Research On Parallel Algorithm For Three Dimentional Forward Modeling Of DC Resistivity Method And Magnetotelluric Method Based On MPI And GPU

Electromagetic exploration is an important branch of exploration geophysics methods and has two categories. One is conductive electromagnetic method; another one is inductive electromagnetic method. The main method of conductive electromagnetic method is direct currency method. The main method of inductive electromagnetic method is electromagetic sounding method, which is representative of magnetotelluric method. With the development of electromagnetic exploration technology, especially the update of three-dimensional forward modeling and inversion technology, there are more and more large-scale computation problems. So it urgently needs to apply the latest technology of parallel computing to the interpretation of electromagnetic exploration.Both of three-dimensional forward modeling of DC method and magnetotelluric method need to solve linear equations with large sparse symmetric coefficient matrix. It takes long computation time and reduces the computation efficiency for forward modeling, while reducing the efficiency of three-dimensional inversion. Because there is parallelism in both of three-dimensional forward modeling computation of DC method and magnetotelluric method, this topic uses the latest technology of parallel computing based on GPU combined with parallel computing based on MPI to parallelize traditional three-dimensional forward modeling serial algorithms of DC method and magnetotelluric method. Parallel computing based on MPI coarse-grainedly distributes computing tasks to each computing node, and then each computing node use parallel computing based on GPU to fine-grainedly solve linear equations with large sparse symmetric coefficient matrix. Let many stream processors of GPU execute heavy computing tasks.For DC method, parallel computing based on MPI coarse-grainedly distributes several data sets collected by measuring electrode based on moving point source which is equivalent to several different positions of point source to each computing node, and then each computing node fine-grainedly parallelizes the process of solving linear equations with large sparse symmetric coefficient matrix using conjugate gradient method, distributing to many stream processors of GPU to execute computing tasks.For magnetotelluric method, because all the processed data are based on a number of different frequencies, so parallel computing based on MPI coarse-grainedly distributes all these frequencies which are for processing data to each computing node, and then each computing node fine-grainedly parallelizes the method of solving linear equations with large sparse symmetric coefficient matrix using conjugate gradient method, distributing to many stream processors of GPU to execute computing tasks.Finally, we verify the validity and performance of both of the three-dimensional parallel algorithms of DC method and magnetotelluric method by experiments choosing different models. Using this new parallel computing mode can achieve a greater level of parallelism and considerably improve both of three dimensional forward modeling algorithms of DC method and magnetotelluric method.