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Particle Swarm Optimization Based Reversible Circuit Synthesis Using Mixed Control Toffoli Gates

机译:基于粒子群优化的混合控制Toffoli门可逆电路综合

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With the sustained developments in semiconductor technology, power dissipation has become a vital concern. Several low-power design alternatives have been explored and developed to overcome this problem. The relationship between information lossless computation and low-power implementations have also been explored. Reversible logic is considered as a viable alternative in this context because of its information lossless nature, and hence has become a progressive research area. Various synthesis approaches for reversible logic circuits exist in the literature. Some of the methods try to generate optimal solutions for smaller circuits, while some try to synthesize larger circuits which lead to sub-optimal solutions. The metrics that are used for evaluation are typically Gate Count (GC) and Quantum Cost (QC). In this paper we propose a particle swarm optimization (PSO) based synthesis technique that uses both positive and negative control Toffoli gates. In this iterative approach, particles representing solutions are probabilistically mutated (modified) based on a cost-based evolution approach. Experimental results show that the method can generate solutions very fast and provide optimal solutions for many of the benchmarks.
机译:随着半导体技术的不断发展,功耗已成为至关重要的问题。为了克服这个问题,已经探索和开发了几种低功耗设计替代方案。还探索了信息无损计算与低功耗实现之间的关系。在这种情况下,可逆逻辑由于其信息无损的特性而被认为是可行的替代方法,因此已成为一个渐进的研究领域。文献中存在用于可逆逻辑电路的各种合成方法。一些方法试图为较小的电路生成最优解,而另一些方法则试图合成导致次优解的较大电路。用于评估的指标通常是门计数(GC)和量子成本(QC)。在本文中,我们提出了一种基于粒子群优化(PSO)的综合技术,该技术同时使用正控制和负控制Toffoli门。在这种迭代方法中,代表解决方案的粒子基于基于成本的演化方法进行概率变异(修改)。实验结果表明,该方法可以非常快速地生成解决方案,并为许多基准测试提供了最佳解决方案。

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