Development of a Robust Multiobjective Simulated Annealing Algorithm for Solving Multiobjective Optimization Problems

Structural Determination of (Al2O3)(n) (n = 1-15) Clusters Based on Graphic Processing Unit

Global optimization algorithms have been widely used in the field of chemistry to search the global minimum structures of molecular and atomic clusters, which is a nondeterministic polynomial problem with the increasing sizes of clusters. Considering that the computational ability of a graphic processing unit (GPU) is much better than that of a central processing unit (CPU), we developed a GPU-based genetic algorithm for structural prediction of clusters and achieved a high acceleration ratio compared to a CPU. On the one-dimensional (1D) operation of a GPU, taking (Al2O3)n clusters as test cases, the peak acceleration ratio in the GPU is about 220 times that in a CPU in single precision and the value is 103 for double precision in calculation of the analytical interatomic potential. The peak acceleration ratio is about 240 and 107 on the block operation, and it is about 77 and 35 on the 2D operation compared to a CPU in single precision and double precision, respectively. And the peak acceleration ratio of the whole genetic algorithm program is about 35 compared to CPU at double precision. Structures of (Al2O3)n clusters at n = 1-10 reported in previous works are successfully located, and their low-lying structures at n = 11-15 are predicted.