GPU acceleration for Sudoku solution with genetic operations

In this paper, we use the problem of solving Sudoku puzzles to demonstrate the possibility of achieving practical processing time through the use of GPUs for parallel processing in the application of genetic computation to problems for which the use of genetic computing has not been investigated before because of the processing time problem. To increase accuracy, we propose a genetic operation that takes building-block linkage into account. As a parallel processing model for higher performance, we use a multiple-population coarse-grained GA model to counter initial value dependence under the condition of a limited number of individuals. Specifically, we show that it is possible to reach a solution in a few seconds of processing time with a correct solution rate of 100%, even for extremely difficult problems by parallel processing of genetic computation on a GeForce GTX 460, a commercial GPU produced by the NVIDIA Corporation.