Energy-Aware Scheduling of Conditional Task Graphs on NoC-Based MPSoCs

Tariq, Umair Ullah
Wu, Hui
Abd Ishak, Suhaimi
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We investigate the problem of scheduling a set of tasks with individual deadlines and conditional precedence constraints on a heterogeneous Network on Chip (NoC)-based Multi-Processor System-on-Chip (MPSoC) such that the total expected energy consumption of all the tasks is minimized, and propose a novel approach. Our approach consists of a scheduling heuristic for constructing a single unified schedule for all the tasks and assigning a frequency to each task and each communication assuming continuous frequencies, an Integer Linear Programming (ILP)-based algorithm and a polynomial time heuristic for assigning discrete frequencies and voltages to tasks and communications. We have performed experiments on 16 synthetic and 4 real-world benchmarks. The experimental results show that compared to the state-of-the-art approach, our approach using the ILP-based algorithm and our approach using the polynomial-time heuristic achieve average improvements of 31% and 20%, respectively, in terms of energy reduction.
Software Development for Mobile Devices, Wearables, and the Internet-of-Things, Dynamic Voltage and Frequency Scaling Energy-Aware Scheduling Conditional Task Graphs Heterogeneous MPSoCs Non-Linear Programming
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