The objective of our investigation is to establish robust inverse algorithms to convert GRACE gravity and ICESat altimetry mission data into global current and past surface mass variations. To assess separation of global sources of change and to evaluate spatio-temporal resolution and accuracy statistically from full posterior covariance matrices, a high performance version of a global simultaneous grid inverse algorithm is essential. One means to accomplish this is to implement a general, well-optimized, parallel global model on massively parallel supercomputers. In our present work, an efficient parallel version of a global inverse program has been implemented on the Origin 2000 using the OpenMP programming model. In this paper, porting a sequential global code to a shared-memory computing system is discussed; several efficient strategies to optimize the code are reported; well-optimized scientific libraries are used; detailed parallel implementation of the global model is reported; performance data of the code are analyzed. Scaling performance on a shared-memory system is also discussed. The parallel version software gives good speedup and dramatically reduces total data processing time.