A fast static scheduling algorithm for DAGs on an unbounded number of processors
Proceedings of the 1991 ACM/IEEE conference on Supercomputing
Static scheduling algorithms for allocating directed task graphs to multiprocessors
ACM Computing Surveys (CSUR)
An Incremental Genetic Algorithm Approach to Multiprocessor Scheduling
IEEE Transactions on Parallel and Distributed Systems
A Comparison of Multiprocessor Scheduling Heuristics
ICPP '94 Proceedings of the 1994 International Conference on Parallel Processing - Volume 02
A transformation-based approach to static multiprocessor scheduling
Proceedings of the 10th annual conference on Genetic and evolutionary computation
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This paper presents a set of metrics for estimating the speedup achievable in static multiprocessor scheduling using a previously introduced Genetic Algorithm (GA) approach. This is of major importance because, although conventional wisdom suggests that metaheuristics such as GAs have the potential to improve over standard heuristics, little research has been conducted on characterizing the sorts of graphs that they should excel at. We describe several metrics and illustrate that four of them can predict the speed up with an accuracy of almost 90%.