Exploring Tabu Search Based Algorithms for Mapping and Placement in NoC-based Reconfigurable Systems

Abstract

Nowadays, the development of systems based on Networks-on-Chip (NoCs) brings big challenges to the designers due to problems of scalability, such as efficient Mapping and Placement, which are NP-hard problems. Several solutions have been proposed to solve this type of problem that is a variation of Quadratic Assignment Problems (QAP), being Tabu Search (TS) algorithms the ones showing most promising results. In NoC-based dynamically reconfigurable systems (NoC-DRSs), both mapping and placement problems present several layers of complexity due the reconfigurable scenarios. A previous work has adopted TS algorithm variations, but the best solution is not achieved with the wished high frequency. This paper introduces the original Forced Inversion (FI) Heuristic over Tabu Search algorithms for 2D-Mesh FPGA NoC-DRSs, in order to avoid local minima. Results with a series of benchmarks are presented and the performances of different approaches are quantitatively and qualitatively compared.