Error Bounded Exact BDD Minimization in Approximate Computing
Saman Froehlich, Daniel J. Grosse, Rolf Drechsler · 2017
The Error Bounded Exact BDD Minimization (EBEBM) problem arises in approximate computing when one is trying to find a functional approximation with a minimal representation in terms of BDD size for a single output function with respect to a given error bound. In this paper we present an exact algorithm for EBEBM. This algorithm constructs a BDD representing all functions, which meet the restrictions induced by the given error bound. From this BDD we can derive an optimal solution. We compute the exact solutions for all functions with up to 4 variables and varying error bounds. Based on the results we demonstrate the benefit of our approachfor evaluating the quality of heuristic approximation algorithms.