Multilevel Modeling and Architectural Solutions for Emerging Technology Circuits

In the last decades, the main driving force behind the astonishing development of CMOS technology, was the transistor scaling process. The reduction of transistor sizes has granted a continuous boost in circuits performance. But now that the scaling process is reaching its physical limits, researchers are forcusing on new emerging technologies. Research on these new technologies is usually carried on using a traditional approach. Some studies concentrate on new devices without analyzing circuits based on them. Other studies analyze circuit architectures without considering devices characteristics and limitations. However, given that the nature of emerging technologies can be very different from CMOS, new research methodologies should be adopted. A clear link between device and architectural analysis is necessary to understand the true potential of the technology under study. The objective of this PhD thesis is the analysis of emerging technologies using an innovative methodology. Using complex and realistic circuits as benchmark, high level models are built incorporating low level device characteristics. This methodology strongly links device and architectural levels. The methodology was applied to two emerging technologies: NanoMagnet Logic (NML) and Nanoscale Application Specific Integrated Circuits (NASIC). A brief introduction of fundamental information on the two technologies is given in Chapter 1. The application of the methodology on NML technology is divided in two parts (Chapter 2): i) architecture-level timing and performance analysis and circuits optimization; (ii) area and power estimations using VHDL modeling. Starting from an exhaustive analysis of the effects and the consequences derived by the presence of loops in a complex NML sequential architecture, solutions have been proposed to address the problem of signal synchronization, and optimization techniques have been explored for performance maximization. Area and power estimations have been performed on multiple NML architectures in order to obtain a complete evaluation on the implementation of NanoMagnet Logic in comparison with the CMOS technology. Chapter 4 is dedicated to NASIC technology with basic principles described in Chapter 3. Basic computational blocks are implemented using a multilevel modeling approach. A detailed analysis of circuits' area and power estimations is obtained. Techniques to optimize the area of circuits at the cost of reduced throughput were also investigated. The research activity presented in this thesis highlights the development of an innovative methodology based on high-level models that embed information obtained from physical level simulations. By exploiting this methodology to different emerging technologies, such as NML and NASIC, it allows to eciently analyze circuits and therefore to bring architectural improvements

Cellular Automata

Modelling and simulation are disciplines of major importance for science and engineering. There is no science without models, and simulation has nowadays become a very useful tool, sometimes unavoidable, for development of both science and engineering. The main attractive feature of cellular automata is that, in spite of their conceptual simplicity which allows an easiness of implementation for computer simulation, as a detailed and complete mathematical analysis in principle, they are able to exhibit a wide variety of amazingly complex behaviour. This feature of cellular automata has attracted the researchers' attention from a wide variety of divergent fields of the exact disciplines of science and engineering, but also of the social sciences, and sometimes beyond. The collective complex behaviour of numerous systems, which emerge from the interaction of a multitude of simple individuals, is being conveniently modelled and simulated with cellular automata for very different purposes. In this book, a number of innovative applications of cellular automata models in the fields of Quantum Computing, Materials Science, Cryptography and Coding, and Robotics and Image Processing are presented

The Deep Space Network

Deep Space Network progress in flight project support, tracking and data acquisition, research and technology, network engineering, hardware and software implementation, and operations is cited. Topics covered include: tracking and ground based navigation; spacecraft/ground communication; station control and operations technology; ground communications; and deep space stations