Research on Parallel Algorithms for uv-faceting Imaging

The uv-faceting imaging is one of the widely used large field of view imaging technologies, and will be considered for the data processing on the low frequency array in the first stage of the Square Kilometre Array (SKA1). Due to the raw data scale of SKA1 is unprecedentedly large, and the efficiency of data processing directly using original uv-faceting imaging will be very low. Therefore, a uv-faceting imaging algorithm based on the MPI (Message Passing Interface)+OpenMP (Open Multi-Processing) and a uv-facteing imaging algorithm based on the MPI+CUDA (Compute Unified Device Architecture) are proposed. The most time-consuming data reading and gridding in the algorithm are optimized in parallel. The verifiable results show that the results of the proposed two algorithms are basically the same as those obtained by the current mainstream data processing software (Common Astronomy Software Applications, CASA), which indicates that the proposed two algorithms are basically correct. Further analysis of the accuracy and total running time shows that the MPI+CUDA method is better than the MPI+OpenMP method in both correct rate and running speed. The performance test results show that the proposed algorithms are effective and have certain scalability.