Simulation Optimization with Multiple-demes Genetic Algorithms in Master-Slave Parallel Mode

Simulation optimization for complex space is realized by applying genetic algorithms (GAs) to searching the optimum parameters that satisfying the desired characteristics. It is necessarily to use parallel calculation to obtain satisfying results in a reasonable amount of time. The advantages and drawbacks of existing parallel calculation mode are analyzed. Then the multiple-demes GAs in master-slave mode (MDMS) is proposed to make progress in not only the quality of solutions but also the speedup for multiple-processors, when comparing to conventional master-slave mode, while shows less limitations on the number of processors than that of coarse-grained and neighborhood mode. The test example in semiconductor device synthesis shows the efficiency.

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