Thermal Switching Error versus Delay Tradeoffs in Clocked QCA Circuits

S. Bhanja and S. Sarkar, “Thermal Switching Error versus Delay Tradeoffs in Clocked QCA Circuits”, Volume 16, Issue 5, pp. 528 – 541, IEEE Transactions on VLSI Systems, May 2008.

@ARTICLE{4459693,
title={Thermal Switching Error Versus Delay Tradeoffs in Clocked QCA Circuits},
author={Bhanja, S. and Sarkar, S.},
journal={Very Large Scale Integration (VLSI) Systems, IEEE Transactions on},
year={2008},
month={May },
volume={16},
number={5},
pages={528-541},
abstract={The quantum-dot cellular automata (QCA) model offers a novel nano-domain computing architecture by mapping the intended logic onto the lowest energy configuration of a collection of QCA cells, each with two possible ground states. A four-phased clocking scheme has been suggested to keep the computations at the ground state throughout the circuit. This clocking scheme, however, induces latency or delay in the transmission of information from input to output. In this paper, we study the interplay of computing error behavior with delay or latency of computation induced by the clocking scheme. Computing errors in QCA circuits can arise due to the failure of the clocking scheme to switch portions of the circuit to the ground state with change in input. Some of these non-ground states will result in output errors and some will not. The larger the size of each clocking zone, i.e., the greater the number of cells in each zone, the more the probability of computing errors. However, larger clocking zones imply faster propagation of information from input to output, i.e., reduced delay. Current QCA simulators compute just the ground state configuration of a QCA arrangement. In this paper, we offer an efficient method to compute the N-lowest energy modes of a clocked QCA circuit. We model the QCA cell arrangement in each zone using a graph-based probabilistic model, which is then transformed into a Markov tree structure defined over subsets of QCA cells. This tree structure allows us to compute the N-lowest energy configurations in an efficient manner by local message passing. We analyze the complexity of the model and show it to be polynomial in terms of the number of cells, assuming a finite neighborhood of influence for each QCA cell, which is usually the case. The overall low-energy spectrum of multiple clocking zones is constructed by concatenating the low-energy spectra of the individual clocking zones. We demonstrate how the model can be used to study the tradeoff betwee- n switching errors and clocking zones.},
keywords={cellular automata, clocks, quantum computing, quantum dotsMarkov tree structure, clocked quantum-dot cellular automata circuit, delay tradeoff, four-phased clocking, graph-based probabilistic model, information transmission latency, nano-domain computing architecture, quantum-dot cellular automata model, thermal switching error},
doi={10.1109/TVLSI.2007.915448},
ISSN={1063-8210}, }

Integrating Nano-logic Knowledge Module into an Undergraduate Logic Design Course

S. Srivastava and S. Bhanja, “Integrating Nano-logic Knowledge Module into an Undergraduate Logic Design Course”, Accepted for publication in IEEE Transactions on Education, 2008.

@ARTICLE{4569869,
title={Integrating a Nanologic Knowledge Module Into an Undergraduate Logic Design Course},
author={Srivastava, S. and Bhanja, S.},
journal={Education, IEEE Transactions on},
year={2008},
month={Aug. },
volume={51},
number={3},
pages={349-355},
abstract={ This work discusses a knowledge module in an undergraduate logic design course for electrical engineering (EE) and computer science (CS) students, that introduces them to nanocomputing concepts. This knowledge module has a twofold objective. First, the module interests students in the fundamental logical behavior and functionality of the nanodevices of the future, which will motivate them to enroll in other elective courses related to nanotechnology, offered in most EE and CS departments. Second, this module can be used to let students analyze, synthesize, and apply their existing knowledge of the Karnaugh-map-based Boolean logic reduction scheme into a revolutionary design context with majority logic. Where many efforts focus on developing new courses on nanofabrication and even nanocomputing, this work is designed to augment the existing standard EE and CS courses by inserting knowledge modules on nanologic structures so as to stimulate student interest without creating a significant diversion from the course framework. },
keywords={Boolean functions, computer science education, electrical engineering education, logic design, nanoelectronicsKarnaugh-map-based Boolean logic reduction scheme, computer science students, electrical engineering students, nanocomputing concepts, nanodevices, nanofabrication, nanologic knowledge module, revolutionary design, undergraduate logic design course},
doi={10.1109/TE.2008.919660},
ISSN={0018-9359}, }

Sequential Circuit Design in Quantum-Dot Cellular Automata

Sequential Circuit Design in Quantum-Dot Cellular Automata Venkataramani, P. Srivastava, S. Bhanja, S. Dept. of Electr. Eng., Univ. of South Florida, Tampa, FL This paper appears in: Nanotechnology, 2008. NANO '08. 8th IEEE Conference on Publication Date: 18-21 Aug. 2008 On page(s): 534 - 537 Location: Arlington, TX ISBN: 978-1-4244-2103-9 Digital Object Identifier: 10.1109/NANO.2008.159 Current Version Published: 2008-09-03

Abstract In this work we present a novel probabilistic modeling scheme for sequential circuit design in quantum-dot cellular automata(QCA) technology. Clocked QCA circuits possess an inherent direction for flow of information which can be effectively modeled using Bayesian networks (BN). In sequential circuit design this presents a problem due to the presence of feedback cycles since BN are direct acyclic graphs (DAG). The model presented in this work can be constructed from a logic design layout in QCA and is shown to be a dynamic Bayesian Network (DBN). DBN are very powerful in modeling higher order spatial and temporal correlations that are present in most of the sequential circuits. The attractive feature of this graphical probabilistic model is that that it not only makes the dependency relationships amongst node explicit, but it also serves as a computational mechanism for probabilistic inference. We analyze our work by modeling clocked QCA circuits for SR F/F, JK F/F and RAM designs.