Giuliana Gangemi

Towards Multi-Domain and Multi-Physical Electronic Design

Electronic systems are increasingly fusing multiple technology solutions exchanging information both at electrical and at non-electrical levels, and in general both analog and digital operation coexists in multiple physical domains. This paper introduces a homogeneous multi-domain design methodology which blurs analog and digital boundaries and enables the design of etherogeneous electrical and non-electrical building blocks. The methodology is based on the identification of four fundamental quantities (quadrivium), namely signal-to-noise ratio, signal-to-interference ratio, impedance and consumed energy, applicable to both electrical and multiphysics components. Based on their constraining and their propagation on an ensemble of transactions in time domain, these four elements can be used across different domains (digital or analog), and permit architects to extract internal features, so that these are intrinsically oriented to successive physical and technology-related implementation and modeling. With example application cases, we show that these four quantities in turn define design constraints of electrical and nonelectrical internal units. After presenting an electronic design example, to show applicability in multiple physical domains, the paper discusses and applies the quadrivium also in the context of a MEMS sensor and microfluidic components.

Multi-domain simulation as a foundation for the engineering of smart systems: Challenges and the SMAC vision

Technology and market evolutions in smart-systems call for a new design paradigm which is focused on the integration of the development processes in the various engineering disciplines through timely exchange of models, tuned to the specific needs of the different users. According to the vision of the SMAC consortium, these models should be generated automatically through appropriate abstraction flows. The present paper reviews the challenges related to the design of smart-systems and in particular multi-domain simulation and presents the solutions being experimented in the project.

Smart System Case Studies

This chapter presents two case studies showing how the proposed approach applies to smart system design and optimization. The former is the virtual prototyping platform built for a laser pico-projector actuator, where MEMS, analog and digital components are simulated with the aim of optimizing the resulting image quality by means of firmware tuning. The latter, in the context of wearable equipment for inertial body motion reconstruction, deals with the modeling of an inertial sensor node, supporting system accuracy evaluation and sensor fusion enhancement. Finally, the Open-Source Test Case (OSTC) is described, showing a complete modeling and simulation flow on a publicly available design.

Modeling and Simulation of the Power Flow in Smart Systems

Besides their heterogeneity in the type of devices, the other distinctive feature of smart systems is their being energy-autonomous; they are normally equipped with one or more devices able to harvest power from the environment, and, in many cases, also with elements that can smooth fluctuations in the harvested energy and deliver it to the various loads with a predictable “quality of service.”

The MAnON Project

The nano-CMOS technology scaling makes the figures of merit of a circuit, such as performance and power, extremely sensitive to uncontrollable statistical process variation (PV). In this context, multi-objective optimization algorithms and statistical analysis are essential to ensure stable manufacturing and secure high foundry yields. The CAD and Design Services group, part of the IPG R&D in STMicroelectronics, has created a consortium in order to develop, test and implement “Methods for Advanced Multi-objective Optimization for eDFY of Complex Nano-scale Circuits”: the MAnON Project. The contribution presents the industrial and scientific project challenges, the research results, and consequent methodology enhancements and their implementation into a software prototype in order to be usable inside a nanoelectronics industrial design environment.

Minisymposium Optimization and Model Order Reduction in Circuit Design

While during the last decades the great enhancements in the field of digital design methodologies and tools have allowed to design larger digital circuits in less time, the analog circuit design methods have not progressed at the same rate. The design of analog electrical circuits needs electronic engineers with a long experience and a wide knowledge of the theories that rule this kind of circuits. However, experimental optimization tools exist; they search the space of solutions for optimal configurations of variables sets, given a circuit netlist provided by the designers. Typical analog integrated circuit optimization problems are computationally hard and require the handling of multiple, conflicting, and non-commensurate objectives having strong nonlinear interdependence. In general it is possible to reformulate integrated circuit design as constrained multi-objective optimization problems defined in a mixed integer/discrete/continuous domain. The hereby employed traditional numerical techniques are becoming too much time-consuming for circuits of industrial complexity. The long computation time required for the optimization of a complete circuit cannot be tolerated especially in the early design stages. For tackling this complexity problem model reduction methods are a promising approach in order to achieve a faster performance evaluation in order to obtain more robust devices within a more efficient design process.