In this paper, the characteristics of the typical two models of parallel genetic algorithms are compared. Those models are the coarse grained model and the micro grained model. Especially, the parallel eficiency and the total calculation time on PC clusters that are build with commodity hardware are examined. The characteristics are examined through the numerical examples. There are two major characteristics in the coarse grained model. One of them is the network cost is very small. The other is the fact that the necessary number of iteration is smaller than that of the model of the macro grained model. On the other hand, in the micro grained model, the ideal parallel efficiency cannot be reached to 100 %. Therefore, it is concluded the coarse grained model is suitable for PC cluster systems.
In the island model the network traffic is not heavy because iterations of the sequential algorithm are performed in each processor REF .
The differences of parallel efficiency between the two models of parallel genetic algorithms on PC cluster systems
Proceedings Fourth International Conference/Exhibition on High Performance Computing in the Asia-Pacific Region
Proceedings Fourth International Conference/Exhibition on High Performance Computing in the Asia-Pacific Region
Computer Science