In this work, we present the experimental assessment of a parallel framework that allows to reduce the energy consumption of MPSoC platforms running hard real-time systems. We use a power-aware Fork-Join task model based on primitives of the OpenMP library, a scheduling algorithm to execute such model and a schedulability test from the literature to ensure that all timing requirements are met while the energy consumption of the whole system is reduced. Practical experiments involving the deployment of OpenMP applications on a parallel embedded real-time operating system and power measurements on a MPSoC board through an oscilloscope probe show that intra-task parallelism helps to reduce the total energy consumption of the system in a realistic setting.
['Antonio Paolillo', 'Paul Rodriguez', 'Nikita Veshchikov', 'Joël Goossens', 'Ben Rodriguez']
Quantifying Energy Consumption for Practical Fork-Join Parallelism on an Embedded Real-Time Operating System