Abstract: Disturbing gravity gradient is the second derivative of disturbing potential, containing more highfrequency information of the changing and irregular earth gravity field with respect to other sort of gravity data. Using highorder spherical harmonic coefficient model to obtain largescale and highresolution disturbing gravity gradient data is timeconsuming and inefficient caused by repetitive computation. To solve this problem, a simplified method was proposed which computed and saved some intermediate variables that can be converted into global and local parameters separately. Based on this method, a fast heterogeneous parallel algorithm for calculating disturbing gravity gradient tensors was proposed. The parallel calculation of gradient tensor on GPU was realized by CUDA (compute unified device architecture)，and by using this algorithm, a full tensor map of the global disturbing gravity gradient with 5′×5′ resolution was quickly constructed based on the 2 190order EIGEN6C4 model, which shows the numerical characteristics of the disturbing gravity gradient on a global scale and its correlation with changes in topography and Earth’s mass distribution. The reliability of this algorithm was validated by checking whether the calculated Txx, Tyy  and Tzz met the Laplace constrain, and the computational efficiency was compared with the traditional serial algorithm. The experimental result shows that using this algorithm can reduce time consumption by 90% and increase computational efficiency by 60 times.

Key words: Earth gravity field, disturbing gravity gradient, heterogeneous parallelism, spherical harmonic coefficient model, GPU