A3MAP: Architecture-Aware Analytic Mapping for Networks-on-Chip

In this paper, we propose a novel and global A3MAP (Architecture-Aware Analytic Mapping) algorithm applied to NoC (Networks-on-Chip) based MPSoC (Multi-Processor System-on-Chip) not only with homogeneous cores on regular mesh architecture as done by most previous mapping algorithms but also with heterogeneous cores on irregular mesh or custom architecture. As a main contribution, we develop a simple yet efficient interconnection matrix that models any task graph and network. Then, task mapping problem is exactly formulated to an MIQP (Mixed Integer Quadratic Programming). Since MIQP is NP-hard, we propose two effective heuristics, a successive relaxation algorithm and a genetic algorithm. Experimental results show that A3MAP by the successive relaxation algorithm reduces an amount of traffic up to 5.7%, 16.1% and 7.3% on average in regular mesh, irregular mesh and custom network, respectively, compared to the previous state-of-the-art work. A3MAP by the genetic algorithm reduces more traffic up to 8.8%, 29.4% and 16.1% on average than in regular mesh, irregular mesh and custom network, respectively even if its runtime is longer.