A Library-Based Synthesis Methodology for Reversible Logic

TL;DR

This paper introduces a novel library-based synthesis methodology for reversible circuits, utilizing cycle decomposition, graph matching, and optimization steps to improve synthesis efficiency and cost-effectiveness.

Contribution

It presents a new cycle-based synthesis framework with decomposition and assignment algorithms, enhancing the construction of reversible circuits from irreversible functions.

Findings

Effective cycle decomposition for large cycles.

Optimized cycle assignment via graph matching.

Improved synthesis cost through post-optimization.

Abstract

In this paper, a library-based synthesis methodology for reversible circuits is proposed where a reversible specification is considered as a permutation comprising a set of cycles. To this end, a pre-synthesis optimization step is introduced to construct a reversible specification from an irreversible function. In addition, a cycle-based representation model is presented to be used as an intermediate format in the proposed synthesis methodology. The selected intermediate format serves as a focal point for all potential representation models. In order to synthesize a given function, a library containing seven building blocks is used where each building block is a cycle of length less than 6. To synthesize large cycles, we also propose a decomposition algorithm which produces all possible minimal and inequivalent factorizations for a given cycle of length greater than 5. All decompositions contain the maximum number of disjoint cycles. The generated decompositions are used in conjunction with a novel cycle assignment algorithm which is proposed based on the graph matching problem to select the best possible cycle pairs. Then, each pair is synthesized by using the available components of the library. The decomposition algorithm together with the cycle assignment method are considered as a binding method which selects a building block from the library for each cycle. Finally, a post-synthesis optimization step is introduced to optimize the synthesis results in terms of different costs.