Abstract:Aiming at the problems of poor timeliness and low efficiency of conventional data processing in large-scale GNSS network, we design a shared memory model data parallel algorithm from two dimensions of multi-period and multi-subnet respectively based on GAMIT/GLOBK software. It further implements a two-layer parallel solution for spatio-temporal integration of large-scale GNSS network in the time and space domains. The results show that the solution breaks through the limitation of traditional serial processing of GNSS data by the software, which has poor timeliness and low utilization of multi-core computing resources. In the test environment, the maximum speedup ratio is up to 19.39, which fully exploits the computing power of the computer and greatly improves the timeliness of large-scale GNSS network data processing.