在CentOS下实现Fortran并行计算,通常有两种主要方法:使用OpenMP进行多线程并行计算,以及使用MPI进行分布式内存并行计算。以下是具体实现步骤和示例代码:
OpenMP是一种支持多平台共享内存并行编程的API。以下是一个简单的OpenMP示例,展示如何在Fortran中使用OpenMP进行并行计算:
program openmp_example use omp_lib implicit none integer :: i, n real, allocatable :: array(:), result(:) integer :: num_threads, thread_id n = 1000000 allocate(array(n), result(n)) ! 初始化数组 array = 1.0 ! 设置并行区域 num_threads = omp_get_max_threads() print *, "Using", num_threads, "threads for parallel computation." !omp parallel do private(thread_id, i) do i = 1, n thread_id = omp_get_thread_num() result(i) = array(i) * 2.0 end do !omp end parallel do ! 验证结果 if (all(result == 2.0)) then print *, "Parallel computation successful." else print *, "Error in parallel computation." end if deallocate(array, result) end program openmp_example
MPI是一种用于分布式内存系统并行计算的标准。以下是一个简单的MPI示例,展示如何在Fortran中使用MPI进行并行计算:
program mpi_example use mpi implicit none integer :: ierr, rank, size, n, i real, allocatable :: array(:), local_sum, global_sum integer, parameter :: root = 0 call MPI_Init(ierr) call MPI_Comm_rank(MPI_COMM_WORLD, rank, ierr) call MPI_Comm_size(MPI_COMM_WORLD, size, ierr) n = 1000000 / size allocate(array(n)) array = real(rank) * 1.0 ! 每个进程计算部分和 local_sum = 0.0 do i = 1, n local_sum = local_sum + array(i) end do ! 所有部分和相加得到全局和 call MPI_Reduce(local_sum, global_sum, 1, MPI_REAL, MPI_SUM, root, MPI_COMM_WORLD, ierr) if (rank == root) then print *, "Global sum:", global_sum end if deallocate(array) call MPI_Finalize(ierr) end program mpi_example
gfortran -fopenmp -o openmp_example openmp_example.f90 ./openmp_example
mpif90 -o mpi_example mpi_example.f90 mpirun -np <core-count> ./mpi_example
通过上述步骤和示例代码,您可以在CentOS系统下使用Fortran实现并行计算。根据具体需求选择OpenMP或MPI,并进行相应的编译和运行。