STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
A scheduling model for reduced CPU energy
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Algorithmic problems in power management
ACM SIGACT News
Policies for dynamic clock scheduling
OSDI'00 Proceedings of the 4th conference on Symposium on Operating System Design & Implementation - Volume 4
Speed scaling for weighted flow time
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Speed Scaling Functions for Flow Time Scheduling Based on Active Job Count
ESA '08 Proceedings of the 16th annual European symposium on Algorithms
Speed scaling with an arbitrary power function
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Non-clairvoyant speed scaling for batched parallel jobs on multiprocessors
Proceedings of the 6th ACM conference on Computing frontiers
Speed scaling of processes with arbitrary speedup curves on a multiprocessor
Proceedings of the twenty-first annual symposium on Parallelism in algorithms and architectures
Communications of the ACM
Non-clairvoyant batch sets scheduling: fairness is fair enough
ESA'07 Proceedings of the 15th annual European conference on Algorithms
Energy-Efficient algorithms for flow time minimization
STACS'06 Proceedings of the 23rd Annual conference on Theoretical Aspects of Computer Science
Speed scaling of tasks with precedence constraints
WAOA'05 Proceedings of the Third international conference on Approximation and Online Algorithms
Competitive online adaptive scheduling for sets of parallel jobs with fairness and efficiency
Journal of Parallel and Distributed Computing
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We consider energy-performance tradeoff for scheduling parallel jobs on multiprocessors using dynamic speed scaling. The objective is to minimize the sum of energy consumption and certain performance metric, including makespan and total flow time. We focus on designing algorithms that are aware of the jobs' instantaneous parallelism but not their characteristics in the future. For total flow time plus energy, it is known that any algorithm that does not rely on instantaneous parallelism is Ω(ln1/α P)-competitive, where P is the total number of processors. In this paper, we demonstrate the benefits of knowing instantaneous parallelism by presenting an O(1)-competitive algorithm. In the case of makespan plus energy, which is considered in the literature for the first time, we present an O(ln1-1/α P)-competitive algorithm for batched jobs consisting of fully-parallel and sequential phases. We show that this algorithm is asymptotically optimal by providing a matching lower bound.