Energy-efficient dynamic scheduling on parallel machines
HiPC'08 Proceedings of the 15th international conference on High performance computing
Energy- and performance-aware scheduling of tasks on parallel and distributed systems
ACM Journal on Emerging Technologies in Computing Systems (JETC)
Task graph pre-scheduling, using Nash equilibrium in game theory
The Journal of Supercomputing
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Static DVS (Dynamic Voltage Scaling) algorithms for DAG (Directed Acyclic Graph) execution use the estimated execution time which is, in practice, an upper bound on the actual execution time to guarantee that an application completes in a given deadline. Therefore, many tasks may complete earlier than expected during the actual execution. This allows that the extra available slack can be allocated to tasks that have not yet begun execution with the goal of reducing the total energy requirements while still meeting the deadline constraints. In this paper, we present novel dynamic algorithms for reallocating the slack to future tasks. Experimental results show that our algorithms are comparable to static algorithms applied at runtime in terms of energy minimization, but require considerably smaller computational time.