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

A Novel Reconfiguration Scheme in Quantum-Dot Cellular Automata for Energy Efficient Nanocomputing

Quantum-Dot Cellular Automata (QCA) is currently being investigated as an alternative to CMOS technology. There has been extensive study on a wide range of circuits from simple logical circuits such as adders to complex circuits such as 4-bit processors. At the same time, little if any work has been done in considering the possibility of reconfiguration to reduce power in QCA devices. This work presents one of the first such efforts when considering reconfigurable QCA architectures which are expected to be both robust and power efficient. We present a new reconfiguration scheme which is highly robust and is expected to dissipate less power with respect to conventional designs. An adder design based on the reconfiguration scheme will be presented in this thesis, with a detailed power analysis and comparison with existing designs. In order to overcome the problems of routing which comes with reconfigurability, a new wire crossing mechanism is also presented as part of this thesis

Performance analysis of fault-tolerant nanoelectronic memories

Performance growth in microelectronics, as described by Moore’s law, is steadily approaching its limits. Nanoscale technologies are increasingly being explored as a practical solution to sustaining and possibly surpassing current performance trends of microelectronics. This work presents an in-depth analysis of the impact on performance, of incorporating reliability schemes into the architecture of a crossbar molecular switch nanomemory and demultiplexer. Nanoelectronics are currently in their early stages, and so fabrication and design methodologies are still in the process of being studied and developed. The building blocks of nanotechnology are fabricated using bottom-up processes, which leave them highly susceptible to defects. Hence, it is very important that defect and fault-tolerant schemes be incorporated into the design of nanotechnology related devices. In this dissertation, we focus on the study of a novel and promising class of computer chip memories called crossbar molecular switch memories and their demultiplexer addressing units. A major part of this work was the design of a defect and fault tolerance scheme we called the Multi-Switch Junction (MSJ) scheme. The MSJ scheme takes advantage of the regular array geometry of the crossbar nanomemory to create multiple switches in the fabric of the crossbar nanomemory for the storage of a single bit. Implementing defect and fault tolerant schemes come at a performance cost to the crossbar nanomemory; the challenge becomes achieving a balance between device reliability and performance. We have studied the reliability induced performance penalties as they relate to the time (delay) it takes to access a bit, and the amount of power dissipated by the process. Also, MSJ was compared to the banking and error correction coding fault tolerant schemes. Studies were also conducted to ascertain the potential benefits of integrating our MSJ scheme with the banking scheme. Trade-off analysis between access time delay, power dissipation and reliability is outlined and presented in this work. Results show the MSJ scheme increases the reliability of the crossbar nanomemory and demultiplexer. Simulation results also indicated that MSJ works very well for smaller nanomemory array sizes, with reliabilities of 100% for molecular switch failure rates in the 10% or less range

Designing memory cells with a novel approaches based on a new multiplexer in QCA Technology

Transistor-based CMOS technology has many drawbacks such that it cannot continue to follow the scaling of Moore’s law in the near future. These drawbacks lead researchers to think about alternatives. Quantum-dot Cellular Automata (QCA) is a nanotechnology that has unique features in terms of size and power consumption. QCA has the ability to represent binary numbers by electrons configuration. The memory circuit is a very important part of the digital system. In QCA technology, there are many approaches presented to accomplish memory cells in both RAM and CAM types. CAM is a type of memory used in high-speed applications. In this thesis, novel approaches to design memory cells are proposed. The proposed approaches are based on a 2:1 multiplexer. Using the proposed approach of RAM cell, a singular form of RAM cell (SFRAMC) is accomplished. In QCA technology, researchers strive to design electronic circuits with an emphasis on minimizing important metrics such as cell count, area, delay, cost and power consumption. The SFRAMC demonstrated significant improvements, with a reduction cell count, occupied area and power consumption by 25%, 24% and 36%. In terms of implementation cost, the SFRAMC saves 43% of the cost when compared to the previous best design. On the other hand, by using the proposed approach of CAM cell, two different structures of the QCA-CAM cell have been introduced. The first proposed CAM cell (FPCAMC) gives improvements in terms of cell count, and delay by 15% and 17% respectively. The second proposed CAM cell (SPCAMC) gives improvements in terms of cell count, and delay by 6% and 17% respectively. In terms of total power consumption, both FPCAMC and SPCAMC have an improvement of about 53% over the best-reported design. The above features of the proposed memory cells (RAM and CAM) could pave the road for designing energy-efficient and cost-efficient memory circuits in the future

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

Fault tolerance issues in nanoelectronics

The astonishing success story of microelectronics cannot go on indefinitely. In fact, once devices reach the few-atom scale (nanoelectronics), transient quantum effects are expected to impair their behaviour. Fault tolerant techniques will then be required. The aim of this thesis is to investigate the problem of transient errors in nanoelectronic devices. Transient error rates for a selection of nanoelectronic gates, based upon quantum cellular automata and single electron devices, in which the electrostatic interaction between electrons is used to create Boolean circuits, are estimated. On the bases of such results, various fault tolerant solutions are proposed, for both logic and memory nanochips. As for logic chips, traditional techniques are found to be unsuitable. A new technique, in which the voting approach of triple modular redundancy (TMR) is extended by cascading TMR units composed of nanogate clusters, is proposed and generalised to other voting approaches. For memory chips, an error correcting code approach is found to be suitable. Various codes are considered and a lookup table approach is proposed for encoding and decoding. We are then able to give estimations for the redundancy level to be provided on nanochips, so as to make their mean time between failures acceptable. It is found that, for logic chips, space redundancies up to a few tens are required, if mean times between failures have to be of the order of a few years. Space redundancy can also be traded for time redundancy. As for memory chips, mean times between failures of the order of a few years are found to imply both space and time redundancies of the order of ten

Majority-based Synthesis for Nanotechnologies

We study the logic synthesis of emerging nanotechnologies whose elementary devices abstraction is a majority voter. We argue that synthesis tools, natively supporting the majority logic abstraction, are the technology enablers. This is because they allow designers to validate majority-based nanotechnologies on large-scale benchmarks. We describe models and data-structures for logic design with majority-based nanotechnologies and we show results of applying new synthesis algorithms and tools. We conclude that new logic synthesis methods are required to achieve a fair assessment on emerging nanotechnologies

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

Energy efficient hybrid computing systems using spin devices

Emerging spin-devices like magnetic tunnel junctions (MTJ\u27s), spin-valves and domain wall magnets (DWM) have opened new avenues for spin-based logic design. This work explored potential computing applications which can exploit such devices for higher energy-efficiency and performance. The proposed applications involve hybrid design schemes, where charge-based devices supplement the spin-devices, to gain large benefits at the system level. As an example, lateral spin valves (LSV) involve switching of nanomagnets using spin-polarized current injection through a metallic channel such as Cu. Such spin-torque based devices possess several interesting properties that can be exploited for ultra-low power computation. Analog characteristic of spin current facilitate non-Boolean computation like majority evaluation that can be used to model a neuron. The magneto-metallic neurons can operate at ultra-low terminal voltage of ∼20mV, thereby resulting in small computation power. Moreover, since nano-magnets inherently act as memory elements, these devices can facilitate integration of logic and memory in interesting ways. The spin based neurons can be integrated with CMOS and other emerging devices leading to different classes of neuromorphic/non-Von-Neumann architectures. The spin-based designs involve `mixed-mode\u27 processing and hence can provide very compact and ultra-low energy solutions for complex computation blocks, both digital as well as analog. Such low-power, hybrid designs can be suitable for various data processing applications like cognitive computing, associative memory, and currentmode on-chip global interconnects. Simulation results for these applications based on device-circuit co-simulation framework predict more than ∼100x improvement in computation energy as compared to state of the art CMOS design, for optimal spin-device parameters