A Communication Probability-Based Mapping Algorithm for Mesh-Based Network-on-Chip Systems

Abstract

Network-on-chip (NoC) mapping algorithms significantly affect NoC system performance in terms of communication cost and energy consumption. For a specific application represented by a task graph, this paper proposes an energy-efficient mapping algorithm that searches for the mapping decision with best communication locality and therefore lowest energy consumption. To this end, we formulate the concerned mapping problem as an optimization model, and propose an effective meta-heuristic algorithm to solve the formulated optimization model. During the mapping procedure, we employ a simulation-free, communication probability-based energy model to evaluate the quality of each candidate mapping. By iteratively updating the best explored mapping decision using a meta-heuristic search strategy, the mapping procedure can eventually identify an mapping decision with optimal energy efficiency in the search space. The proposed mapping algorithm has been verified on NoC systems of different sizes using a variety of benchmark applications. Simulation results demonstrate that the mapping decision produced by this algorithm achieves an up to 23% energy reduction compared with the traditional round-robin strategy.