Reversible Logic Synthesis Using Gröbner Base

Hu, Jing; Lin, Yuheng; Zhang, Xiwei

doi:10.1109/eltech.2019.8839444

Cited by 1 publication

(1 citation statement)

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“…A lot of effort is evident in the literature in developing effective algorithms for reversible circuit synthesis. From the specifications of the input Boolean function to be realized, exact and heuristic based synthesis algorithms have been employed to realize the input function with low cost such as: Transformation Based Synthesis (TBS), And-Inverter Graphs (AIGs), and Lookup Table (LUT) based synthesis [8,9,10]. However, the limited scalability of such algorithms is a major barrier when synthesizing an input function with a large number of variables.…”

Section: Introductionmentioning

confidence: 99%

Reversible Logic Synthesis Using Binary Decision Diagrams With Exploiting Efficient Reordering Operators

2020

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With the continuous shrinkage of transistor sizes in very large scale integrated circuits, power consumption forms a serious concern to be tackled. With their ability to allow for zero energy dissipation, reversible circuits have been considered as promising solution to meetup with low power design requirements. Moreover, advances in their synthesis methodologies can be easily applied to quantum circuits due to the inherited reversibility of the latter. Although numerous algorithms have been proposed in the literature to synthesize reversible circuits and map them into their corresponding quantum circuits, the scalability and computational effort of such algorithms form a serious concern when synthesizing large size input functions. Binary Decision Diagram-based synthesis for reversible circuits has shown great evidence in realizing reversible circuits with low quantum cost through exploiting proper reduction rules for smaller graph size. However, the order of the variables in the decision diagram impacts its overall size, and thus, the cost of its corresponding reversible circuit. While several reordering algorithms have been proposed in this manner, their direct impact on the quantum cost has not been considered. In this paper, a Binary Decision Diagram-based algorithm for reversible circuit synthesis is proposed to synthesize reversible circuits for a given Boolean function with low quantum cost through exploiting a linearized relationship between the decision diagram size and the corresponding quantum cost. Thereafter, different decision diagram reordering algorithms have been integrated with the proposed algorithm and compared in terms of their impact on the quantum cost. Experimental results show that Genetic Algorithm-based reordering for decision diagram, supported with, cycle crossover, inverse mutation, and tournament selection, results in the least quantum cost of the output circuit if compared with other algorithms due to its property in preserving the nodes of the decision diagram in their near-optimal locations during the optimiation recipe.

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Section: Introductionmentioning

confidence: 99%