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The main promise of Quantum Dot Cellular Automata (QCA) as a new computing paradigm is the possbility of implementing a set of universal logic gates and thus feasibility of general-purpose computing.
In the standard cellular-automata model for a fault an element of stress is randomly added to a grid of boxes until a box has four elements, these are then redistributed to the adjacent boxes on the grid. The redistribution can result in one or more of these boxes having four or more elements in which case further redistributions are required. On the average added elements are lost from the edges of the grid. The model is modified so that the boxes have a scale-invariant distribution of sizes. The objective is to model a scale-invariant distribution of fault sizes. When a redistribution from a box occurs it is equivalent to a characteristic earthquake on the fault. A redistribution from a small box (a foreshock) can trigger an instability in a large box (the main shock). A redistribution from a large box always triggers many instabilities in the smaller boxes (aftershocks). The frequency-size statistics for both main shocks and aftershocks satisfy the Gutenberg-Richter relation with b = 0.835 for main shocks and b = 0.635 for aftershocks. Model foreshocks occur 28 percent of the time.
We are developing software to explore the fault tolerance of quantum dot cellular automata gate architectures in the presence of manufacturing variations and device defects. The Topology Optimization Methodology using Applied Statistics (TOMAS) framework extends the capabilities of the A Quantum Interconnected Network Array Simulator (AQUINAS) by adding front-end and back-end software and creating an environment that integrates all of these components. The front-end tools establish all simulation parameters, configure the simulation system, automate the Monte Carlo generation of simulation files, and execute the simulation of these files. The back-end tools perform automated data parsing, statistical analysis and report generation.
As transistor geometries are reduced, quantum effects begin to dominate device performance. At some point, transistors cease to have the properties that make them useful computational components. New computing elements must be developed in order to keep pace with Moore s Law. Quantum dot cellular automata (QCA) represent an alternative paradigm to transistor-based logic. QCA architectures that are robust to manufacturing tolerances and defects must be developed. We are developing software that allows the exploration of fault tolerant QCA gate architectures by automating the specification, simulation, analysis and documentation processes.
There has been significant improvement in the performance of VLSI devices, in terms of size, power consumption, and speed, in recent years and this trend may also continue for some near future. However, it is a well known fact that there are major obstacles, i.e., physical limitation of feature size reduction and ever increasing cost of foundry, that would prevent the long term continuation of this trend. This has motivated the exploration of some fundamentally new technologies that are not dependent on the conventional feature size approach. Such technologies are expected to enable scaling to continue to the ultimate level, i.e., molecular and atomistic size. Quantum computing, quantum dot-based computing, DNA based computing, biologically inspired computing, etc., are examples of such new technologies. In particular, quantum-dots based computing by using Quantum-dot Cellular Automata (QCA) has recently been intensely investigated as a promising new technology capable of offering significant improvement over conventional VLSI in terms of reduction of feature size (and hence increase in integration level), reduction of power consumption, and increase of switching speed. Quantum dot-based computing and memory in general and QCA specifically, are intriguing to NASA due to their high packing density (10(exp 11) - 10(exp 12) per square cm ) and low power consumption (no transfer of current) and potentially higher radiation tolerant. Under Revolutionary Computing Technology (RTC) Program at the NASA/JPL Center for Integrated Space Microelectronics (CISM), we have been investigating the potential applications of QCA for the space program. To this end, exploiting the intrinsic features of QCA, we have designed novel QCA-based circuits for co-planner (i.e., single layer) and compact implementation of a class of data permutation matrices, a class of interconnection networks, and a bit-serial processor. Building upon these circuits, we have developed novel algorithms and QCA-based architectures for highly parallel and systolic computation of signal/image processing applications, such as FFT and Wavelet and Wlash-Hadamard Transforms.
A generalization of the hexagonal lattice gas model of Frisch, Hasslacher and Pomeau is shown to lead to two-dimensional magnetohydrodynamics. The method relies on the ideal point-wise conservation law for vector potential.
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On-line programming for the following topics is discussed: (1) artificial intelligence, (2) automata theory, (3) cellular automata, (4) computation structures, (5) computer systems research, (6) dynamic modeling, computer graphics, and computer networks, (7) education, (8) implicit computation, (10) interactive management systems, (11) interactive algebraic manipulation, and (12) programming languages.
Electronic and optoelectronic hardware implementations of highly parallel computing architectures address several ill-defined and/or computation-intensive problems not easily solved by conventional computing techniques. The concurrent processing architectures developed are derived from a variety of advanced computing paradigms including neural network models, fuzzy logic, and cellular automata. Hardware implementation technologies range from state-of-the-art digital/analog custom-VLSI to advanced optoelectronic devices such as computer-generated holograms and e-beam fabricated Dammann gratings. JPL's concurrent processing devices group has developed a broad technology base in hardware implementable parallel algorithms, low-power and high-speed VLSI designs and building block VLSI chips, leading to application-specific high-performance embeddable processors. Application areas include high throughput map-data classification using feedforward neural networks, terrain based tactical movement planner using cellular automata, resource optimization (weapon-target assignment) using a multidimensional feedback network with lateral inhibition, and classification of rocks using an inner-product scheme on thematic mapper data. In addition to addressing specific functional needs of DOD and NASA, the JPL-developed concurrent processing device technology is also being customized for a variety of commercial applications (in collaboration with industrial partners), and is being transferred to U.S. industries. This viewgraph p resentation focuses on two application-specific processors which solve the computation intensive tasks of resource allocation (weapon-target assignment) and terrain based tactical movement planning using two extremely different topologies. Resource allocation is implemented as an asynchronous analog competitive assignment architecture inspired by the Hopfield network. Hardware realization leads to a two to four order of magnitude speed-up over conventional techniques and enables multiple assignments, (many to many), not achievable with standard statistical approaches. Tactical movement planning (finding the best path from A to B) is accomplished with a digital two-dimensional concurrent processor array. By exploiting the natural parallel decomposition of the problem in silicon, a four order of magnitude speed-up over optimized software approaches has been demonstrated.
Suitably patterned arrays (blocks) of quantum-dot cellular automata (QCA) have been proposed as fault-tolerant universal logic gates. These block QCA gates could be used to realize the potential of QCA for further miniaturization, reduction of power consumption, increase in switching speed, and increased degree of integration of very-large-scale integrated (VLSI) electronic circuits. The limitations of conventional VLSI circuitry, the basic principle of operation of QCA, and the potential advantages of QCA-based VLSI circuitry were described in several NASA Tech Briefs articles, namely Implementing Permutation Matrices by Use of Quantum Dots (NPO-20801), Vol. 25, No. 10 (October 2001), page 42; Compact Interconnection Networks Based on Quantum Dots (NPO-20855) Vol. 27, No. 1 (January 2003), page 32; Bit-Serial Adder Based on Quantum Dots (NPO-20869), Vol. 27, No. 1 (January 2003), page 35; and Hybrid VLSI/QCA Architecture for Computing FFTs (NPO-20923), which follows this article. To recapitulate the principle of operation (greatly oversimplified because of the limitation on space available for this article): A quantum-dot cellular automata contains four quantum dots positioned at or between the corners of a square cell. The cell contains two extra mobile electrons that can tunnel (in the quantummechanical sense) between neighboring dots within the cell. The Coulomb repulsion between the two electrons tends to make them occupy antipodal dots in the cell. For an isolated cell, there are two energetically equivalent arrangements (denoted polarization states) of the extra electrons. The cell polarization is used to encode binary information. Because the polarization of a nonisolated cell depends on Coulomb-repulsion interactions with neighboring cells, universal logic gates and binary wires could be constructed, in principle, by arraying QCA of suitable design in suitable patterns. Heretofore, researchers have recognized two major obstacles to realization of QCA-based logic gates: One is the need for (and the difficulty of attaining) operation of QCA circuitry at room temperature or, for that matter, at any temperature above a few Kelvins. It has been theorized that room-temperature operation could be made possible by constructing QCA as molecular-scale devices. However, in approaching the lower limit of miniaturization at the molecular level, it becomes increasingly imperative to overcome the second major obstacle, which is the need for (and the difficulty of attaining) high precision in the alignments of adjacent QCA in order to ensure the correct interactions among the quantum dots.
Three areas of study in MHD turbulence are considered. These are the turbulent relaxation of the toroidal Z pinch, density fluctuations in MHD fluids, and MHD cellular automata. A Boolean computer game that updates a cellular representation in parallel and that has macroscopic averages converging to solutions of the two-dimensional MHD equations is discussed.
Non-enzymatic, template-directed synthesis of oligonucleotides has been extensively studied in the laboratory as a model to understand the kind of chemical processes that might have contributed to the origin of life on Earth. Several oligonucleotides have been shown to catalyze the synthesis of their complements from activated mononucleotides; however, a restricted number of them have been found to self-replicate. Recently we developed an efficient modified cellular automata method that supports the study of self-replicating oligonucleotides. With this method the oligonucleotide molecules are represented as active cells imbedded in a two-dimensional array of inactive cells symbolizing the environment. Random movements and probability-governed chemical reactions occurring in a cellular space can effectively simulate the experimental behavior observed in self-directed replication of oligonucleotides.
A proposed integrated circuit based on quantum-dot cellular automata (QCA) would function as a bit-serial adder. This circuit would serve as a prototype building block for demonstrating the feasibility of quantum-dots computing and for the further development of increasingly complex and increasingly capable quantum-dots computing circuits. QCA-based bit-serial adders would be especially useful in that they would enable the development of highly parallel and systolic processors for implementing fast Fourier, cosine, Hartley, and wavelet transforms. The proposed circuit would complement the QCA-based circuits described in "Implementing Permutation Matrices by Use of Quantum Dots" (NPO-20801), NASA Tech Briefs, Vol. 25, No. 10 (October 2001), page 42 and "Compact Interconnection Networks Based on Quantum Dots" (NPO-20855), which appears elsewhere in this issue. Those articles described the limitations of very-large-scale-integrated (VLSI) circuitry and the major potential advantage afforded by QCA. To recapitulate: In a VLSI circuit, signal paths that are required not to interact with each other must not cross in the same plane. In contrast, for reasons too complex to describe in the limited space available for this article, suitably designed and operated QCA-based signal paths that are required not to interact with each other can nevertheless be allowed to cross each other in the same plane without adverse effect. In principle, this characteristic could be exploited to design compact, coplanar, simple (relative to VLSI) QCA-based networks to implement complex, advanced interconnection schemes. To enable a meaningful description of the proposed bit-serial adder, it is necessary to further recapitulate the description of a quantum-dot cellular automation from the first-mentioned prior article: A quantum-dot cellular automaton contains four quantum dots positioned at the corners of a square cell. The cell contains two extra mobile electrons that can tunnel (in the quantum-mechanical sense) between neighboring dots within the cell. The Coulomb repulsion between the two electrons tends to make them occupy antipodal dots in the cell. For an isolated cell, there are two energetically equivalent arrangements (denoted polarization states) of the extra electrons. The cell polarization is used to encode binary information. Because the polarization of a nonisolated cell depends on Coulomb-repulsion interactions with neighboring cells, universal logic gates and binary wires could be constructed, in principle, by arraying QCA of suitable design in suitable patterns. Again, for reasons too complex to describe here, in order to ensure accuracy and timeliness of the output of a QCA array, it is necessary to resort to an adiabatic switching scheme in which the QCA array is divided into subarrays, each controlled by a different phase of a multiphase clock signal. In this scheme, each subarray is given time to perform its computation, then its state is frozen by raising its inter-dot potential barriers and its output is fed as the input to the successor subarray. The successor subarray is kept in an unpolarized state so it does not influence the calculation of preceding subarray. Such a clocking scheme is consistent with pipeline computation in the sense that each different subarray can perform a different part of an overall computation. In other words, QCA arrays are inherently suitable for pipeline and, moreover, systolic computations. This sequential or pipeline aspect of QCA would be utilized in the proposed bit-serial adders.
The Massively Parallel Processor (MPP) is an ideal machine for computer experiments with simulated neural nets as well as more general cellular automata. Experiments using the MPP with a formal model neural network are described. The results on problem mapping and computational efficiency apply equally well to the neural nets of Hopfield, Hinton et al., and Geman and Geman.
Cellular automata modeling of the advection of a passive scalar in a two-dimensional flow is examined in the context of discrete lattice kinetic theory. It is shown that if the passive scalar is represented by tagging or 'coloring' automation particles a passive advection-diffusion equation emerges without use of perturbation expansions. For the specific case of the hydrodynamic lattice gas model of Frisch et al. (1986), the diffusion coefficient is calculated by perturbation.
Problem partitioning of regular computation over two dimensional meshes on multiprocessor systems is examined. The regular computation model considered involves repetitive evaluation of values at each mesh point with local communication. The computational workload and the communication pattern are the same at each mesh point. The regular computation model arises in numerical solutions of partial differential equations and simulations of cellular automata. Given a communication pattern, a systematic way to generate a family of partitions is presented. The influence of various partitioning schemes on performance is compared on the basis of computation to communication ratio.
The present class of models for cellular automata involving a quiescent hydrodynamic lattice gas with multiple-valued passive labels termed 'colors', the lattice collisions change individual particle colors while preserving net color. The rigorous proofs of the multicolor lattice gases' essential features are rendered more tractable by an equivalent subparticle representation in which the color is represented by underlying two-state 'spins'. Schemes for the introduction of Dirichlet and Neumann boundary conditions are described, and two illustrative numerical test cases are used to verify the theory. The lattice gas model is equivalent to a Poisson equation solution.