Platforms have become an important concept in the design of electronic systems. We present here the motivations behind the interest shown and the challenges that we have to face to make the Platform-based Design method a standard. As a generic term, platforms have meant different things to different people. The main challenges are to distill the essence of the method, to formalize it and to provide a framework to support its use in areas that go beyond the original domain of application.

Analog performance space exploration identifies the range of feasible performance values of a given circuit topology. It is an extremely challenging task of great importance to topology selection and hierarchical sizing. In this paper, a novel technique for the efficient simulation-based exploration of high-dimensional performance spaces is presented. To this end, fundamental circuit design knowledge is described by constraint functions. Based on a linearization of the latter and of the circuit performance functions, a description of the feasible performance range in the form of a polytope is derived. Moreover, the approach is integrated into a hierarchical sizing method, where it propagates topological and technological constraints bottom-up. Practical application results demonstrate the efficiency and usefulness of the new method. 1.

This paper describes a novel approach to system level analog design. A new abstraction level –the platform – is introduced to separate circuit design from design space exploration. An Analog Platform encapsulates analog components concurrently modeling their behavior and their achievable performances. Performance models are obtained through statistical sampling of circuit configurations. The design configurations space is specified with Analog Constraint Graphs so that the sampling space is significantly reduced. System level exploration can be achieved through optimization on behavioral models constrained by performance models. Finally, an example is provided showing the effectiveness of the approach on a WCDMA amplifier. 1.

We propose a hierarchical mixed signal design methodology based on the principles of Platform-Based Design (PBD). The methodology is a meet-in-the-middle approach where design components are modeled bottom-up at various abstraction levels and performance constraints are mapped top-down to select among the available components the ones that best meet the constraints. The design methodology can seamlessly operate on both analog and digital designs, thus dealing with mixed signal designs in a consistent way. We demonstrate the effectiveness of the approach optimizing an 80 MS/s 14 bit pipelined Analog-to-Digital Converter (ADC) including digital calibration, yielding 64 % power reduction compared to the original hand optimized design.

Universal Mobile Telecommunication System (UMTS) front end design is challenging because of the need to optimize power while satisfying a very high dynamic range requirement. Dealing with this design problem at the transistor level does not allow to explore efficiently the design space, while using behavioral models does not allow to take into consideration important second-order effects. We present an extension of the platform-based design methodology originally developed for digital systems to the analog domain to conjugate the need of higher levels of abstraction to deal with complexity as well as the one of capturing enough of the actual circuit-level characteristics to deal with second order effects. We show how this methodology applied to the UMTS front-end design yields power savings as large as 47% versus an original hand optimized design. 1.

analog circuit synthesis. It usually consist of two steps: feasibility design space identification and performance macromodels generation. A feasibility design space is defined as a multidimensional space in which every design satisfies all the design constraints. The minimum set of constraints is the one that ensures the correct functionality of the given circuit topology. Performance macromodels are only constructed and thereby valid in the functionally correct design space. Support vector machines (SVMs) are used as classifier to identify the feasible design space of analog circuits. A kernel is an integral part of the SVM and contributes in obtaining an optimized and accurate classifier. The most commonly used kernels are Radial Basis Function (RBF), polynomial, spline, multilayer perceptron. In this paper, some new kernels and some other kernels composed through modifications on the some of the standard kernels, are explored. The classifiers using these kernel functions have been tested on different analog circuits in order to identify the feasible design space. HSPICE has been used for generation of learning data. Least Square SVM toolbox interfaced with MATLAB was used for classification. We found that use of modified kernels improves classification accuracy as well as shortens classifier generation time.

Abstract—This is Part I of a sequence of two papers on Contract-Based Design (CBD). It is intended to: • Introduce the concepts underlying CBD; • Present the challenges facing facing designers of large-scale complex systems today; • Review the design methodologies so far used to address these challenges and show how contracts can be used in all these approaches to enhance their applicability and the quality of the final result, and • Present three examples of the use of contracts: one simple example to underline the key steps of contract-based design, one about the use of contracts in enhancing and extending the AUTOSAR automotive standard and one related to analog-mixed signal integrated circuit design. Part II covers the theoretical foundations for contracts that are