  Many technologies have been developed to help improve spatial resolution of
observational images for ground-based solar telescopes, such as adaptive optics
(AO) systems and post-processing reconstruction. As any AO system correction is
only partial, it is indispensable to use post-processing reconstruction
techniques. In the New Vacuum Solar Telescope (NVST), speckle masking method is
used to achieve the diffraction limited resolution of the telescope. Although
the method is very promising, the computation is quite intensive, and the
amount of data is tremendous, requiring several months to reconstruct
observational data of one day on a high-end computer. To accelerate image
reconstruction, we parallelize the program package on a high performance
cluster. We describe parallel implementation details for several reconstruction
procedures. The code is written in C language using Message Passing Interface
(MPI) and optimized for parallel processing in a multi-processor environment.
We show the excellent performance of parallel implementation, and the whole
data processing speed is about 71 times faster than before. Finally, we analyze
the scalability of the code to find possible bottlenecks, and propose several
ways to further improve the parallel performance. We conclude that the
presented program is capable of executing in real-time reconstruction
applications at NVST.
