scholarly journals Σχεδιασμός και προσομοίωση νανοηλεκτρικών κυκλωμάτων κβαντικών κυψελιδωτών αυτομάτων

2011 ◽  
Author(s):  
Βασίλειος Μαρδύρης

In last decades exponential reduction of integrated circuits feature size and increase in operating frequency was achieved in VLSI fabrication industry using the conventional CMOS technology. However the CMOS technology faces serious challenges as the CMOS transistor reaches its physical limits, such as ultra thin gate oxides, short channel effects, doping fluctuations and increased difficulty and consequently increased lithography cost in the nanometer scale. It is projected that the CMOS technology, in its present state will reach its limits when the transistors channel length reaches approximatly 7 nm, probably near 2019. Emerging technologies have been a topic of great interest in the last few years. The emerging technologies in nanoelectronics provide new computing possibilities that arise from their extremely reduced feature sizes. Quantum Cellular Automata (QCA) is one of the most promising emerging technologies in the fast growing area of nanoelectronics. QCA relies mostly on Coulombic interactions and uses innovative processing techniques which are very different from the CMOS-based model. QCAs are not only a new nanoelectronic model but also provide a new method of computation and information process. In QCA circuits computation and data transfer occurs simultaneously. Appling the QCA technology, the elementary building component (QCA cells) cover an area of a few nanometers. For this feature sizes the integration can reach values of 1012 cells/cm2 and the circuit switching frequency the THz level. The implementation of digital logic using QCA nanoelectronic circuits not only drives the already developed systems based on conventional technology to the nanoelectronic era but improves their performance significantly. At the present Ph.D. thesis, a study of QCA circuit clocking schemes is presented showing how these schemes contribute to the robustness of QCA circuits. A novel design of a QCA 2 to 1 multiplexer is presented. The QCA circuit is simulated and its operation is analyzed. A modular design and simulation methodology is developed for the first time. This methodology can be used to design 2n to 1 QCA multiplexers using the 2 to 1 QCA multiplexer as a building block. The design methodology is formulated in order to increase the circuit stability.Furthermore in this Ph.D. thesis, a novel design of a small size, modular quantum-dot cellular automata (QCA) 2n to 1 multiplexer is proposed, These multiplexers can be used for memory addressing. The design objective is to develop an evolving modular design methodology which can produce QCA 2n to 1 multiplexer circuits, improved in terms of circuit area and operating frequency. In these implementations the circuit stability was a major issue and was considered carefully. In the recent years, Cellular Automata (CAs) have been widely used in order to model and simulate physical systems and also to solve scientific problems. CAs have also been successfully used as a VLSI architecture and proved to be very efficient in terms of silicon-area utilization and clock-speed maximization. In the present Ph.D. thesis a design methodology is developed for the first time, which can be used to design CA models using QCA circuitry. The implementation of CAs using QCA nanoelectronic circuits significantly improves their performance due to the unique properties of the nanoelectronic circuits. In this Ph.D. thesis a new CAD system we develope for the first time, and was named Design Automation Tool of 1-D Cellular Automata using Quantum Cellular Automata (DATICAQ), that builds a bridge between one-dimensional CAs as models of physical systems and processes and one-dimensional CAs as a nanoelectronic architecture. The CAD system inputs are the CA dimensionality, size, local rule, and the initial and boundary conditions imposed by the particular problem. DATICAQ produces as output the layout of the QCA implementation of the particular one-dimensional CA model. The proposed system also provides the simulation input vectors and their corresponding outputs, in order to simplify the simulation process. No prior knowledge of QCA circuit designing is required by the user. DATICAQ has been tested for a large number of QCA circuits. Paradigms of QCA circuits implementing CA models for zero and periodic boundary conditions are presented in the thesis. Simulations of CA models and the corresponding QCA circuits showed that the CA rules and models have been successfully implemented. At the present Ph.D. thesis, the design of large scale QCA circuits is analyzed and a study of the problems arising on complex algorithm implementation using QCAs is presented. One of the most important problems of the large scale QCA circuits is the synchronization of the internal signals of the circuit between the subsystems of the large QCA circuit. This problem becomes more difficult when the circuit includes signal loops. In the present thesis a methodology and a QCA circuit is presented for the first time, which solves the above mentioned synchronization problem. The QCA circuit implements the Firing Squad Synchronization Algorithm proposed by Mazoyer in order to solve the synchronization problem. The implementation was obtained using a one-dimensional 3-bit digital CA model. The QCA circuit is simulated and its operation is analyzed.

Author(s):  
Yuliya Tanasyuk ◽  
Petro Burdeinyi

The given paper is devoted to the software development of block cipher based on reversible one-dimensional cellular automata and the study of its statistical properties. The software implementation of the proposed encryption algorithm is performed in C# programming language in Visual Studio 2017. The paper presents specially designed approach for key generation. To ensure desired cryptographic stability, the shared secret parameters can be adjusted to contain information needed for creating substitution tables, defining reversible rules, and hiding final data. For the first time, it is suggested to create substitution tables based on iterations of a cellular automaton that is initialized by the key data.


2021 ◽  
Author(s):  
Ajay Singh ◽  
Vivek Saraswat ◽  
Maryam Shojaei Baghini ◽  
Udayan Ganguly

Abstract Low-power and low-area neurons are essential for hardware implementation of large-scale SNNs. Various novel physics based leaky-integrate-and-fire (LIF) neuron architectures have been proposed with low power and area, but are not compatible with CMOS technology to enable brain scale implementation of SNN. In this paper, for the first time, we demonstrate hardware implementation of LSM reservoir using band-to-band-tunnelling (BTBT) based neuron. A low-power thresholding circuit and current-to-voltage converter design are proposed. We further propose a predistortion technique to linearize a nonlinear neuron without any area and power overhead. We establish the equivalence of the proposed neuron with the ideal LIF neuron to demonstrate its versatility. To verify the effect of the proposed neuron, a 36-neuron LSM reservoir is fabricated in GF-45nm PDSOI technology. We achieved 5000x lower energy-per-spike at a similar area, 50x less area at a similar energy-per-spike, and 10x lower standby power at a similar area and energy-per-spike. Such overall performance improvement enables brain scale computing.


2010 ◽  
Vol 19 (02) ◽  
pp. 349-365 ◽  
Author(s):  
VASILIOS A. MARDIRIS ◽  
IOANNIS G. KARAFYLLIDIS

Multiplexers are extremely important parts of signal control systems. Some critical circuits of computing systems, like memories, use large multiplexers in order to present the value of a specific memory cell to their output. Several quantum-dot cellular automata (QCA) circuits have been designed and the need for a QCA memory access system becomes prominent. A modular 2n to 1 QCA multiplexer covering small area could reduce the size of such circuits and conclusively could increase circuit integration. In this paper we present a novel design of a small size, modular quantum-dot cellular automata (QCA) 2n to 1 multiplexer that can be used for memory addressing. The design objective is to develop a modular design methodology which can be used to implement 2n to 1 multiplexers using building blocks. For the QCA implementation a careful consideration is taken into account concerning the design in order to increase the circuit stability.


2019 ◽  
Vol 8 (2S11) ◽  
pp. 2853-2857

This article presents the design of high-speed adders using Quantum cellular automata. Quantum Automata is an efficient evaluation platform than CMOS in nanotechnology. Power, surface and performance play a virtual role in nanotechnology. Quantum Automata is an emerging technology in nanotechnology. QCA provides more speed, less power consumption and large scale integration in VLSI. By using Quantum-Dot cellular automata, we can reduce the power of leaks. Generally, for transferring the data and store data, electric fields are used in CMOS technology but in QCA, storing the data and transfer the data done by electronic polarization. This article presents different combinational logic circuits depend on QCA technology. The proposed modified CSLA (carry select adder) offer the best results of delay compared to the Ripple carry adder (RCA).


2010 ◽  
Vol 1 (3) ◽  
pp. 66-84 ◽  
Author(s):  
Predrag T. Tošic

In this paper, cellular automata (CA) are viewed as an abstract model for distributed computing. The author argues that the classical CA model must be modified in several important respects to become a relevant model for large-scale MAS. The paper first proposes sequential cellular automata (SCA) and formalizes deterministic and nondeterministic versions of SCA. The author then analyzes differences in possible dynamics between classical parallel CA and various SCA models. The analysis in this paper focuses on one-dimensional parallel and sequential CA with node update rules restricted to simple threshold functions, as arguably the simplest totalistic, yet non-linear (and non-affine) update rules. The author identifies properties of asymptotic dynamics that can be proven to be entirely due to the assumption of perfect synchrony in classical, parallel CA. Finally, the paper discusses what an appropriate CA-based abstraction would be for large-scale distributed computing, insofar as the inter-agent communication models. In that context, the author proposes genuinely asynchronous CA and discusses main differences between genuinely asynchronous CA and various weakly asynchronous sequential CA models found in the literature.


2005 ◽  
Vol 77 (5) ◽  
pp. 369-375 ◽  
Author(s):  
Abdurrahman Hacioğlu

PurposeTo propose a robust and more effective algorithm for aerodynamic design optimization problem by using neural network.Design/methodology/approachNeural network and genetic algorithm (GA) are hybridized in a new way, and quasi one‐dimensional Euler equations are solved for internal flow in the nozzle.FindingsThe results indicate that the nozzle design can be performed successfully and quickly by using the implemented algorithm. It is observed that using the method decreased CFD solver calls about 21 and 46 per cent for transonic and supersonic flow, respectively.Originality/valueIt is the first time that the neural network is used for the candidate solution in the GA.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yupeng Zhou ◽  
Mengyu Zhao ◽  
Mingjie Fan ◽  
Yiyuan Wang ◽  
Jianan Wang

PurposeThe set-union knapsack problem is one of the most significant generalizations of the Non-deterministic Polynomial (NP)-hard 0-1 knapsack problem in combinatorial optimization, which has rich application scenarios. Although some researchers performed effective algorithms on normal-sized instances, the authors found these methods deteriorated rapidly as the scale became larger. Therefore, the authors design an efficient yet effective algorithm to solve this large-scale optimization problem, making it applicable to real-world cases under the era of big data.Design/methodology/approachThe authors develop three targeted strategies and adjust them into the adaptive tabu search framework. Specifically, the dynamic item scoring tries to select proper items into the knapsack dynamically to enhance the intensification, while the age-guided perturbation places more emphasis on the diversification of the algorithm. The lightweight neighborhood updating simplifies the neighborhood operators to reduce the algorithm complexity distinctly as well as maintains potential solutions. The authors conduct comparative experiments against currently best solvers to show the performance of the proposed algorithm.FindingsStatistical experiments show that the proposed algorithm can find 18 out of 24 better solutions than other algorithms. For the remaining six instances on which the competitor also achieves the same solutions, ours performs more stably due to its narrow gap between best and mean value. Besides, the convergence time is also verified efficiency against other algorithms.Originality/valueThe authors present the first implementation of heuristic algorithm for solving large-scale set-union knapsack problem and achieve the best results. Also, the authors provide the benchmarks on the website for the first time.


2019 ◽  
Vol 18 (2) ◽  
pp. 66-70
Author(s):  
Boris Altemeyer

Purpose This paper aims to analyse two large-scale business case studies for the benefits of using AI, computer science and machine learning to assess, recruit and retain staff. Design/methodology/approach The authors interrogate two large-scale case studies, including metrics on the success of AI in relation to user experience, compatibility, psychometric benchmarking. Findings The authors conclude that AI removes bias from assessment, recruitment and training processes and can save businesses significant time and resources as well as improve the cultural fit and diversity of their recruits. There is a balance to be struck, though, as the systems used are only as good as the science supporting the selection – and humans must ultimately retain the role of decision makers. Originality/value These business case studies are examined in detail for the first time in this paper.


2018 ◽  
Vol 18 (6) ◽  
pp. 6-13
Author(s):  
M. R. Agliullin ◽  
Z. R. Khairullina ◽  
A. V. Faizullin ◽  
A. I. Petrov ◽  
A. A. Badretdinova ◽  
...  

The one-dimensional channel pore system and the moderately strong acid centers inherent in aluminophosphate (AlPO4-11) and silicoaluminophosphate (SAPO-11) molecular sieves make them promising catalyst for hydroisomerization of higher n-paraffins. However, the mechanism of crystallization of these materials is not well understood as yet. XRD,27Al and31P MAS NMR, lowtemperature adsorption-desorption of nitrogen, and SEM techniques were used for the first time for studying the stage crystallization of aluminophosphate AlPO4-11 for commercial boehmite based aluminium source. AlPO4-11 was shown to form via an intermediate phase based on layered crystalline aluminophosphate. It was established that highly crystalline and phase-pure AlPO4-11 was formed at 200 °C during 6 to 24 hours. When the crystallization at 200 °C lasted for more than two days, AlPO4-11 turned into non-porous cristobalite. The results obtained will be used for developing methods for deliberate control of the phase composition and crystallinity of industrially important silicoaluminophosphate sieves SAPO-11 with required properties to develop promising catalysts based thereon for large-scale processes of hydroisomerization of n-paraffins.


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