A MPI + OpenMP + CUDA Hybrid Parallel Scheme for MT Occam Inversion

Abstract

To improve the performance of the Magnetotelluric Occam inversion, by in-depth analysis of the sequential algorithm, we develop a multi-level hybrid parallel computing scheme for MT Occam inversion based on MPI+OpenMP+CUDA and implement it on a small heterogeneous cluster. We implement the parallel algorithm for solving linear equations with Gauss elimination, jacobian matrix, cross-product matrix calculations and Cholesky decomposition. Through reasonable decomposition, combination and mapping of computing tasks, the scheme reduces the data traffic and realizes the purpose of load balancing. By changing the matrix storage order ， the memory access speed is significantly increased. The scheme is tested with multiple synthesis data from 2-D theoretical models and the execution efficiency of sequential code and parallel code on a 4 nodes PC cluster is comparatively analyzed. The test results show that the realization of this hybrid parallel algorithm is feasible and efficient. Compared with the sequential code and pure message passing algorithm, the inversion speed is obviously increased.