Parallel Algorithm of Bi-Dimensional Empirical Mode Decomposition Based on MPI

This paper investigates a parallel algorithm of bi-dimensional empirical mode decomposition(BEMD) based on MPI technique to solve the problem that it will take a long time using BEMD to decompose large-size images. At first, the running time of extreme points selecting, plane triangulation and numerical interpolation in serial program was collected, the result showed that numerical interpolation was the main part of time-comsuming as well as the key part of parallelization. Then the parallel environment was constructed in high-performance computing platform, and the envelope surface was parallelized based on MPI technique. The specific method was that triangular series were evenly divided according to the number of processes, so the entire image was divided into many sub-areas assigned to the corresponding process, then each process fitted Bezier surface and was merged by 0 process to generate the up and down envelope surface. At last, this algorithm was evaluated by some indicators such as speedup. The results show that the speedup is 20.1396 when algorithm iss executed in 30 core parallelization, and the utilization is 64.97%, the efficiency is enhanced. The scalability indicators is 1.3975 when the data amount has been 25 times of original data, showing that the algorithm has good adaptability for large amount of data.