The development of efficient methods for mapping applications on heterogeneous multicore platforms is a key issue in the field of embedded systems. In this article, a novel approach based on the Logic-Based Benders decomposition principle is introduced for mapping complex applications on these platforms, aiming at optimizing their execution time. To provide optimal solutions for this problem in a short time, a new hybrid model that combines Integer Linear Programming (ILP) and Constraint Programming (CP) models is introduced. Also, to reduce the complexity of the model and its solution time, a set of novel techniques for generating additional constraints called Benders cuts is proposed. An extensive set of experiments has been performed in which synthetic applications described by Directed Acyclic Graphs (DAGs) were mapped to a number of heterogeneous multicore platforms. Moreover, experiments with DAGs that correspond to two real-life applications have also been performed. Based on the experimental results, it is proven that the proposed approach outperforms the pure ILP model in terms of the solution time and quality of the solution. Specifically, the proposed approach is able to find an optimal solution within a time limit of 2 hours in the vast majority of performed experiments, while the pure ILP model fails. Also, for the cases where both methods fail to find an optimal solution within the time limit, the solution of the proposed approach is systematically better than the solution of the ILP model.
['Andreas Emeretlis', 'George Theodoridis', 'Panayiotis Alefragis', 'Nikolaos S. Voros']
A Logic-Based Benders Decomposition Approach for Mapping Applications on Heterogeneous Multicore Platforms