Energy-aware scheduling under reliability and makespan constraints

International audienceWe 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

QoS-aware predictive workflow scheduling

This research places the basis of QoS-aware predictive workflow scheduling. This research novel contributions will open up prospects for future research in handling complex big workflow applications with high uncertainty and dynamism. The results from the proposed workflow scheduling algorithm shows significant improvement in terms of the performance and reliability of the workflow applications

Energy-aware scheduling: models and complexity results

International audienceThis paper presents several energy-aware scheduling algorithms whose design is optimized for different speed models. Dynamic Voltage and Frequency Scaling (DVFS) is a model frequently used to reduce the energy consumption of a schedule, but it has negative effect on reliability. While the reliability of a schedule can sometimes be neglected (battery powered systems such as cell-phones or personal computers), it becomes extremely important when considering massively parallel architectures (petascale, exascale). In this work, we consider the problem of minimizing the energy within a makespan constraint. Additionally, we consider two models, one that takes into account a reliability constraint, and one that does not. We assume that the mapping is given, say by an ordered list of tasks to execute on each processor, and we aim at optimizing the energy consumption while enforcing a prescribed bound on the execution time. While it is not possible to change the allocation of a task, it is possible to change its speed. Rather than using a local approach such as backfilling, we consider the problem as a whole and study the impact of several speed variation models on its complexity. To improve the reliability of a schedule while reducing the energy consumption, we allow for the re-execution of some tasks. We present several results in that framework, as well as future research plans