Kriging interpolation algorithm is of great practical significance and is widely applied to various fields of geoscience. However, Kriging interpolation would inevitably encounter the performance bottleneck when the output grid or input samples increase. Implemented with OpenCL and OpenMP, the ordinary Kriging interpolation was accelerated on heterogeneous platforms: GPU and CPU. By considering the performance difference of CPU and GPU on the densities of samples, a new load balancing method of LBCPDD (Load Balancing based on Computation Performance and Data Distribution) was proposed, in which not only hardware performance but also data distribution characteristics were taken into account. Experiment results show that LBCPDD method can effectively enhance the speed of ordinary Kriging, save memory space and improve the efficiency of memory access.