Improving the iterative power of resynthesis

We present a method of improving the iterative power of resynthesis of Boolean networks in this paper. In principle it is based on iterative resynthesis of parts of the network, instead of processing the network as a whole. The parts are randomly selected, thus more variability is introduced. The process is scalable, at least as much as the state-of-the-art. We show that our method performs better than the academic state-of-the-art, the ABC tool from Berkeley. This is documented by extensive experiments on LGSynth´93 benchmark circuits.