Quantum-dot Cellular Automata: Review Paper

Quantum-dot Cellular Automata (QCA) is one of the most important discoveries that will be the successful alternative for CMOS technology in the near future. An important feature of this technique, which has attracted the attention of many researchers, is that it is characterized by its low energy consumption, high speed and small size compared with CMOS.  Inverter and majority gate are the basic building blocks for QCA circuits where it can design the most logical circuit using these gates with help of QCA wire. Due to the lack of availability of review papers, this paper will be a destination for many people who are interested in the QCA field and to know how it works and why it had taken lots of attention recentl

Fault and Defect Tolerant Computer Architectures: Reliable Computing With Unreliable Devices

This research addresses design of a reliable computer from unreliable device technologies. A system architecture is developed for a fault and defect tolerant (FDT) computer. Trade-offs between different techniques are studied and yield and hardware cost models are developed. Fault and defect tolerant designs are created for the processor and the cache memory. Simulation results for the content-addressable memory (CAM)-based cache show 90% yield with device failure probabilities of 3 x 10(-6), three orders of magnitude better than non fault tolerant caches of the same size. The entire processor achieves 70% yield with device failure probabilities exceeding 10(-6). The required hardware redundancy is approximately 15 times that of a non-fault tolerant design. While larger than current FT designs, this architecture allows the use of devices much more likely to fail than silicon CMOS. As part of model development, an improved model is derived for NAND Multiplexing. The model is the first accurate model for small and medium amounts of redundancy. Previous models are extended to account for dependence between the inputs and produce more accurate results

Towards FPGA hardware in the loop for QCA simulation

As transistors begin to hit raw physical limits and performance barriers, other technologies are being researched to potentially replace conventional integrated circuit technology. Quantum-dot Cellular Automata (QCA) is one such technology which executes computations using coulomb interactions and quantum-mechanical effects. Part of this research is pursuant to the design of circuits which exploit QCA technology and take advantage of what it has to offer. These circuits must be simulated to ensure their functionality and help prove the viability of QCA. These simulations, like many scientific computing applications, can take a long time to complete; hours or days, depending on their size and complexity. Many scientific applications have benefitted from research into Field Programmable Gate Array (FPGA) application development, which has been used to accelerate the speed at which such simulations execute. This thesis investigates the possibility of using FPGAs to accelerate the simulation of QCA circuits. The hardware developed is a streaming type architecture using floating point arithmetic and hardware/software techniques. Hardware implementation shows the system to run slower than the existing software code, but demonstrates the ability to simulate a small QCA circuit. Analysis of the design reveals good potential for achieving speedup, and an alternate design is proposed to improve the execution time. In the course of this work, improvements to the existing software are also developed and contributed to the community

New Symmetric and Planar Designs of Reversible Full-Adders/Subtractors in Quantum-Dot Cellular Automata

Quantum-dot Cellular Automata (QCA) is one of the emerging nanotechnologies, promising alternative to CMOS technology due to faster speed, smaller size, lower power consumption, higher scale integration and higher switching frequency. Also, power dissipation is the main limitation of all the nano electronics design techniques including the QCA. Researchers have proposed the various mechanisms to limit this problem. Among them, reversible computing is considered as the reliable solution to lower the power dissipation. On the other hand, adders are fundamental circuits for most digital systems. In this paper, Innovation is divided to three sections. In the first section, a method for converting irreversible functions to a reversible one is presented. This method has advantages such as: converting of irreversible functions to reversible one directly and as optimal. So, in this method, sub-optimal methods of using of conventional reversible blocks such as Toffoli and Fredkin are not used, having of minimum number of garbage outputs and so on. Then, Using the method, two new symmetric and planar designs of reversible full-adders are presented. In the second section, a new symmetric, planar and fault tolerant five-input majority gate is proposed. Based on the designed gate, a reversible full-adder are presented. Also, for this gate, a fault-tolerant analysis is proposed. And in the third section, three new 8-bit reversible full-adder/subtractors are designed based on full-adders/subtractors proposed in the second section. The results are indicative of the outperformance of the proposed designs in comparison to the best available ones in terms of area, complexity, delay, reversible/irreversible layout, and also in logic level in terms of garbage outputs, control inputs, number of majority and NOT gates

New Symmetric and Planar Designs of Reversible Full-Adders/Subtractors in Quantum-Dot Cellular Automata

Quantum-dot Cellular Automata (QCA) is one of the emerging nanotechnologies, promising alternative to CMOS technology due to faster speed, smaller size, lower power consumption, higher scale integration and higher switching frequency. Also, power dissipation is the main limitation of all the nano electronics design techniques including the QCA. Researchers have proposed the various mechanisms to limit this problem. Among them, reversible computing is considered as the reliable solution to lower the power dissipation. On the other hand, adders are fundamental circuits for most digital systems. In this paper, Innovation is divided to three sections. In the first section, a method for converting irreversible functions to a reversible one is presented. This method has advantages such as: converting of irreversible functions to reversible one directly and as optimal. So, in this method, sub-optimal methods of using of conventional reversible blocks such as Toffoli and Fredkin are not used, having of minimum number of garbage outputs and so on. Then, Using the method, two new symmetric and planar designs of reversible full-adders are presented. In the second section, a new symmetric, planar and fault tolerant five-input majority gate is proposed. Based on the designed gate, a reversible full-adder are presented. Also, for this gate, a fault-tolerant analysis is proposed. And in the third section, three new 8-bit reversible full-adder/subtractors are designed based on full-adders/subtractors proposed in the second section. The results are indicative of the outperformance of the proposed designs in comparison to the best available ones in terms of area, complexity, delay, reversible/irreversible layout, and also in logic level in terms of garbage outputs, control inputs, number of majority and NOT gates

A polymorphic hardware platform

In the domain of spatial computing, it appears that platforms based on either reconfigurable datapath units or on hybrid microprocessor/logic cell organizations are in the ascendancy as they appear to offer the most efficient means of providing resources across the greatest range of hardware designs. This paper encompasses an initial exploration of an alternative organization. It looks at the effect of using a very fine-grained approach based on a largely undifferentiated logic cell that can be configured to operate as a state element, logic or interconnect - or combinations of all three. A vertical layout style hides the overheads imposed by reconfigurability to an extent where very fine-grained organizations become a viable option. It is demonstrated that the technique can be used to develop building blocks for both synchronous and asynchronous circuits, supporting the development of hybrid architectures such as globally asynchronous, locally synchronous

Heterogeneous Reconfigurable Fabrics for In-circuit Training and Evaluation of Neuromorphic Architectures

A heterogeneous device technology reconfigurable logic fabric is proposed which leverages the cooperating advantages of distinct magnetic random access memory (MRAM)-based look-up tables (LUTs) to realize sequential logic circuits, along with conventional SRAM-based LUTs to realize combinational logic paths. The resulting Hybrid Spin/Charge FPGA (HSC-FPGA) using magnetic tunnel junction (MTJ) devices within this topology demonstrates commensurate reductions in area and power consumption over fabrics having LUTs constructed with either individual technology alone. Herein, a hierarchical top-down design approach is used to develop the HSCFPGA starting from the configurable logic block (CLB) and slice structures down to LUT circuits and the corresponding device fabrication paradigms. This facilitates a novel architectural approach to reduce leakage energy, minimize communication occurrence and energy cost by eliminating unnecessary data transfer, and support auto-tuning for resilience. Furthermore, HSC-FPGA enables new advantages of technology co-design which trades off alternative mappings between emerging devices and transistors at runtime by allowing dynamic remapping to adaptively leverage the intrinsic computing features of each device technology. HSC-FPGA offers a platform for fine-grained Logic-In-Memory architectures and runtime adaptive hardware. An orthogonal dimension of fabric heterogeneity is also non-determinism enabled by either low-voltage CMOS or probabilistic emerging devices. It can be realized using probabilistic devices within a reconfigurable network to blend deterministic and probabilistic computational models. Herein, consider the probabilistic spin logic p-bit device as a fabric element comprising a crossbar-structured weighted array. The Programmability of the resistive network interconnecting p-bit devices can be achieved by modifying the resistive states of the array\u27s weighted connections. Thus, the programmable weighted array forms a CLB-scale macro co-processing element with bitstream programmability. This allows field programmability for a wide range of classification problems and recognition tasks to allow fluid mappings of probabilistic and deterministic computing approaches. In particular, a Deep Belief Network (DBN) is implemented in the field using recurrent layers of co-processing elements to form an n x m1 x m2 x ::: x mi weighted array as a configurable hardware circuit with an n-input layer followed by i ≥ 1 hidden layers. As neuromorphic architectures using post-CMOS devices increase in capability and network size, the utility and benefits of reconfigurable fabrics of neuromorphic modules can be anticipated to continue to accelerate

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