design features can improve the design process by pointing out the main benefits of the features, and the capability to their reuse for other problems. The design set variety can indicate the fraction of the design space that has been explored, and can suggest “directions” along which new design features might be located. The two metrics can act as diversification strategies in situations for which traditional solutions are not sufficient. It is also expected that, on the long run, the metrics can help in better understanding the circuit design process, developing more systematic circuit design methods, better ways of educating young designers, and, hopefully, lead to superior CAD tools.

The paper has the following structure. Section 2 describes the metrics used in evaluating the uniqueness and variety of design features. Section 3 presents the analysis performed for three types of analog circuits, current mirrors, transconductors and operational amplifiers. Finally, conclusions are put forth.

Section snippets

Metrics for design feature characterization

This section presents the adaptation for analog circuit design of two metrics proposed in the literature [1], [2] to measure the uniqueness (frequency of occurrence) of the features of a design, and the variety of the features of a design set.

Design feature characterization for analog circuits

This section presents the results for applying the two metrics, design feature uniqueness and variety metrics, to state-of-the-art circuits found in the related literature. To study their versatility, metrics have been used for three different circuit design problems: design of (1) current mirrors, (2) transconductors, and (3) operational amplifiers.

Conclusions and future work

This paper investigates the uniqueness and variety of the design features of popular analog circuits by using the set of metrics proposed in the design science literature [1], [2]. The considered circuits include current mirrors, transconductors, and operational amplifiers. The features refer to topological structures for implementing physical principles (i.e. saturation, triode or sub-threshold), working principles (e.g., voltage or current biasing), and embodiment principles (like

Acknowledgment

This work was supported by major collaborative research National Science Foundation CreativeIT Grant no. IIS 0856038.

Cristian Ferent received Dipl. Ing. degree in electronics and telecommunications engineering from the Technical University of Cluj-Napoca, Romania in 2007. He is currently a Ph.D. student in the Department of Electrical and Computer Engineering at the State University of New York at Stony Brook, USA. His research interests are in CAD for analog circuit design, particulary methods for systematically improving the innovation and creativity level of automatically produced design solutions.

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    Cristian Ferent received Dipl. Ing. degree in electronics and telecommunications engineering from the Technical University of Cluj-Napoca, Romania in 2007. He is currently a Ph.D. student in the Department of Electrical and Computer Engineering at the State University of New York at Stony Brook, USA. His research interests are in CAD for analog circuit design, particulary methods for systematically improving the innovation and creativity level of automatically produced design solutions.

    Alex Doboli received the M.S. and Ph.D. degrees in Computer Science from ”Politehnica” University Timisoara, Romania, in 1990 and 1997, respectively, and the Ph.D. degree in Computer Engineering from University of Cincinnati, Cincinnati, OH in 2000. He is currently an Associate Professor at the Department of Electrical and Computer Engineering, State University of New York (SUNY) at Stony Brook, NY. His research is in electronic design automation, with special interest in mixed-signal CAD and hardware–software codesign. Dr. Doboli is senior member of IEEE and member of Sigma Xi.

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