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Data distribution management (DDM) aims to reduce the transmission of irrelevant data between High Level Architecture (HLA) compliant simulators by taking their interesting regions into account (i.e. region matching). In a large-scale simulation, computation intensive region matching would have a direct impact on the simulation performance. To deal with the high computation cost of region matching, the whole process of region matching is offloaded to graphical processing units (GPUs) based on Computer Unified Device Architecture (CUDA). Two approaches are proposed to perform region matching in parallel. Several metrics, including different numbers of regions, different sizes of regions and different distributions of regions, are used in the experimental tests. The experimental results indicate that the performance of region matching on a GPU can be improved more than one or two orders of magnitude in comparison with that on a CPU.