Energy-aware Application Mapping onto 3D Mesh-Based Network-on-Chip using Heuristic Mapping Algorithms

Network-on-chip (NoC) architectures have emerged as a potential solution for facilitating communication between processing elements (PEs) in modern multi-core systems. The design and optimization of NoC architectures are critical for achieving efficient communication, reduced energy consumption, and improved overall system performance. In this study, we investigate and compare the performance of two prominent optimization algorithms, like Genetic Algorithm (GA) and CastNet Algorithm, for 2D and 3D mesh NoC architectures. The study’s objective is to estimate these algorithms’ effectiveness in optimizing communication cost, communication energy, and CPU run time in both 2D and 3D mesh NoC architectures. Performance metrics such as communication cost, communication energy consumption, and CPU run time are measured and compared between the two algorithms and carried out on real and custom benchmark applications like MWD, VOPD and MPEG4.