Scheduling parallel program tasks onto arbitrary target machines
Journal of Parallel and Distributed Computing - Special issue: software tools for parallel programming and visualization
Efficient local search for very large-scale satisfiability problems
ACM SIGART Bulletin
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Proceedings of the 1992 ACM/IEEE conference on Supercomputing
Task scheduling in parallel and distributed systems
Task scheduling in parallel and distributed systems
IEEE Transactions on Parallel and Distributed Systems
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Communications of the ACM
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Partitioning and Scheduling Parallel Programs for Multiprocessors
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IEEE Software
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IEEE Transactions on Parallel and Distributed Systems
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IEEE Transactions on Parallel and Distributed Systems
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Frontiers of Computer Science: Selected Publications from Chinese Universities
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Scheduling DAGs to multiprocessors is one of the key issues in high-performance computing. Most realistic scheduling algorithms are heuristic and heuristic algorithms often have room for improvement. The quality of a scheduling algorithm can be effectively improved by a local search. In this paper, we present a fast local search algorithm based on topological ordering. This is a compaction algorithm that can effectively reduce the schedule length produced by any DAG scheduling algorithm. Thus, it can improve the quality of existing DAG scheduling algorithms. This algorithm can quickly determine the optimal search direction. Thus, it is of low complexity and extremely fast.