Game tree search is a classical problem in the field of game theory and artificial intelligence. Focus of the system is on how to leverage massive parallelism capabilities of GPUs to accelerate the speed of game tree algorithms and propose a concise and general parallel game tree algorithm on GPUs. Comparison can be done for classical CPU-based game tree algorithms with pruning and without pruning. The paper is to identify possibilities of tasks parallelization when searching and assess game search trees that would perform better on SIMD processors of graphics cards.