High-performance parallel image reconstruction for the New Vacuum Solar Telescope

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), a 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 the C language using the Message Passing Interface (MPI) and is optimized for parallel processing in a multiprocessor 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 reconstruction applications in real-time at NVST.