Scheduling task graphs optimally with A*
The Journal of Supercomputing
Optimal linear programming solutions for multiprocessor scheduling with communication delays
ICA3PP'12 Proceedings of the 12th international conference on Algorithms and Architectures for Parallel Processing - Volume Part I
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This paper describes a new task scheduling algorithm based on clustering. In this new approach, clustering of the tasks is achieved by applying a force model to the task graph. From an initial configuration of the task graph, forces act upon the nodes to manoeuvre them into a low energy or equilibrium state. Clusters are created from the equilibrium state and scheduled for an unlimited number of processors. This algorithm is compared in an extensive experimental evaluation to three other clustering algorithms namely, linear, single edge and dominant sequence clustering. By keeping the mapping and scheduling phases of the algorithms identical, we compare only the difference in clustering between all algorithms. Results show that force directed clustering is very promising, especially for a limited number of processors.