Aspects of systems and circuits for nanoelectronics

A large number of devices, a limitation of wiring, and very low power dissipation density are design constraints of future nanoelectronic circuits composed of quantum-effect devices. Furthermore, functional integration, which is the possibility of exploiting quantum effects to obtain a function specific behavior, becomes a core design principle. This paper analyzes the effect of this technological progress on the design of nanoelectronic circuits and describes computational paradigms revealing novel features such as distributed storage, fault tolerance, self-organization, and local processing. In particular, linear threshold networks, the associative matrix, self-organizing feature maps, and cellular arrays are investigated from the viewpoint of their potential significance for nanoelectronics. Although these concepts have already been implemented using present technologies, the intention of this paper is to give an impression of their usefulness to system implementations with quantum-effect devices.

[1]  Masahiro Asada,et al.  Theoretical and measured characteristics of metal (CoSi/sub 2/)-insulator(CaF/sub 2/) resonant tunneling transistors and the influence of parasitic elements , 1995 .

[2]  Karl Goser,et al.  Robot Learning in Analog Neural Hardware , 1996, ICANN.

[3]  Yong Yao,et al.  Model of biological pattern recognition with spatially chaotic dynamics , 1990, Neural Networks.

[4]  Robert W. Keyes,et al.  Physics of digital devices , 1989 .

[5]  R. Feynman.  Quantum mechanical computers , 1986 .

[6]  Karl Goser.  Tunneling and thermal noise as limiting factors in microelectronics , 1988 .

[7]  Schmutz,et al.  Robust competitive networks. , 1992, Physical review. A, Atomic, molecular, and optical physics.

[8]  L. Esaki,et al.  Resonant tunneling in semiconductor double barriers , 1974 .

[9]  Bernabe Linares-Barranco,et al.  A CMOS Implementation of Fitzhugh-Nagumo Neuron Model , 1990, ESSCIRC '90: Sixteenth European Solid-State Circuits Conference.

[10]  M. Conrad.  The lure of molecular computing: While marketable products seem decades away, researchers are crystallizing theories and devices that will give biological organisms the power to compute , 1986, IEEE Spectrum.

[11]  Klaus Sutner,et al.  Computation theory of cellular automata , 1998 .

[12]  John H. Davies,et al.  The Smallest Electronic Device: An Electron Waveguide , 1994 .

[13]  Hermann Haken,et al.  Information and Self-Organization: A Macroscopic Approach to Complex Systems , 2010 .

[14]  E. Capaldi,et al.  The organization of behavior. , 1992, Journal of applied behavior analysis.

[15]  R. Landauer,et al.  Need for critical assessment , 1996 .

[16]  Wolfgang Banzhaf,et al.  Self-Replicating Sequences of Binary Numbers: The Build-Up of Complexity , 1994, Complex Syst..

[17]  Koichi Maezawa,et al.  Analysis of Switching Time of Monostable-Bistable Transition Logic Elements Based on Simple Model Calculation , 1995 .

[18]  G. Whitesides,et al.  Molecular self-assembly and nanochemistry: a chemical strategy for the synthesis of nanostructures. , 1991, Science.

[19]  K. Likharev.  Correlated discrete transfer of single electrons in ultrasmall tunnel junctions , 1988 .

[20]  Naoki Yokoyama,et al.  Logic circuits using resonant-tunneling hot-electron transistors (RHETs) , 1992 .

[21]  H. C. Lin,et al.  Resonant tunneling diodes for multi-valued digital applications , 1994, Proceedings of 24th International Symposium on Multiple-Valued Logic (ISMVL'94).

[22]  稲井 基彦.  Quantum effect devices , 1994 .

[23]  Teuvo Kohonen,et al.  The self-organizing map , 1990, Neurocomputing.

[24]  Karl H. Pribram,et al.  Rethinking neural networks : quantum fields and biological data , 1993 .

[25]  Pellizzari,et al.  Stabilization of quantum states in quantum-optical systems. , 1996, Physical review. A, Atomic, molecular, and optical physics.

[26]  Stamatis Vassiliadis,et al.  Block Save Addition with Threshold Gates , 1995 .

[27]  M. Mehring,et al.  Concepts of Molecular Information Storage , 1989 .

[28]  Klaus Schumacher,et al.  VLSI technologies for artificial neural networks , 1989, IEEE Micro.

[29]  Hubert Harrer.  Discrete time cellular neural networks , 1992, Int. J. Circuit Theory Appl..

[30]  R. Douglas,et al.  A silicon neuron , 1991, Nature.

[31]  T. Beth,et al.  Codes for the quantum erasure channel , 1996, quant-ph/9610042.

[32]  C.J.M. Verhoeven,et al.  Single electron tunneling technology for neural networks , 1996, Proceedings of Fifth International Conference on Microelectronics for Neural Networks.

[33]  H. T. Kung.  Why systolic architectures? , 1982, Computer.

[34]  Kevin J. Chen,et al.  Reset-set flipflop based on a novel approach of modulating resonant-tunnelling current with FET gates , 1994 .

[35]  Jehoshua Bruck,et al.  Neural computation of arithmetic functions , 1990 .

[36]  W.C.B. Peatman,et al.  Novel resonant tunneling transistor with high transconductance at room temperature , 1994, IEEE Electron Device Letters.

[37]  K.J. Chen,et al.  Monolithic integration of resonant tunneling diodes and FET's for monostable-bistable transition logic elements (MOBILE's) , 1995, IEEE Electron Device Letters.

[38]  Mark A. Reed,et al.  Realization of a three-terminal resonant tunneling device: The bipolar quantum resonant tunneling transistor , 1989 .

[39]  S. Cotofana,et al.  Block Save Addition with Telescopic SumsS , 1995 .

[40]  Delsing,et al.  Single-electron charging effects in one-dimensional arrays of ultrasmall tunnel junctions. , 1989, Physical review letters.

[41]  Ahmed Louri,et al.  3D optical interconnects for high-speed interchip and interboard communications , 1994, Computer.

[42]  Lutz J. Micheel,et al.  Multiple-valued logic computation circuits using micro- and nanoelectronic devices , 1993, [1993] Proceedings of the Twenty-Third International Symposium on Multiple-Valued Logic.

[43]  A. W. Wieder.  Status, trends and challenges in microelectronics for the next 10 to 15 years , 1996 .

[44]  Trevor Clarkson,et al.  VLSI Design of Neural Networks , 1992 .

[45]  José Luis Huertas Díaz,et al.  A CMOS Implementation of Fitzhugh-Nagumo Neuron Model , 1990 .

[46]  U. Meirav,et al.  Single-electron phenomena in semiconductors , 1996 .

[47]  K. Goser,et al.  A Chip for Selforganizing Feature Maps , 1994 .

[48]  S. Wolfram,et al.  Two-dimensional cellular automata , 1985 .

[49]  Eric A. Vittoz,et al.  Analog VLSI signal processing: Why, where, and how? , 1994, J. VLSI Signal Process..

[50]  T. Mizutani,et al.  Weighted sum threshold logic operation of MOBILE (monostable-bistable transition logic element) using resonant-tunneling transistors , 1993, IEEE Electron Device Letters.

[51]  A. Seabaugh,et al.  Nine-state resonant tunneling diode memory , 1992, IEEE Electron Device Letters.

[52]  S. Kawai,et al.  Optical computing and interconnects , 1996, Proc. IEEE.

[53]  Roberto Serra,et al.  Complex Systems and Cognitive Processes , 1990, Springer Berlin Heidelberg.

[54]  Leon O. Chua,et al.  The CNN paradigm , 1993 .

[55]  Kenneth Showalter,et al.  Nonlinear Chemical Dynamics: Oscillations, Patterns, and Chaos , 1996 .

[56]  J. Austin.  Associative memory , 1987 .

[57]  Leon O. Chua,et al.  Cellular neural networks: applications , 1988 .

[58]  Tadahiro Ohmi,et al.  An intelligent MOS transistor featuring gate-level weighted sum and threshold operations , 1991, International Electron Devices Meeting 1991 [Technical Digest].

[59]  S. Esener,et al.  A scalable optoelectronic neural system using free-space optical interconnects , 1992, IEEE Trans. Neural Networks.

[60]  Karl F. Goser,et al.  Implementation of artificial neural networks into hardware: concepts and limitations , 1996 .

[61]  Robert J. Safranek,et al.  Signal compression based on models of human perception , 1993, Proc. IEEE.

[62]  Carver Mead,et al.  Analog VLSI and neural systems , 1989 .

[63]  Ming-Huei Shieh,et al.  A multiple-dimensional multiple-state SRAM cell using resonant tunneling diodes , 1994, IEEE J. Solid State Circuits.

[64]  T. Toffoli,et al.  Conservative logic , 2002, Collision-Based Computing.

[65]  Kristof Sienicki,et al.  Molecular electronics and molecular electronic devices , 1993 .

[66]  Lars Thylén,et al.  Analysis of an electron‐wave Y‐branch switch , 1992 .

[67]  Stephen Wolfram,et al.  Approaches to complexity engineering , 1986 .

[68]  W. Freeman.  The physiology of perception. , 1991, Scientific American.

[69]  K. Goser,et al.  Analog VLSI cellular fuzzy automata networks for relaxation labeling , 1994, Proceedings of the Fourth International Conference on Microelectronics for Neural Networks and Fuzzy Systems.

[70]  Gérard Weisbuch,et al.  Complex Systems Dynamics , 1994 .

[71]  Werner Weber,et al.  On the application of the Neuron MOS transistor principle for modern VLSI design , 1996 .

[72]  Lin-Bao Yang,et al.  Cellular neural networks: theory , 1988 .

[73]  Arnold Rosenblum.  The Quantum Mechanical Computer , 1991 .

[74]  A. Seabaugh,et al.  Coupled-quantum-well field-effect resonant tunneling transistor for multi-valued logic/memory applications , 1994 .

[75]  H.J. Levy,et al.  A feedforward artificial neural network based on quantum effect vector-matrix multipliers , 1993, IEEE Trans. Neural Networks.

[76]  Nabil H. Farhat,et al.  The transversal imager: a photonic neurochip with programmable synaptic weights , 1995, IEEE Trans. Neural Networks.

[77]  T.L. Lee,et al.  P-N double quantum well resonant interband tunneling diode with peak-to-valley current ratio of 144 at room temperature , 1994, IEEE Electron Device Letters.

[78]  T. Adachihara,et al.  Logic circuits using resonant-tunneling hot electron transistors (RHETs) , 1991, [1991] GaAs IC Symposium Technical Digest.

[79]  John von Neumann,et al.  Theory Of Self Reproducing Automata , 1967 .

[80]  Lipo Wang,et al.  Artificial neural networks - oscillations, chaos, and sequence processing , 1993 .

[81]  R W Keyes,et al.  What Makes a Good Computer Device? , 1985, Science.

[82]  J. Hopfield,et al.  Computing with neural circuits: a model. , 1986, Science.