Efficient Binary Decision Diagram Manipulation by Reducing the Number of Intermediate Nodes

The complexity of hardware systems has increased significantly in recent decades. Due to increasing user requirements, there is a need to develop more efficient data structures and algorithms to guarantee the correct behavior of such systems. A Reduced Ordered Binary Decision Diagram (BDD) is a suitable data structure as it represents all Boolean functions canonically given a variable order as well as provides algorithms for efficient manipulation. However, BDDs also have challenges: practicability depends on their minimization and there is a large memory consumption for some complex functions.To address these issues, this work investigates the number of emerged intermediate nodes that are not used in the final BDD result and presents a novel approach for efficient BDD manipulation by reducing the number of such nodes. Experiments on BDD benchmarks show that peak BDD node sizes can be significantly reduced, leading to accelerated BDD manipulation.