Low power predictable memory and processing architectures

Great demand in power optimized devices shows promising economic potential and draws lots of attention in industry and research area. Due to the continuously shrinking CMOS process, not only dynamic power but also static power has emerged as a big concern in power reduction. Other than power optimization, average-case power estimation is quite significant for power budget allocation but also challenging in terms of time and effort. In this thesis, we will introduce a methodology to support modular quantitative analysis in order to estimate average power of circuits, on the basis of two concepts named Random Bag Preserving and Linear Compositionality. It can shorten simulation time and sustain high accuracy, resulting in increasing the feasibility of power estimation of big systems. For power saving, firstly, we take advantages of the low power characteristic of adiabatic logic and asynchronous logic to achieve ultra-low dynamic and static power. We will propose two memory cells, which could run in adiabatic and non-adiabatic mode. About 90% dynamic power can be saved in adiabatic mode when compared to other up-to-date designs. About 90% leakage power is saved. Secondly, a novel logic, named Asynchronous Charge Sharing Logic (ACSL), will be introduced. The realization of completion detection is simplified considerably. Not just the power reduction improvement, ACSL brings another promising feature in average power estimation called data-independency where this characteristic would make power estimation effortless and be meaningful for modular quantitative average case analysis. Finally, a new asynchronous Arithmetic Logic Unit (ALU) with a ripple carry adder implemented using the logically reversible/bidirectional characteristic exhibiting ultra-low power dissipation with sub-threshold region operating point will be presented. The proposed adder is able to operate multi-functionally

Asynchrobatic logic for low-power VLSI design

In this work, Asynchrobatic Logic is presented. It is a novel low-power design style that combines the energy saving benefits of asynchronous logic and adiabatic logic to produce systems whose power dissipation is reduced in several different ways. The term “Asynchrobatic” is a new word that can be used to describe these types of systems, and is derived from the concatenation and shortening of Asynchronous, Adiabatic Logic. This thesis introduces the concept and theory behind Asynchrobatic Logic. It first provides an introductory background to both underlying parent technologies (asynchronous logic and adiabatic logic). The background material continues with an explanation of a number of possible methods for designing complex data-path cells used in the adiabatic data-path. Asynchrobatic Logic is then introduced as a comparison between asynchronous and Asynchrobatic buffer chains, showing that for wide systems, it operates more efficiently. Two more-complex sub-systems are presented, firstly a layout implementation of the substitution boxes from the Twofish encryption algorithm, and secondly a front-end only (without parasitic capacitances, resistances) simulation that demonstrates a functional system capable of calculating the Greatest Common Denominator (GCD) of a pair of 16-bit unsigned integers, which under typical conditions on a 0.35μm process, executed a test vector requiring twenty-four iterations in 2.067μs with a power consumption of 3.257nW. These examples show that the concept of Asynchrobatic Logic has the potential to be used in real-world applications, and is not just theory without application. At the time of its first publication in 2004, Asynchrobatic Logic was both unique and ground-breaking, as this was the first time that consideration had been given to operating large-scale adiabatic logic in an asynchronous fashion, and the first time that Asynchronous Stepwise Charging (ASWC) had been used to drive an adiabatic data-path

Advanced Timing and Synchronization Methodologies for Digital VLSI Integrated Circuits

This dissertation addresses timing and synchronization methodologies that are critical to the design, analysis and optimization of high-performance, integrated digital VLSI systems. As process sizes shrink and design complexities increase, achieving timing closure for digital VLSI circuits becomes a significant bottleneck in the integrated circuit design flow. Circuit designers are motivated to investigate and employ alternative methods to satisfy the timing and physical design performance targets. Such novel methods for the timing and synchronization of complex circuitry are developed in this dissertation and analyzed for performance and applicability.Mainstream integrated circuit design flow is normally tuned for zero clock skew, edge-triggered circuit design. Non-zero clock skew or multi-phase clock synchronization is seldom used because the lack of design automation tools increases the length and cost of the design cycle. For similar reasons, level-sensitive registers have not become an industry standard despite their superior size, speed and power consumption characteristics compared to conventional edge-triggered flip-flops.In this dissertation, novel design and analysis techniques that fully automate the design and analysis of non-zero clock skew circuits are presented. Clock skew scheduling of both edge-triggered and level-sensitive circuits are investigated in order to exploit maximum circuit performances. The effects of multi-phase clocking on non-zero clock skew, level-sensitive circuits are investigated leading to advanced synchronization methodologies. Improvements in the scalability of the computational timing analysis process with clock skew scheduling are explored through partitioning and parallelization.The integration of the proposed design and analysis methods to the physical design flow of integrated circuits synchronized with a next-generation clocking technology-resonant rotary clocking technology-is also presented. Based on the design and analysis methods presented in this dissertation, a computer-aided design tool for the design of rotary clock synchronized integrated circuits is developed

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

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

On the road towards robust and ultra low energy CMOS digital circuits using sub/near threshold power supply

Ph.DNUS-TU/E JOINT PH.D. PROGRAMM

Quantum Stochastic Processes and Quantum Many-Body Physics

This dissertation investigates the theory of quantum stochastic processes and its applications in quantum many-body physics. The main goal is to analyse complexity-theoretic aspects of both static and dynamic properties of physical systems modelled by quantum stochastic processes. The thesis consists of two parts: the first one addresses the computational complexity of certain quantum and classical divisibility questions, whereas the second one addresses the topic of Hamiltonian complexity theory. In the divisibility part, we discuss the question whether one can efficiently sub-divide a map describing the evolution of a system in a noisy environment, i.e. a CPTP- or stochastic map for quantum and classical processes, respectively, and we prove that taking the nth root of a CPTP or stochastic map is an NP-complete problem. Furthermore, we show that answering the question whether one can divide up a random variable $X$ into a sum of $n$ iid random variables $Y_i$, i.e. $X=\sum_{i=1}^n Y_i$, is poly-time computable; relaxing the iid condition renders the problem NP-hard. In the local Hamiltonian part, we study computation embedded into the ground state of a many-body quantum system, going beyond "history state" constructions with a linear clock. We first develop a series of mathematical techniques which allow us to study the energy spectrum of the resulting Hamiltonian, and extend classical string rewriting to the quantum setting. This allows us to construct the most physically-realistic QMAEXP-complete instances for the LOCAL HAMILTONIAN problem (i.e. the question of estimating the ground state energy of a quantum many-body system) known to date, both in one- and three dimensions. Furthermore, we study weighted versions of linear history state constructions, allowing us to obtain tight lower and upper bounds on the promise gap of the LOCAL HAMILTONIAN problem in various cases. We finally study a classical embedding of a Busy Beaver Turing Machine into a low-dimensional lattice spin model, which allows us to dictate a transition from a purely classical phase to a Toric Code phase at arbitrarily large and potentially even uncomputable system sizes

Perspectives on adaptive dynamical systems

Adaptivity is a dynamical feature that is omnipresent in nature, socio-economics, and technology. For example, adaptive couplings appear in various real-world systems, such as the power grid, social, and neural networks, and they form the backbone of closed-loop control strategies and machine learning algorithms. In this article, we provide an interdisciplinary perspective on adaptive systems. We reflect on the notion and terminology of adaptivity in different disciplines and discuss which role adaptivity plays for various fields. We highlight common open challenges and give perspectives on future research directions, looking to inspire interdisciplinary approaches

Two Phase Flow, Phase Change and Numerical Modeling

The heat transfer and analysis on laser beam, evaporator coils, shell-and-tube condenser, two phase flow, nanofluids, complex fluids, and on phase change are significant issues in a design of wide range of industrial processes and devices. This book includes 25 advanced and revised contributions, and it covers mainly (1) numerical modeling of heat transfer, (2) two phase flow, (3) nanofluids, and (4) phase change. The first section introduces numerical modeling of heat transfer on particles in binary gas-solid fluidization bed, solidification phenomena, thermal approaches to laser damage, and temperature and velocity distribution. The second section covers density wave instability phenomena, gas and spray-water quenching, spray cooling, wettability effect, liquid film thickness, and thermosyphon loop. The third section includes nanofluids for heat transfer, nanofluids in minichannels, potential and engineering strategies on nanofluids, and heat transfer at nanoscale. The forth section presents time-dependent melting and deformation processes of phase change material (PCM), thermal energy storage tanks using PCM, phase change in deep CO2 injector, and thermal storage device of solar hot water system. The advanced idea and information described here will be fruitful for the readers to find a sustainable solution in an industrialized society