Power-aware Bag-of-Tasks scheduling on heterogeneous platforms

Abstract

Energy preservation is very important nowadays. A large number of applications in science, engineering, astronomy and business analytics are classified as Bag-of-Tasks (BoT) applications. A BoT is a collection of independent tasks that do not communicate with each other during execution. BoT scheduling has been severely studied from a performance point of view. In this paper, we address the problem of energy-efficient BoT scheduling in a heterogeneous environment with the twin objectives of minimizing finish time and energy consumption. Specifically, we extend two performance-oriented scheduling policies, Min---Min and Max---Min, and propose power-aware centralized scheduling policies that incorporate a dynamic voltage/frequency scaling mechanism and can power on and off unneeded computing nodes of a heterogeneous cluster environment using dynamic power management. Additionally, to evaluate the system using a more realistic workload, high-priority tasks with and without time-constraints are also submitted. A series of simulation experiments conducted, show that we can achieve significant energy savings without affecting significantly the execution of BoTs and high-priority tasks. Additional experiments on a real system also confirmed the effectiveness of our policies.