Maximum Fanout-Free Window Enumeration: Towards Multi-Output Sub-Structure Synthesis

Ruofei Tang, Xuliang Zhu, Lei Chen, Xing Li, Xin Huang, Mingxuan Yuan, Jianliang Xu

Abstract: Peephole optimization is commonly used in And-Inverter Graphs (AIGs) optimization algorithms. The efficiency of these algorithms heavily relies on the enumeration process of sub-structures. One common sub-structure is the cut, known for its efficient enumeration method and single-output characteristic. However, an increasing number of optimization algorithms now target sub-structures that incorporate multiple outputs. In this paper, we explore Maximum Fanout-Free Windows (MFFWs), a novel sub-structure with a multi-output nature, as well as its practical applications and enumeration algorithms. To accommodate various algorithm execution processes, we propose two different enumeration styles: Dynamic and Static. The Dynamic approach provides flexibility in adapting to changes in the AIG structure, whereas the Static method ensures efficiency as long as the AIG structure remains unchanged during execution. We apply these methods to rewriting and technology mapping to improve their runtime performance. Experimental results on pure enumeration and practical scenarios show the scalability and efficiency of the proposed MFFW enumeration methods.

External IDs:dblp:conf/date/TangZCLHYX25