Partitioning and Dynamic Mapping Evaluation for Energy Consumption Minimization on NoC-Based MPSoC

Eduardo Antunes,  Matheus Soares,  Alexandra Aguiar,  Sergio Johann F.,  Marcos Sartori,  Fabiano Hessel,  Cesar Marcon
PUCRS


Abstract

Software complexity has increased considerably over recent years, needing special target architectures as MPSoCs to fulfill the heavy memory, communication and computation requirements. Nevertheless, the use of MPSoCs has brought attention to the need for effective methods and tools for parallel software development. Methodologies aggregating partitioning and mapping are normally employed to fulfill the heavy requirements of such systems. This paper explores task-partitioning and processor-mapping methods on homogeneous NoC-Based MPSoC. The effect of both on application’s energy consumption is explored alone and jointly. Experiments with several synthetic and four real applications show that the energy consumption is reduced up to 18%, 31.8% or 38.1% when applying partitioning, mapping or both, respectively.