Energy-aware scheduling under reliability and makespan constraints

TL;DR

This paper addresses energy-efficient scheduling of task graphs on homogeneous processors, balancing makespan, reliability, and energy by re-executing tasks and proposing heuristics under different speed models.

Contribution

It introduces novel heuristics for tri-criteria scheduling considering re-execution and evaluates their effectiveness under continuous and VDD speed models.

Findings

Two heuristics are highly efficient and complementary.

Re-execution improves reliability without excessive energy cost.

Heuristics perform well under different speed models.

Abstract

We consider a task graph mapped on a set of homogeneous processors. We aim at minimizing the energy consumption while enforcing two constraints: a prescribed bound on the execution time (or makespan), and a reliability threshold. Dynamic voltage and frequency scaling (DVFS) is an approach frequently used to reduce the energy consumption of a schedule, but slowing down the execution of a task to save energy is decreasing the reliability of the execution. In this work, to improve the reliability of a schedule while reducing the energy consumption, we allow for the re-execution of some tasks. We assess the complexity of the tri-criteria scheduling problem (makespan, reliability, energy) of deciding which task to re-execute, and at which speed each execution of a task should be done, with two different speed models: either processors can have arbitrary speeds (continuous model), or a processor can run at a finite number of different speeds and change its speed during a computation (VDD model). We propose several novel tri-criteria scheduling heuristics under the continuous speed model, and we evaluate them through a set of simulations. The two best heuristics turn out to be very efficient and complementary.