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Algorithms, games, and the internet
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Multi-Objective Optimization Using Evolutionary Algorithms
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IEEE Transactions on Parallel and Distributed Systems
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On Task Scheduling Accuracy: Evaluation Methodology and Results
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IEEE Transactions on Computers
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Algorithmic Game Theory
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The Journal of Supercomputing
Dynamic Algorithms for Energy Minimization on Parallel Machines
PDP '08 Proceedings of the 16th Euromicro Conference on Parallel, Distributed and Network-Based Processing (PDP 2008)
A dominant predecessor duplication scheduling algorithm for heterogeneous systems
The Journal of Supercomputing
An Evolutionary Approach to Task Graph Scheduling
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I
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SOFSEM '09 Proceedings of the 35th Conference on Current Trends in Theory and Practice of Computer Science
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Theory of Computing Systems
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The Journal of Supercomputing
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Energy aware DAG scheduling on heterogeneous systems
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IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
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The Journal of Supercomputing
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The Journal of Supercomputing
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HPCA'09 Proceedings of the Second international conference on High Performance Computing and Applications
Energy efficient scheduling of parallel tasks on multiprocessor computers
The Journal of Supercomputing
Energy- and reliability-aware task scheduling onto heterogeneous MPSoC architectures
The Journal of Supercomputing
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Prescheduling algorithms are targeted at restructuring of task graphs for optimal scheduling. Task graph scheduling is a NP-complete problem. This article offers a prescheduling algorithm for tasks to be executed on the networks of homogeneous processors. The proposed algorithm merges tasks to minimize their earliest start time while reducing the overall completion time. To this end, considering each task as a player attempting to reduce its earliest time as much as possible, we have applied the idea of Nash equilibrium in game theory to determine the most appropriate merging. Also, considering each level of a task graph as a player, seeking for distinct parallel processors to execute each of its independent tasks in parallel with the others, the idea of Nash equilibrium in game theory can be applied to determine the appropriate number of processors in a way that the overall idle time of the processors is minimized and the throughput is maximized. The communication delay will be explicitly considered in the comparisons. Our experiments with a number of known benchmarks task graphs and also two well-known problems of linear algebra, LU decomposition and Gauss---Jordan elimination, demonstrate the distinguished scheduling results provided by applying our algorithm. In our study, we consider ten scheduling algorithms: min---min, chaining, A 驴, genetic algorithms, simulated annealing, tabu search, HLFET, ISH, DSH with task duplication, and our proposed algorithm (PSGT).