2018
DOI: 10.1109/tcad.2018.2789782
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An Energy-Aware Model for the Logic Synthesis of Quantum-Dot Cellular Automata

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Cited by 156 publications
(101 citation statements)
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“…In addition to this, energy analysis has also been done by using QCADesigner‐E tool, 44 which is an extension of QCADesigner tool; however, it also implements the estimation of energy dissipation of QCA circuits based on the previous studies 43,45,46 . In this, it is assumed that QCA cells form a “bath” of energy when separated for each clock cycle, and total energy dissipation is estimated as the sum of all energies of E bath , where E bath is the sum of energy transfers to the QCA bath.…”
Section: Energy Dissipation Analysismentioning
confidence: 99%
“…In addition to this, energy analysis has also been done by using QCADesigner‐E tool, 44 which is an extension of QCADesigner tool; however, it also implements the estimation of energy dissipation of QCA circuits based on the previous studies 43,45,46 . In this, it is assumed that QCA cells form a “bath” of energy when separated for each clock cycle, and total energy dissipation is estimated as the sum of all energies of E bath , where E bath is the sum of energy transfers to the QCA bath.…”
Section: Energy Dissipation Analysismentioning
confidence: 99%
“…The schematic of Fredkin and Feynman proposed gates are illustrated in Fig.5 and output waveforms of these gates are shown in Fig.6 which is simulated by using QCADesigner tool. Table 4 and Table 5 presents the QCA layout comparison between the exiting design [19] and the proposed design of the Fredkin and Feynman gate respectively. Energy dissipation can be calculated using QCA Designer-E [20] on considering the parameters shown in fig.10.…”
Section: Proposed Designmentioning
confidence: 99%
“…QCA computation is based out of electrostatic interaction that exists amongst all QCA cells [14]. Some essential components for QCA are wire, inverter, and majority gate voter (MV) [7] as appeared in Fig. 1.…”
Section: Basics Of Qcamentioning
confidence: 99%
“…In the last few years, CMOS technology has facilitated the exponential growth in increase of processing power and feature size; however, the emerging technologies are the need of hour to overcome the physical limitations of CMOS devices. Few of the recent low power technologies include Reversible logic, Adiabatic logic, and Quantum-dot Cellular Automata (QCA) technology [7]. Reversible logic circuits must have one-to-one mapping between input vectors and output vectors; thus the vector of output states can always be used to reconstruct the vector of input states.…”
Section: Introductionmentioning
confidence: 99%