The continuation of the remarkable exponential increases in processing power over the recent past faces imminent challenges due in part to the physics of deep-submicron CMOS devices and the costs of both chip masks and future fabrication plants. A promising solution to these problems is offered by an alternative to CMOS-based computing, chemically assembled electronic nanotechnology (CAEN). In this paper we outline how CAEN-based computing can become a reality. We briefly describe recent work in CAEN and how CAEN will affect computer architecture. We show how the inherently reconfigurable nature of CAEN devices can be exploited to provide high-density chips with defect tolerance at significantly reduced manufacturing costs. We develop a layered abstract architecture for CAEN-based computing devices and we present preliminary results which indicate that such devices will be competitive with CMOS circuits.

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Quantum theory has found a new field of applications in the realm of information and computation during the recent years. This paper reviews how quantum physics allows information coding in classically unexpected and subtle nonlocal ways, as well as information processing with an efficiency largely surpassing that of the present and foreseeable classical computers. Some outstanding aspects of classical and quantum information theory will be addressed here. Quantum teleportation, dense coding, and quantum cryptography are discussed as a few samples of the impact of quanta in the transmission of information. Quantum logic gates and quantum algorithms are also discussed as instances of the improvement in information processing by a quantum computer. We provide finally some examples of current experimental

Hypercomputation or super-Turing computation is a “computation ” that transcends the limit imposed by Turing’s model of computability. The field still faces some basic questions, technical (can we mathematically and/or physically build a hypercomputer?), cognitive (can hypercomputers realize the AI dream?), philosophical (is thinking more than computing?). The aim of this paper is to address the question: can we mathematically build a hypercomputer? We will discuss the solutions of the Infinite Merchant Problem, a decision problem equivalent to the Halting Problem, based on results obtained in [9, 2]. The accent will be on the new computational technique and results rather than formal proofs. 1

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The mathematical technique of randomization yielding probabilistic algorithms is shown, for the first time, through a physical interpretation based on statistical thermodynamics, to be a basis for energy savings in computing. Concretely, at the fundamental limit, it is shown that the energy needed to compute a single probabilistic bit or PBIT is proportional to the probability p of computing a PBIT accurately. This result is established through the introduction of an idealized switch, for computing a PBIT, using which a network of switches can be constructed. Interesting examples of such networks including AND, OR and NOT gates (or as functions, boolean conjunction, disjunction and negation respectively), are constructed and the potential for energy savings through randomization is established. To quantify these savings, novel measures of "technology independent" energy complexity are introduced---these parallel conventional machine-independent measures of computational complexity such as the algorithm's running time. Networks of switches can be shown to be equivalent to Turing machines and to boolean circuits, both of which are widely-known and well-understood models of computation. These savings are realized using a novel way of representing a PBIT in the physical domain through a group of classical microstates. A measurement and thus detection of a microstate yields the value of the PBIT. While the eventual goal of this work is to lead to the physical realization of these theoretical constructs through the innovation of randomized (CMOS based) devices, the current goal is to rigorously establish the potential for energy savings through probabilistic computing at a fundamental physical level, based on the canonical thermodynamic models of idealized monoa...

: Finite computing agents that interact with an environment are shown to be more expressive than Turing machines according to a notion of expressiveness that measures problem-solving ability and is specified by observation equivalence. Sequential interactive models of objects, agents, and embedded systems are shown to be more expressive than algorithms. Multi-agent (distributed) models of coordination, collaboration, and true concurrency are shown to be more expressive than sequential models. The technology shift from algorithms to interaction is expressed by a mathematical paradigm shift that extends inductive definition and reasoning methods for finite agents to coinductive methods of set theory and algebra. An introduction to models of interactive computing is followed by an account of mathematical models of sequential interaction in terms of coinductive methods of non-well-founded set theory, coalgebras, and bisimulation. Models of distributed information flow and multi-agent inter...

A previously developed quantum search algorithm for solving 1-SAT problems in a single step is generalized to apply to a range of highly constrained k-SAT problems. We identify a bound on the number of clauses in satisfiability problems for which the generalized algorithm can find a solution in a constant number of steps as the number of variables increases. This performance contrasts with the linear growth in the number of steps required by the best classical algorithms, and the exponential number required by classical and quantum methods that ignore the problem structure. In some cases, the algorithm can also guarantee that insoluble problems in fact have no solutions, unlike previously proposed quantum search algorithms. 1. Introduction Quantum computers (Benioff, 1982; Bernstein & Vazirani, 1993; Deutsch, 1985, 1989; DiVincenzo, 1995; Feynman, 1986; Lloyd, 1993) offer a new approach to combinatorial search problems (Garey & Johnson, 1979) with quantum parallelism, i.e., the abilit...

Krishna V. Palem Center for Research in Embedded Systems and Technology School of Electrical and Computer Engineering Georgia Institute of Technology 777 Atlantic Drive Atlanta, Georgia, USA.

Energy dissipation associated with logic operations imposes a fundamental physical limit on computation and is generated by the entropic cost of information erasure, which is a consequence of irreversible logic elements. We show how to encode information in DNA and use DNA amplification to implement a logically reversible gate that comprises a complete set of operators capable of universal computation. We also propose a method using this design to connect, or 'wire', these gates together in a biochemical fashion to create a logic network, allowing complex parallel computations to be executed. The architecture of the system permits highly parallel operations and has properties that resemble well known genetic regulatory systems. Logically reversible operations occupy a central role in considerations of the fundamental physical limits of information handling (1). The early work of Landauer (2) showed that energy dissipation occurs during the destruction of information of the previous st...