Filtreler
Memetic algorithms for parallel code optimization

Özcan, E. | Onbaşioğlu, E.

Article | 2007 | International Journal of Parallel Programming35 ( 1 ) , pp.33 - 61

Discovering the optimum number of processors and the distribution of data on distributed memory parallel computers for a given algorithm is a demanding task. A memetic algorithm (MA) is proposed here to find the best number of processors and the best data distribution method to be used for each stage of a parallel program. Steady state memetic algorithm is compared with transgenerational memetic algorithm using different crossover operators and hill-climbing methods. A self-adaptive MA is also implemented, based on a multimeme strategy. All the experiments are carried out on computationally intensive, communication intensive, and mi . . .xed problem instances. The MA performs successfully for the illustrative problem instances. © Springer Science+Business Media, LLC 2007 Daha fazlası Daha az

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