Grid parallel preprocessing method based on MPI

Abstract

The invention discloses a grid parallel preprocessing method based on MPI. The grid parallel preprocessing method based on the MPI comprises the following steps: giving a partition number of grids in a computation area; starting MPI multiprocessing, setting a process number; judging whether the process number is equal to the partition number; opening grid files if the process number is equal to the partition number, reading grid cell information files by a main process, initially and averagely assigning the grid cells to each process, creating an adjacent array of each process; otherwise, restarting the MPI multiprocessing; invoking ParMETIS by each process to divide the grids; reading the grid cell information by blocks into the array through each process, setting an index position of the array; looping through the grid cell information files by each process, judging whether the difference of subtracting the index position number of the array from the array length is less than the length of the grid cell information; if the answer is yes, reading data of the grid cell information files and filling the array with the data; otherwise, assigning array elements to the grid cells; judging whether the partition number of the grid cell is equal to the process number; if the answer is yes, storing the grid cell information into a process file; otherwise, keeping judging circularly.

Description

technical field [0001] The invention relates to a parallel preprocessing technology, in particular to a grid parallel preprocessing method. Background technique [0002] In the field of scientific and engineering computing, the grid is of great significance to the numerical solution of various differential equations, and the grid distribution is the basic environment for solving calculations. The solution of differential equations mainly includes two steps of numerical discretization and solution of algebraic equations. When the discretization method is determined, the grid distribution information can directly reflect the logical structure of algebraic equations solution vector and coefficient matrix. With the widespread application of parallel computing, grid plays a very important role in the parallel solution of differential equations. For distributed parallel computing, the parallel execution of grid division based on domain decomposition and distributed storage of gri...

AI Technical Summary

Problems solved by technology

[0004] Data segmentation and grid information management are the main time-consuming stages of grid parallel preprocessing. The existing technology is time-consuming and inefficient in the data segmentation and grid information management stages of grid preprocessing.

For grid division, the existing multi-layer recursive bisection, row and column division and other technologies are slow and the division quality is not ideal

Most of the existing grid preprocessing schemes are serially executed, which can only be executed on a single CPU core. At the same time, most of the grid files are traversed serially, and the speed is relatively slow.

Moreover, existing grid preprocessing schemes mostly store grid data files in one or a few files. When the data scale is large, I / O file read and write congestion will occur, which affects the scale of grid processing data. and speed

Images