Using DVFS and task scheduling algorithms for a hard real-time heterogeneous multicore processor environment

Abstract

The usage of heterogeneous multicore processors (HMP) are rapidly spreading from data centers for large scale deployment to smart phones for the flexibility to adapt to power constraints and performance needs. In this paper, we show that for an example HMP environment, an intelligent-task scheduler is critical in improving performance and energy efficiency. The environment in this paper assumes that the tasks are independent, have hard real-time constraints, and a multicore systems where processors can be manipulated to change the clock cycle speed and power levels. Tasks are assumed to arrive aperiodically and these tasks are applications from the SPEC CPU 2006 benchmark suite. For evaluation, an actual system composed of two multicore processors which support on-the-fly DVFS is used in this study. One of our energy efficient algorithms achieved 49.9% higher task completion rate than an enhanced version of the naïve Linux scheduler while consuming only 45.3% of the energy.