Partitioning algorithms analysis for heterogeneous NoC based MPSoC

Several new applications have high complexity degree, requiring high processing rate and memory usage. Multiprocessor System-on-Chip (MPSoC) is a promising architecture to fulfill these requirements, due to its high parallelism that enables several tasks been executed at the same time. One problem in current heterogeneous MPSoC design is application's tasks partitioning aiming energy consumption minimization and load balance. In order to optimize partition problems, many algorithms have been applied to generate quality solutions. This work aims to analyze and compare stochastic and heuristic partitioning algorithms for obtaining low energy consumption and load balance when applied to tasks partitioning onto heterogeneous MPSoC.