Document Type
Conference Proceeding
Publication Date
8-2018
Abstract
NPN classification of Boolean functions is a powerful technique used in many logic synthesis and technology mapping tools in FPGA design flows. Computing the canonical form of a function is the most common approach of Boolean function classification. In this paper, a novel algorithm for computing NPN canonical form is proposed. By exploiting symmetries under different phase assignments and higher-order symmetries of Boolean functions, the search space of NPN canonical form computation is pruned and the runtime is dramatically reduced. The algorithm can be adjusted to be a slow exact algorithm or a fast heuristic algorithm with lower quality. For exact classification, the proposed algorithm achieves a 30× speedup compared to a state-of-the-art algorithm. For heuristic classification, the proposed algorithm has similar performance as the state-of-the-art algorithm with a possibility to trade runtime for quality.
Recommended Citation
X. Zhou, L. Wang, P. Zhao, and A. Mishchenko, "Fast adjustable NPN classification using generalized symmetries", Proc. FPL'18, 2018. doi: 10.1109/FPL.2018.00008
Copyright
IEEE
Comments
This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Proceedings of the 28th International Conference on Field Programmable Logic and Applications (FPL) in 2018. The definitive publisher-authenticated version is available online at DOI: 10.1109/FPL.2018.00008.