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Optimizing a parameterized message-passing metaheuristic scheme on a heterogeneous cluster
José-Matías Cutillas-Lozano 1 - Personal Name
Domingo Giménez 1 - Personal Name
This paper studies the development of message- passing parameterized schemes of metaheuristics and the use of auto-tuning techniques to optimize their execution time. Previous parameterized schemes on shared-memory are extended with new metaheuristic-parallelism parameters representing the migration frequency, the size of the migra- tion and the number of processes. An optimization Problem of Electricity Consumption in Exploitation of Wells is used as test case. Experimental results in heterogeneous systems are reported for this problem, and the influence of the parallelism parameters is studied. The message-passing scheme proves to be preferable to the shared-memory scheme in terms of execution time, giving similar results for the goodness of the solutions. In the executions in a heterogeneous cluster, the best experimental results are obtained in terms of speed-up and quality of the solution by mapping a number of processes close to the value of the population size, and considering the relative speeds of the components of the heterogeneous sys-tem. Furthermore, optimized execution times can be achieved with auto-tuning techniques based on theoretical–empirical models of the execution time.
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| EB00000002364K | Available |
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Parameterized metaheuristic schemes
Parallel metaheuristics
Message-passing metaheuristic schemes
Heterogeneous computing
Auto-tuning
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